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Pharmacokinetic/Pharmacodynamic Characterization of Ceftobiprole

Permanent Link: http://ufdc.ufl.edu/UFE0024280/00001

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Title: Pharmacokinetic/Pharmacodynamic Characterization of Ceftobiprole
Physical Description: 1 online resource (166 p.)
Language: english
Creator: Barbour, April
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Pharmacy -- Dissertations, Academic -- UF
Genre: Pharmaceutical Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Ceftobiprole is a novel-cephalosporin with broad-spectrum activity against both Gram-positive and Gram-negative pathogens, including activity against numerous resistant species such as methicillin-resistant Staphylococcus aureus (MRSA) and penicillin-resistant Streptococcus pneumonia (PRSP). The lead indication of ceftobiprole is complicated skin and skin structure infections. Therefore, to further characterize the pharmacokinetics, the concentration in the interstitial space fluid of skeletal muscle and subcutaneous adipose tissue after a single 500 mg 2 hour intravenous infusion was determined by microdialysis and compared to plasma concentrations. To characterize the pharmacodynamics, a time-kill experiment was performed with MRSA to evaluate the pharmacodynamic activity of ceftobiprole over time. Pharmacokinetic and pharmacodynamic models were developed and simulations were performed to evaluate the generally recommended dosing regimen of ceftobiprole, a 500 mg 2 hour i.v. infusion every 8 hours. It was found that this dosing regimen is efficacious at the site of action based on two different pharmacodynamic endpoints, whether the time the free concentration remained above the MIC for at least 40% of the dosing interval and whether at least a 1-log bacterial kill was achieved at 24 hours.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by April Barbour.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Derendorf, Hartmut C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024280:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024280/00001

Material Information

Title: Pharmacokinetic/Pharmacodynamic Characterization of Ceftobiprole
Physical Description: 1 online resource (166 p.)
Language: english
Creator: Barbour, April
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Pharmacy -- Dissertations, Academic -- UF
Genre: Pharmaceutical Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Ceftobiprole is a novel-cephalosporin with broad-spectrum activity against both Gram-positive and Gram-negative pathogens, including activity against numerous resistant species such as methicillin-resistant Staphylococcus aureus (MRSA) and penicillin-resistant Streptococcus pneumonia (PRSP). The lead indication of ceftobiprole is complicated skin and skin structure infections. Therefore, to further characterize the pharmacokinetics, the concentration in the interstitial space fluid of skeletal muscle and subcutaneous adipose tissue after a single 500 mg 2 hour intravenous infusion was determined by microdialysis and compared to plasma concentrations. To characterize the pharmacodynamics, a time-kill experiment was performed with MRSA to evaluate the pharmacodynamic activity of ceftobiprole over time. Pharmacokinetic and pharmacodynamic models were developed and simulations were performed to evaluate the generally recommended dosing regimen of ceftobiprole, a 500 mg 2 hour i.v. infusion every 8 hours. It was found that this dosing regimen is efficacious at the site of action based on two different pharmacodynamic endpoints, whether the time the free concentration remained above the MIC for at least 40% of the dosing interval and whether at least a 1-log bacterial kill was achieved at 24 hours.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by April Barbour.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Derendorf, Hartmut C.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024280:00001


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PHARMACOKINETIC/PHARMACODYNAMIC CHARACTERIZATION OF CEFTOBIPROLE By APRIL MARIE BARBOUR A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009 1

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2009 April Marie Barbour 2

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To my father 3

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ACKNOWLEDGEMENTS I would like to express my great appreciation to Dr. Hart mut Derendorf for his support and guidance throughout my graduate career. Working with Dr. Derendorf has been an incredible learning experience and I ha ve truly enjoyed my time at UF. I would like to thank the me mbers of my supervisory committee, Dr. Guenther Hochhaus, Dr. Jeffrey Hughes, and Dr. Kenneth Rand, for their support and guidance. I would like to thank the staff of the General Clinical Research Center and Shands Hospital for their support duri ng the microdialysis study. I would also like to thank the administrative staff of the Department of Pharmaceutics, especially Mrs. Khan, Mrs. Ke irnan-Sanchez, and Mr. Rhoden. Finally, I would like to thank all the graduate students and post-docs in the Department of Pharmaceutics, especially Stepha n, Sab, Navin, and Martina. 4

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TABLE OF CONTENTS page ACKNOWLEDGEMENTS .............................................................................................................4LIST OF TABLES ...........................................................................................................................9LIST OF FIGURES .......................................................................................................................11ABSTRACT ...................................................................................................................... .............13CHAPTER 1 CLASS-DEPENDENT RELEVANCE OF TISSUE DISTRIBUTION IN THE INTERPRETATION OF ANTIMICROBIAL PK/PD INDICES ..........................................14Hypothesis and Specific Aims ................................................................................................14Hypothesis ..............................................................................................................................14Specific Aims ..........................................................................................................................14Introduction .................................................................................................................. ...........15Beta-lactams .................................................................................................................. .........17Aminoglycosides ............................................................................................................... .....18Fluoroquinolones .............................................................................................................. ......19Oxazolidinones ................................................................................................................ .......20Tetracyclines and Glycylcyclines ...........................................................................................21Macrolides, Ketolides, Azalides .............................................................................................22Glycopeptides ................................................................................................................. ........23Conclusion .................................................................................................................... ..........242 APPLICATIONS OF ANTIMICROBIAL PHARMACOKINETICS/PHARMACODYNAMICS ..........................................................31Characterization of Antimicrobial Pharmacokinetics/Pharmacodynamics ............................31Pharmacodynamic Models ......................................................................................................33One-Population Models ...................................................................................................33Two-Population Models with Persistent Bacteria ...........................................................34Two-Population Models with Resistant Bacteria ............................................................36Adaptation Models ..........................................................................................................38Summary ....................................................................................................................... ..........393 CEFTOBIPROLE: A NOVEL CEPHAL OSPORIN WITH ACTIVITY AGAINST GRAM-POSITIVE AND GRAM-NEGATIV E PATHOGENS, INCLUDING MRSA ........46Introduction .................................................................................................................. ...........46Pharmacokinetics .............................................................................................................. ......47Plasma Concentrations ....................................................................................................47Protein Binding ................................................................................................................48 5

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Volume of Distribution ....................................................................................................48Tissue Distribution ..........................................................................................................48Clearance and Metabolism ..............................................................................................49Half-life ..................................................................................................................... ......49Pharmacokinetics in Patients with Complicat ed Skin and Skin Structure Infections .....50Drug Administration ........................................................................................................50Adverse Events ................................................................................................................51Pharmacodynamics .............................................................................................................. ...52In Vitro Activity ..............................................................................................................52Resistance Studies ...........................................................................................................53In Vivo -Animal Studies ...................................................................................................53In Vivo-Pivotal Studies ...................................................................................................55Pharmacokinetics/Pharmacodynamics (PK/PD) ....................................................................56PK/PD Characterization ..................................................................................................56PK/PD for Dose Selection ...............................................................................................56Summary ....................................................................................................................... ..........574 IN VITRO MICRODIALYSIS OF CEFTOBIPROLE ...........................................................65Objective ..................................................................................................................... ............65Chemicals and Equipment ......................................................................................................6 5Test Article ......................................................................................................................65Reagents ...................................................................................................................... ....65Equipment ..................................................................................................................... ...65Reagent Preparation ................................................................................................................66Ceftobiprole Standards and Qu ality Control Solutions ...................................................66HPLC Mobile Phase ........................................................................................................660.1% Formic Acid in DMSO ...........................................................................................67Sample Preparation ............................................................................................................ .....67Calibration Solutions for Microdialysis ..........................................................................67Dialysate Samples ...........................................................................................................67Apparatus Setup ......................................................................................................................67Sample Analysis .....................................................................................................................68HPLC/UV Set Up ............................................................................................................68HPLC Pump Conditions ..................................................................................................68Autosampler Conditions ..................................................................................................68Detector Conditions .........................................................................................................69Analysis Procedure ..........................................................................................................69Microdialysis ..........................................................................................................................69Introduction .................................................................................................................. ...69Extraction Efficiency Method (EE) .................................................................................70Retrodialysis Method (RD) .............................................................................................71Results .....................................................................................................................................71Method Validation Results ..............................................................................................71In vitro Microdialysis Results .........................................................................................72Conclusions .............................................................................................................................72 6

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5 HPLC/UV METHOD VALIDATION OF CEFTOBIPROLE IN LACTATED RINGERS SOLUTION .........................................................................................................76Objective ..................................................................................................................... ............76Validation Procedure ..............................................................................................................76Results .....................................................................................................................................77Reproducibility of the Calibration Curve Parameters .....................................................77Lower Limit of Quantification ........................................................................................77Intra-batch Variability for Quality Control Samples .......................................................77Inter-batch Variability for Quality Control Samples .......................................................78Freeze-thaw Stability .......................................................................................................78Stability at Room Temperature .......................................................................................79Refrigeration Stability of QCs .........................................................................................80Freezer (long-term ) Stability ...........................................................................................80Robustness .................................................................................................................... ...80Chemicals and Equipment ......................................................................................................8 1Test Article ......................................................................................................................81Reagents ...................................................................................................................... ....81Equipment and Disposables ............................................................................................81Reagent Preparation ................................................................................................................82Ceftobiprole Stock Standard Solution .............................................................................82Ceftobiprole Working St andard Solutions ......................................................................82Ceftobiprole QC Samples ................................................................................................82HPLC Mobile Phase ........................................................................................................830.1% Formic Acid in DMSO ...........................................................................................83HPLC Wash Solution ......................................................................................................83Sample Preparation ............................................................................................................ .....83Assay Procedure ............................................................................................................... ......84HPLC/UV Set Up ............................................................................................................84HPLC Pump Conditions ..................................................................................................84Autosampler Conditions ..................................................................................................84Detector Conditions .........................................................................................................84Analysis Procedure ..........................................................................................................84System Suitability ............................................................................................................ 85Summary ....................................................................................................................... ..........856 SOFT TISSUE PENETRATION OF CEFTOBIPROLE IN HEALTHY VOLUNTEERS DETERMINED BY IN VIVO MICRODIALYSIS ....................................98Introduction .................................................................................................................. ...........98Materials and Methods ...........................................................................................................99Healthy Volunteers ..........................................................................................................99Microdialysis .................................................................................................................100Study Design .................................................................................................................100Analysis Methods ..........................................................................................................101Results ...................................................................................................................................103Discussion .................................................................................................................... .........104 7

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7 PHARMACODYNAMC PROPERTIES OF CEFTOBIPROLE AGAINST MRSA ..........109Introduction .................................................................................................................. .........109Materials and Methods .........................................................................................................110Study Conduct ...............................................................................................................110Preparation of Ceftobiprole ...........................................................................................110Preparation of Sterile Br oth and Normal Saline ............................................................110Inoculum Preparation ....................................................................................................111MIC Determination .......................................................................................................111In Vitro Infection Model with Consta nt Antibiotic Concentration ...............................111Bacterial Quantification .................................................................................................112Stability of Ceftobiprole in Mueller Hinton Broth (MHB) ...........................................112Data Analysis ........................................................................................................................113Results ...................................................................................................................................113MIC Determination .......................................................................................................113Time-Kill Curves ...........................................................................................................113Stability of Ceftobiprole in MHB ..................................................................................113Pharmacodynamic Model Development .......................................................................114Pharmacodynamic Model Validation ............................................................................116Conclusions ...........................................................................................................................1168 POPULATION PHARMACOKINETICS AND MONTE CARLO SIMULATIONS FOR THE EVALUTION OF THE CURRENTLY RECOMMENDED DOSING REGIMEN OF CEFTOBIPROLE ........................................................................................124Introduction .................................................................................................................. .........124Materials and Methods .........................................................................................................125Population Pharmacokinetic Model Development ........................................................125Probability of Target Attainment ...................................................................................125Results ...................................................................................................................................126Population Pharmacokinetic Model Development ........................................................126Probability of Target Attainment ...................................................................................128Conclusions ...........................................................................................................................1299 CONCLUSIONS ................................................................................................................. .145LIST OF REFERENCES .............................................................................................................149BIOGRAPHICAL SKETCH .......................................................................................................166 8

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LIST OF TABLES Table page 1-1 Volume of distribution of antimicrobials by class determined from clinical studies ........30 2-1 Definition of each symbol used throughout the chapter ....................................................45 3-1 In vitro activity of Ceftobiprole against common skin and soft tissue and respiratory pathogens ...........................................................................................................................59 3-2 Pharmacokinetics following single a nd multiple doses presented as mean .......................60 3-3 Most common adverse events in healthy volunteers and patients .....................................61 4-1 Standard preparation of BAL9141 .....................................................................................73 4-2 Method validation accuracy and precision ........................................................................74 4-3 In vitro microdialysis results ..............................................................................................75 5-1 Intra-batch variability of quality control samples ..............................................................86 5-2 Inter-batch variability of quality control samples ..............................................................87 5-3 Freeze/thaw stability of QCs ..............................................................................................88 5-4 Freeze/thaw stability of ceftobiprole stock standard solution ............................................89 5-5 Room temperature stability of ceftobipr ole stock standard solution after 5.5 hours ........90 5-6 Room temperature stability of ceftobiprole QCs after 3 hour ...........................................91 5-7 Refrigeration (4C) stability of QC samples over 24 and 48 hours ...................................92 5-8 Freezer stability of QC samples over 32 days ...................................................................93 5-9 Interbatch variability of ceftobiprole using a different column to test robustness ............94 5-10 Standard preparation of ceftobiprole .................................................................................95 5-11 Quality control sample preparation of ceftobiprole ...........................................................96 6-1 Noncompartmental pha rmacokinetic analysis .................................................................107 6-2 Soft tissue penetration of four ce phalosporins determined by microdialysis ..................108 7-1 Pharmacodynamic parameters based on time-kill curves and CDD Results ...................117 9

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8-1 Results from bootstrap of base model ..............................................................................140 8-2 Results from bootstra p of covariate model ......................................................................141 8-3 Probability targ et attainment for f T>MIC of >30% at steady state .....................................142 8-4 Probability target attainment f T>MIC of >40% at steady state ...........................................143 8-5 Probability of target attainme nt based on 1-log kill at 24 hours ......................................144 10

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LIST OF FIGURES Figure page 1-1 Time-kill curves with Pseudomonas aeruginosa (ATCC 27853) against tobromycin, ciprofloxacin, and ticarcillin ..............................................................................................26 1-2 Time-kill curves for Streptococcus pyogenes against a glycopeptide, two betalactams, a fluoroquinolone, and a macrolide .....................................................................27 1-3 Both the time above MIC and AUC corre late well to the efficacy of tigecycline against Streptococcus pneumoniae 1199 in the neutropenic murine thigh infection model compared to the Cmax ..............................................................................................28 1-4 Increase in free azithromycin c oncentration once infection was induced as determined by in vivo microdialysis in rats .......................................................................29 2-1 Two hypothetical killing profiles resulting in identical mi crobial burden after 24 h of antimicrobial exposure. ......................................................................................................4 1 2-2 Curve fits for four bacterial strains with the various constant concentrations. A monophasic activity profile is displayed over 6 hours .......................................................42 2-3 Time-kill curves for Streptococcus pyogenes exposed to five antibiotics at concentrations ranging from 0 to 64 times the MIC. A biphasic activity profile is displayed over 24 hours with th e exception of vancomycin. .............................................43 2-4 Effect of dose schedule on efficacy of ciprofloxacin against Bacillus anthracis ..............44 3-1 Mean concentration-time profile for a 500 mg two hour i.v. infusion in healthy volunteers .................................................................................................................... .......62 3-2 Mean volume of distribution, clearance, dose normalized AUC0, and dose normalized maximum concentration vs. dose. ...................................................................63 3-3 Formation of diacetly (2,3-butanedio ne) during the convers ion of ceftobiprole medocaril to the active moiety ceftobiprole .......................................................................64 5-1 Typical chromatogram for ceftobiprole. ............................................................................97 6-1 Mean ceftobiprole concentration in pl asma, skeletal muscle ISF, and s.c. adipose tissue ISF over twelve hours. ...........................................................................................106 7-1 Time-kill curves of Ceftobiprole against MRSA performed over 24 hours. ...................118 7-2 Degradation of Ceftobiprole in MHB with MRSA at 37C. ............................................119 7-3 Diagnostic plot of observed CFU/mL vs. population predicted. .....................................120 11

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7-4 Diagnostic plot of the natural log observed CFU/mL vs. individual predicted. ..............121 7-5 Diagnostic plot of weighted re siduals vs. individu al predicted. ......................................122 7-6 Individual fits of the model population pr edicted and individual predicted curves for time-kill expe riments .......................................................................................................12 3 8-1 Two-compartment body model with elimin ation from the central compartment and drug delivery via i.v. infusion. .........................................................................................131 8-2 Plots of interindividual vari ability vs. possible covariates. .............................................132 8-3 Dependent variables vs. population predicted values ......................................................133 8-4 Dependent variables vs. individual predicted values .......................................................134 8-5 Weighted residuals vs. population predicted values. .......................................................135 8-6 Individual fits of the covariate mode l population predicted and individual predicted curves for free plasma ......................................................................................................13 6 8-7 Individual fits of the model population predicted and individual predicted curves for skeletal muscle ............................................................................................................... ..137 8-8 Individual fits of the model population pr edicted and individual predicted curves for s.c. adipose tissue ........................................................................................................... ..138 8-9 Example of a success and a failure based on achieving 1-log kill at 24 hours ................139 12

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Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy PHARMACOKINETIC/PHARMACODYNAMIC CHARACTERIZATION OF CEFTOBIPROLE By April Marie Barbour May 2009 Chair: Hartmut Derendorf Major: Pharmaceutical Sciences Ceftobiprole is a novel-cephalosporin with broad-spectrum activity against both Grampositive and Gram-negative pathogens, including activity against numerous resistant species such as methicillin-resistant Staphylococcus aureus (MRSA) and penicillin-resistant Streptococcus pneumonia (PRSP). The lead indication of cef tobiprole is complicated skin and skin structure infections. Therefore, to further characterize the pharmacokinetics, the concentration in the inte rstitial space fluid of skeletal musc le and subcutaneous adipose tissue after a single 500 mg 2 hour intravenous infu sion was determined by microdialysis and compared to plasma concentrations. To characterize the pharm acodynamics, a time-kill experiment was performed with MRSA to eval uate the pharmacodynamic ac tivity of ceftobiprole over time. Pharmacokinetic and pharmacodynami c models were developed and simulations were performed to evaluate the generally re commended dosing regimen of ceftobiprole, a 500 mg 2 hour i.v. infusion every 8 hours. It was found that this dosing regimen is efficacious at the site of action based on two different pharm acodynamic endpoints, whether the time the free concentration remained above the MIC for at least 40% of the dosing in terval and whether at least a 1-log bacterial kill was achieved at 24 hours. 13

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CHAPTER 1 CLASS-DEPENDENT RELEV ANCE OF TISSUE DISTRIBUTION IN THE INTERPRETATION OF ANTIMICROBIAL PK/PD INDICES Hypothesis and Specific Aims Ceftobiprole is a novel, broa d-spectrum cephalosporin with activity against both Gramnegative and Gram-positive bacteria including so me resistant pathogens such as MRSA and PRSP. Currently, ceftobiprole medocaril, the wa ter soluble prodrug of ceftobiprole, is under FDA review for approval with the lead indica tion of complicated skin and skin structure infections (cSSSI). The lead indication of cSSSI merits the exploration of not only plasma concentrations but also of free concentrations w ith interstitial space flui d (ISF) of subcutaneous tissues to ensure penetration of this intravenously administered compound to the site of action. Once the tissue concentrations have been de termined, it is important to explore the corresponding pharmacodynamic result. The phar macodynamic parameter typically used in PK/PD evaluations is the minimum inhibitory concentration (MIC). However, this pharmacodynamic measure has many drawbacks such as an inherent two-fold variability and the lack of a relationship between the antimicrobial activity and time. Therefore, time-kill curve experiments are a more rational approach for pharmacodynamic characterization of a compound. Hypothesis A currently recommended dosing regimen of ce ftobiprole, 500mg admi nistered as a 2 hour intravenous (i.v.) infusion every eight hours, is efficacious at the site of action based on the pharmacodynamic endpoints of time above the MIC and a 1-log bacterial kill. Specific Aims 1. Perform in vitro microdialysis experiments to validate the feasibility of using microdialysis as a sampling technique to determine free ISF tissue concentrations of ceftobiprole. 2. Develop and validate an HPLC-U V method for the analysis of ceftobiprole in lactated Ringers solution according to GLP guidelines. 14

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3. Perform an in vivo microdialysis clinical study to determ ine the free ISF concentrations in skeletal muscle and subcutaneous adipose tissu e of ceftobiprole in he althy volunteers after a single 500mg dose given as a two-hour i.v. infusion. 4. Perform in vitro pharmacodynamic studies to characterize the antimicrobial activity of ceftobiprole against MRSA by performi ng time-kill experiments and develop a mathematical model to describe the antimicrobial activity. 5. Develop and validate a pharmacokinetic model to evaluate the efficacy of the current dosing regimen in plasma, skeletal muscle, a nd subcutaneous adipose tissue based on two different pharmacodynamic endpoints, the free time above MIC as a percentage of the dosing interval and a 1-log bacterial kill from the starting inoculum at 24 hours. Introduction Pharmacokinetic/pharmacodynamic (PK/PD) charac terization of antimicrobial agents has allowed a better understanding of why a particular dosing regimen achieves clinical success or failure. Using techniques first pioneered by Eagl e (62, 63) and further deve loped by Craig (6, 8, 44), dose selection has become a much more sophisticated process over previous empiric methods. In vitro and in vivo experiments are used to define a relationship between drug concentration (PK) and effect (PD) and allow for a clear target to be identified so that efficacy is achieved in the clinical setting (2). The PK/PD indices typically used for antimicrobials include the time the free drug concentration remains above the minimum inhibitory concentration (MIC) expressed as a percent of the dosing interval ( f T>MIC), the ratio of the maximum concentration and MIC (Cmax/MIC), and the ratio of the twenty-f our hour area under the concentration-time curve and MIC (AUC0-24/MIC) (44). The in vivo PK parameters are usually determined from serum or plasma drug profiles while in vitro PD parameters commonly use culture media drug concentrations. The index which best correlates with a partic ular antibiotic depends on several factors. One of these factors is the pattern of microbial kill exhibited by the compound which is frequently referred to as either time-dependent killing or co ncentration-dependent killing. 15

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Antibiotics which display time-dependent killin g typically reach a ma ximum effect at a concentration approximately 4 times the MIC (47, 99). Once this maximum effect is reached increasing the concentration does not increase the ra te of bacterial death as shown for ticarcillin in Figure 1-1 (47). Antibiotics which displa y concentration-depende nt killing produce an increasing effect as the concentration increases as shown for tobramycin and ciprofloxacin in Figure 1-1. However, categorizing an agents antimicrobial activity as timeor a concentrationdependent is not always obvious as shown in Figure 1-2 where profiles for concentrations greater than 4 times the MIC appear similar for all compounds (136). Concentration-dependent antibiot ics usually correlate efficacy with exposure and the MIC, i.e. the Cmax/MIC or the AUC0-24/MIC. The efficacy of time-dependent antimicrobials usually depends on f T>MIC as a percentage of the dosing interval However, time dependent antibiotics which display a prolonged post-antib iotic effect (PAE), the persistence of activity after removal of the drug or after concentrations drop belo w the MIC (29, 45, 190), ofte n correlate well with the AUC0-24/MIC. Although the mechanisms of the PA E have been speculated, the PAE seems to depend on the drug, the pathogen, and the in fection model (29). The term PAE is used collectively to explain resi dual effects of complex pharm acokinetic and pharmacodynamic processes that are not well defined. Other factors which influence the significance of PK/PD indices for predicting clinical efficacy that are often overlooked include protein binding and tissue distribution. Recently it has been stressed that only free conc entrations should be taken into account in these indices as only free drug has the ability to exhibit a pharmacological effect (138, 160, 194). Similarly, it follows that the most relevant concentrations for antibiotic efficacy would be the concentration within the interstitial space fluid (ISF) of target tissues as most infections are located outside the 16

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plasma or serum where drug concentrations are commonly monitored. The volume of distribution, and subsequently the degree of tissue distribution, vari es greatly between antimicrobial classes as shown in Ta ble 1-1 (30, 40, 89, 102, 115, 128, 167, 174, 184, 185, 196). It is the goal of this paper to review the PK/PD relationship of various antimicrobial classes and analyze this relationship by examining the mechanis m of action, in vitro k ill-kinetics, and free tissue concentrations. Additionally, the PAE will be discussed, in some instances as it may be used to account for additional uncharacterized PD effects. Beta-lactams Beta-lactam antibiotics, which include the penicillins, cephalosporins, and carbapenems, work by inhibiting cell wall synthesis by binding to penicillin binding protei ns (PBPs). The class displays time-dependent killing that is consistent with this mechan ism of action. In general, the beta-lactams correlate well with f T>MIC The PAE is virtually absent with gram-negative bacteria, except the carbapenems (32, 45), and only a modest PAE is reported with gram-positive bacteria, mainly staphylococci (46, 145, 192). The time needed for the concentration to remain above the MIC is slightly different for each subc lass but consistent within groups as long as only free concentrations are considered due to fact that protein binding can vary greatly between compounds, with 2% reported for meropenem and approximately 90% for ertapenem (11, 112, 160). The f T>MIC needed for bactericidal effects in gram -negatives is approximately 40-50% for carbapenems, 50-70% for penicillins, and 70-80 % for cephalosporins (17, 30). For grampositive bacteria the f T>MIC needed is approximately 25-45% for carbapenems, 35-50% for penicillins, and 40-50% for cephalosporins (17). It can be seen that the carbapenems display efficacy with a lower f T>MIC, mainly because this subclass displays the fastest rate of kill (44). Also noteworthy, is that the f T>MIC needed for efficacy is generally less than 40-50% for Staphylococcus spp. possibly due to the PAE (46, 192), wh ich may be better defined by more 17

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thoroughly characterizing PK and/or PD properties. It is intere sting that while the beta-lactams have a volume of distribution of ~18L (30) and th ey do not accumulate at the site of action, i.e. the ISF where concentrations are typically equal to or less than free plasma concentrations (94, 101, 181), the time needed for free concentrations to remain above the MIC is less than the dosing interval. Aminoglycosides The PK and PD of the aminoglycosides are fa irly well characterized and appear to be consistent throughout the class. The mechanism of action of this class involves binding to the 30S ribosomal subunit and preventing protein synt hesis (65). Typically, an tibiotics that inhibit protein synthesis or replication display a concentration-dependent killing pattern and a PAE, as is the case for the aminoglycosides (16, 99). W ith these pharmacodynamic characteristics, the efficacy of aminoglycosides in c linical studies correlates to a Cmax/MIC ratio that exceeds 10 (95) or an AUC0-24/MIC ratio between 80 and100 for maximu m effects in animal models of infection (184, 191). One possibility that may explain a better the correlation between Cmax/MIC compared to the AUC0-24/MIC is the emergence of resistan t populations. Resistance occurs much less when a Cmax/MIC ratio of 10 is achieved (20). Also, uptake of these compounds into bacterial cells is energy depende nt (27, 65) and decreases afte r an initial exposure (49). Therefore, by allowing a larger, less fr equent dose and subsequent larger Cmax, better efficacy may be achieved due prevention of resistant mu tants, mechanism of antibacterial uptake, and other PAE mechanisms. In fact, clinical investigators advocate once daily dosing of aminoglycosides (41, 135) but more data is needed to show a statistically better clinical outcome with a once daily dosing regimen. With the low protein binding and a volume of distribution approximately equal to extracellular space flui d (184), the target AUC0-24/MIC of 80-100 for ami noglycoside clinical 18

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efficacy indicates that the average concentr ation exceeds the MIC over a 24 hour period. A target of approximately 24 would be expected from described PK and PD parameters. The higher AUC0-24/MIC suggested target of 80-100 results from several factors. These factors include, the target for clinical efficacy it is based on a maximum effect and not bacteriostasis, the low protein binding may not truly be negligible and use of plasma concentrations rather than tissue ISF levels. Again, the most relevant concentrations are the free concentrations at the site of action and it has been shown that antibiotics which dist ribute to the ISF, may have tissue concentrations lower than plasma concentrations For example, in subcutaneous adipose tissue gentamicin had a Cmax and AUC0-360 that were approximately 39% and 60% of values determined from plasma, respectively (108). Ev en when the protein binding is considered, approximately 20% (132), free plasma concentrat ions do not equal free I SF concentrations. Fluoroquinolones The fluoroquinolones prevent DNA replication by inhibiting type II topoisomerases, also called DNA gyrase, and topoisomerase IV (76, 81), and may also affect bacterial membranes (176). Like the aminoglycosides, the fluoroquino lones display concentration dependent killing (47) and both the AUC0-24/MIC and Cmax/MIC ratios are correlated with efficacy. However, several clinical studies have revealed the AUC0-24/MIC ratio is the bette r index (61, 70, 71, 149). A high target Cmax/MIC ratio may aid in the prevention of resistance development (149). In gram-negative infections an AUC0-24/MIC ratio of 125, free ~75, was found to be sufficient for efficacy of ciprofloxaci n (71). Similarly, an AUC0-24/MIC of 87, free ~62, was found to be efficacious for levofloxa cin (61) and an AUC0-24/MIC of 75-175, free 37.5-87.5 for grepafloxacin provided an 80% probability of cure for patients with chronic bronchitis (70). For gram-positive pathogens, such as, Streptococcus pneumoniae, the breakpoints seem to be lower. In patients with community-acquired pneumonia or acute exacerbation of chronic bronchitis that 19

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received either levofloxacin or gatifloxacin, a free AUC0-24/MIC ratio above 33.7 provided complete efficacy (3). A Cmax/MIC ratio of 12.2 was also found to predict efficacy in a clinical study (149). This finding was supported by a dose fractionation study in the neutropenic mouse model with lomefloxacin (60). Howe ver, in this animal model the AUC0-24/MIC ratio was more highly correlated to efficacy at lower doses where the Cmax/MIC was less than10. It is interesting that the magnitude of the pl asma based PK/PD indices which correlate with efficacy are in good agreement among this class. The magnitudes of these targets are also similar to the aminoglycosides when comparing free AUC0-24/MIC. However, the fluoroquinolones distribute more extensively into tissue with free tissue/ free plasma ratios of approximately 0.9->2 (88, 166, 195). Therefore, it is somewhat surprising that the magnitude of these indices associated with efficacy is not lower and may be due to some unexplained difference in the PD associated with different mechanisms of action between aminoglycosides and fluoroquinolones. Oxazolidinones Linezolid is the only approved oxazolidinone on the market and has activity against several resistant pathogens including MRSA, VRSA, VRE, PRSP (26, 35, 84). The mechanism of action of this class is inhibiti on of protein synthesis at the in itiation stage by binding to the 50S subunit of the bacterial ribosome (197) and pr eventing the first ami no acid, methionine, tRNA complex from binding at the peptidyl site ( 21). The pharmacodynamics of linezolid were described in a dose fractionation st udy using the neutropenic murine thigh infection model (8). Although this antibiotic displays time-dependent k ill kinetics (157, 198), it best correlates with the AUC0-24/MIC ratio, not the time above MIC, for Streptococcus pneumoniae and correlates well with both the AUC0-24/MIC and time above MIC for Staphylococcus aureus (8). The AUC024/MIC ratio required for a bacteriostatic effect with linezolid was 48 for pneumococci and 83 20

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staphylococci in the neutropenic murine thigh infection model (8). In a clinical study with critically ill patients with bacteremia, an AUC0-24/MIC of 105 and a time above MIC of 82% was associated with a faster time to bacteria erad ication (152). The slight ly higher target in the clinical study is probably due to a more a ggressive endpoint. Taki ng the reported protein binding of 8.7-31% (53, 111) and ti ssue distribution into cons ideration, free tissue and free plasma concentrations are approximately equal (53). These targets are in agreement with the aminoglycosides and fluoroquinolones. Tetracyclines and Glycylcyclines The pharmacokinetics and pharmacodynamics of the tetracyclines and glycylcyclines, especially tigecycline, are not fully understood (14). The mechanism of action of this antibiotic class is inhibition of protein sy nthesis by binding to the 30S s ubunit of the prokaryotic ribosome (196). The tetracyclines display a time-dependent killing pattern and ex hibit considerable PAE (44, 48, 142, 148, 189). A prolonged PAE, as observed with tigecycline (189) suggests that the best PK/PD index is the AUC0-24/MIC. However, time above the MIC for free drug levels versus effect also had a high correlation coefficient as shown in Figure 1-3 (189). In clinical trials with patients with complicated skin and skin stru cture infections (cSSSI) or complicated intraabdominal infections (cIAI), the AUC/MIC rati o was used as the PK/PD index for target development and ratios of 17.9 and 6.96, respective ly, produced a better outcome (117, 146). Although the PAE was used in target selection, it is important to remember that it is the result of residual PK and PD effects that are not well characterized. The PAE of this class of antibiotic may be the result of extensive tissue distribution resu lting in higher active concentrations at the si te of action. The tetracyclines disp lay a varied volume of distribution with values ranging from 0.14L/kg to 1.6L/kg (196). Tigecycline, how ever, is the most extensively distributed compound in this class with a volume of distribution of 7-10L/kg (40, 21

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128). The high volume of distribution reflects th at free concentrations in the ISF could be significantly higher than plasma. This theory is supported by the low PK/PD target values calculated for tigecycline from clinical trials. When protein binding is c onsidered, 36-47% at a pH of 7.3 (144), the targets are much lower than would be exp ected to achieve efficacy, a minimum of 24 for the free AUC0-24/MIC. However, the suggested targets for the free drug are <12 for cSSSI and <5 for cIAI. Macrolides, Ketolides, Azalides The macrolides are characterized by a 1416 member macrocyclic lactone ring. The mechanism of action involves reversible binding to the 50S ribosomal subunit and prevention of protein synthesis (109). Although th is type of mechanism usually re sults in a bactericidal agent, the macrolides can display bacteriostatic or bactericidal killing de pending on the bacterial pathogen (69, 153). Overall, this class mainly disp lays time-dependent killi ng (5). As with the tetracycline/glycylcycline class, a residual an timicrobial effect or PAE is observed for macrolides (143, 151). However, no single PK/PD pa rameter appears to correlate with efficacy for all members in this class and all three targ et parameters have been suggested (5, 55, 89, 137, 141, 169, 188). This likely due to several factors including differences in kill-kinetics and large differences in the pharmacokinetic properties (89). In a clinical study with te lithromycin, it was found that a breakpoint of 3.38 (AUC/MIC) was predictive of efficacy (106). This is much lower than most other antibiotic classes but similar to tigecycline. Like tigecycline, telith romycin displays extensive tissue distribution with a volume of distribution of 2.9L/ kg (147, 169), suggesting that con centrations may be higher at the site of action. This is al so supported by a microdialysis st udy in healthy volunteers with telithromycin which found AUC0-8 ratios of free tissue/free plas ma of 2.1.6 and 1.5.9 for subcutaneous adipose and muscle tissue, resp ectively (79). Another explanation for a low 22

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PK/PD target index is that these antibiotics accu mulate intracellularly, especially azithromycin and telithromycin (24, 80, 133). In human polymorphonuclear le ukocytes (PMNs) after 2 hours of exposure with 10 g/mL, azithromycin displa yed an intracellular/extracellular ratio of 79 while erythromycin displayed and intracellular/extracellula r ratio of 16 (80). When telithromycin was given as a 600 mg oral daily dose for 10 days, the c oncentration in white blood cells was approximately 100 times that in pl asma (124, 133). Therefore, the macrolides may actually be carried to the infection site by white blood cells resulting in a lower magnitude of the appropriate PK/PD index for efficacy (4, 80, 159). This is supported by several studies, such as a microdialysis study where the free concen tration of azithromycin within infected tissue was much higher that noninfected tissue (Figure 1-4). Also, a study using skin blister fluid found the concentration of azithromycin to be higher in inflammatory blisters than either plasma or non-inflammatory blisters (4, 72). These high c oncentrations are the re sult of ion-trapping of azithromycin, a dibasic compound, within acidic lysosomes (4). Therefore, the low PK/PD target is at least in part the result of higher concentrations at the site of action. Glycopeptides Like the beta-lactams, glycopeptides also inhi bit cell wall synthesis. This antibiotic class works by forming hydrogen bonds with bacterial cell wall intermediate peptides and thereby inhibiting peptidoglycan synthesis (154). As characteristic for anti biotics that inhibit cell wall synthesis, the glycopeptides main ly display time-dependent killing in vitro (19, 67, 100, 110, 156). However, oritavancin and dalbavancin have been shown to display bactericidal concentration-dependent activity in vitro (19, 175). In terms of PK /PD, the neutropenic mouse thigh infection model revealed the AUC/MIC to be predictive of efficacy with vancomycin against Staphylococcus aureus (64). In the nonneutropenic mouse peritonitis model with vancomycin against Staphylococcus aureus and Streptococcus pneumoniae, survival was 23

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correlated to the Cmax/MIC (98). In a clinical study involving patients with Staphylococcus aureus lower respiratory tract infec tion receiving vancomycin, an AUC0-24/MIC ratio of 400 resulted in a significantly better clinical outcome and bacterio logical response (119). Although a magnitude of 400 is high compared to other antibioti cs, this value is in better agreement, when free tissue concentrations are considered. This compound displa ys a variable protein binding, ~10-80% (1, 177), and penetration into the ISF may be less than free plasma concentrations (171). Dalbavancin efficacy has been found to correlate to both AUC0-24/MIC and Cmax/MIC in a neutropenic murine thigh in fection model with and R2 of 77% and 57% respectively against Staphylococcus aureus and 78% and 90% respectively against Streptococcus pneumoniae (6). Recently, it has been shown that or itavancin best correlates with f T>MIC as a percent of the dosing interval (18). In patients with Staphylococcus aureus bacteremia infections, it was found that a f T>MIC of 22% had a 76% probability of microbiological cure and an 87% probability of clinical success. This was similar to the findings of an in vivo neutropenic murine thigh infection model, where a f T>MIC of ~17-20% was bacteriostat ic (18, 25). However, in the murine model the free Cmax/MIC was the most highly correlated parameter. The PK/PD parameter which best correlates to efficacy seems to be dependent on drug, pathogen, and infection model, which is a reflection of the difference in kill-kinetics and possibly other PK and PD properties among this class. Therefore, each compound should be individually characterized both in vitro and in vivo before a PK/PD target is selected. Conclusion Pharmacokinetic/pharmacodynamic characterizati on of antimicrobial agents allows for a much more rational approach to antimicrobial dosing than traditional empiric methods. PK/PD indices have been well established for antimicrobial agents but are not fully understood among all antibiotics and/or antibiotic classes. The rationale behind which PK/PD index best predicts 24

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efficacy and the needed magnitude is depende d on several factors. As a general rule, antimicrobial agents which have a mechanism of ac tion of inhibition of either protein or bacterial synthesis generally display c oncentration-dependent killing a nd correlate well with the AUC024/MIC ratio or Cmax/MIC ratio. Antimicrobials which act on the cell wall display timedependent killing and correlate to the time th e free concentration remains above the MIC. However, a major exception is that antimicrobials which display a PAE correlate better with the AUC0-24/MIC ratio. The PAE is identified as antimi crobial activity in the absence of antibiotics or at concentrations below the MIC. One area that is often overlooked when developing PK/PD targets is the tissue distribution and in fact the in vivo PAE may be at least in part due higher free tissue concentrations at the site of in fection as these are concentrations are responsible for the desired clinical effect (121, 179). Beta -lactams and aminoglycosides fo r example distribute well into ISF but free concentrations in tissue may be lower than free concentrations in plasma. Tigecycline and azithromycin, how ever, both extensively distribut e into tissues and the active tissue concentrations at the infection site may be higher than plasma concentrations. In conclusion, when optimizing the dosing regime n the pharmacokinetic properties including protein binding and tissue distribu tion, and the pharmacodynamics, both in vitro and in vivo, should be well characterized. 25

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Figure 1-1. Time-kill curves with Pseudomonas aeruginosa (ATCC 27853) displaying tobromycin and ciprofloxacin as having concentration-dependent kill-kinetics and ticarcillin as having time-dependent kill-k inetics. Reprinted w ith permission from (47). 26

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Figure 1-2. Time-kill curves for Streptococcus pyogenes showing that although vancomycin, a glycopeptide, displays time-dependent killi ng, there is little di fference between the other compounds which include two be ta-lactams, a fluoroquinolone, and a macrolide. Reprinted with permission from (136). 27

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Figure 1-3. Both the time above MIC (panel a) and AUC (panel b) correlate well to the efficacy of tigecycline against Streptococcus pneumoniae 1199 in the neutropenic murine thigh infection model compared to the Cmax (panel c). Reprinted with permission from (189). 28

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Figure 1-4. Increase in free azithromycin concentration once infection was induced as determined by in vivo microdialysis in rats. Az ithromycin was given 50mg/kg subcutaneously. (Figure from Scagli one, presented at ICAAC 2006, work unpublished) 29

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Table 1-1. Volume of distributi on of antimicrobials by class dete rmined from clinical studies (30, 40, 89, 102, 115, 128, 167, 174, 184, 185, 196) Antimicrobial class Volume of dist ribution Physiological distribution Beta-lactams ~0.26 L/kg* EF Aminoglycosides ~0.1-0.3 L/kg EF Oxazolidinones ~0.51-0.67 L/kg* TBW Fluoroquinolones 1.3-8.3 L/kg >TBW Tetracycline (Tigecycline) 0.14L/kg-1.6L/kg (7-10L/kg) TBW Macrolides 0.64L/kg-23L/kg ~TBW-Much Greater than TBW Glycopeptides ~0.1-1L/kg EF-TBW *Based on an average weight of 70kg. EF=E xtracellular Fluid. TB W=Total Body Water 30

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CHAPTER 2 APPLICATIONS OF ANTIMICROBIAL PHARMACOKINETICS/PHARMACODYNAMICS Characterization of Antimicrobial Pharmacokinetics/Pharmacodynamics The learn/confirm paradigm for drug devel opment, as discussed by Sheiner (168), has provided a relatively new but mo re efficient method for development of an investigational pharmaceutical. This model-based approach suggests the focus of drug development should be an understanding of the science rather than usi ng empirical evidence to make decisions. While sequential drug development may be slightly mo re time consuming early in the process, numerous examples in literature have been cited in which model-based drug development has been used to make critical decisions including lead compound selection, trial design, and dose selection (38, 118) All of these examples have ultimately increased efficiency by saving time, money, and resources. The FDA has also stated its support of model-based drug development (186) and approved gabapentin for post herpetic neuralgia based partly on efficacy evidence provided by PK/PD modeling (118). The techniques mentioned above can also be applied to the development of antimicrobial agents and post-approval for the evaluation and possible adjustment of recommended dosing regimens. Unique to antimicrobials, the pharmacodynamics can be extensively and accurately characterized in in vitro and in vivo animal models with a good co rrelation to the effect in infected patients (2) due to the fact that the site if action is th e same in all systems, the bacteria. In order to predict efficacy and select the ap propriate dosing regimen, antimicrobial PK/PD has been traditionally related to one of three indices; the time the free concentration remains above the minimum inhibitory concentration (MIC), th e maximum free concentration to MIC ratio, and the area under free twenty-four hour concentration-time curve to MI C ratio (44). Dose fraction studies are typically performed to select the most appropriate i ndex and magnitude of the index 31

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for each agent (6, 7, 46, 189). Additionally, Monte Carlo simulations are performed to find the most appropriate dosing regime n or evaluate a current regimen based on the pharmacokinetic variability and pharmacodynamic va riability, i.e. inte r/intrapatient vari ability and the MIC distribution (59, 104, 105, 134). Al though these techniques have gr eatly improved antimicrobial development over empiric methods, there is an o pportunity and means to improve the processes currently used. Traditionally, plasma samples are used as th e pharmacokinetic input in PK/PD models. It has now been generally accepted that free concentra tions should be used in these models as only free drug is active (125, 138, 160). Al so, it is important to consider the free concentration at the site of action. Although plasma ma ybe the site of action, i.e. bacteriemia, it is often not. For example, in regards to complicated skin and skin structure infections, it is more meaningful to determine the concentration within the interstitial space fluid (ISF) of subcutaneous soft tissues, e.g. skeletal muscle or adipose tissue. This can be accomplished by using the microdialysis sampling technique, which has been proven su itable for the measurement of free ISF antimicrobial concentrations in virtually any ti ssue in both healthy vol unteers and patients (28, 75, 180, 182). As previously mentioned, the pharmacodynamic parameter most often used with antimicrobials is the MIC. However, there are many limitations if the MIC is used as the only pharmacodynamic parameter. Mainly, the MIC doe s not characterize the antimicrobial activity over time but is rather a static one-point in time measurement. It is possible for an agent to display different kill-kinetics but the same bacterial load after a given incubation period (Figure 2-1). The MIC also does not indicate the degree of pharmacological effect, e.g. a 1-log kill or a 2-log kill over twenty-four hours. The MIC ha s a two-fold variabil ity and is somewhat 32

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subjective as it is based on visual detection of ba cterial growth. Finally, this parameter does not measure the presence or concentration of persiste nt/resistant bacteria th at may be present but may not have grown to a detectable limit by the una ided eye. Time-kill curves are an alternative experimental technique to characterize the pharmacodynamic activity of an antimicrobial agent and circumvent many of the limitations of using the MIC as the pharmacodynamic parameter. These experiments measure the antimicrobial activity over time, dete rmine the extent of antimicrobial activity, and may det ect persistent/resistant populations. The concentrations used in these experiments maybe static or dynamic, i.e. changing to simulate the half-life. Dynamic experiments also have the addi tional benefit of capturing th e antimicrobial activity after concentrations drop below the MIC. Due to the numerous advantages of this te chnique over the MIC, kill-curve experiments have gained in popularity. The mathematical mode ls which have been developed and applied to these experiments for pharmacodynamic characteriz ation are compared below. Additionally, the applications of these experime nts and models are mentioned. Pharmacodynamic Models One-Population Models The primary goal of time-kill curves is to characterize the pharm acodynamic activity of an antimicrobial agent often with the intention of using this informati on to optimize the dosing regimen. These experiments are performed by expos ing bacteria to a range of concentrations, generally as multiples of the MIC. The results are then typically fitted to an Emax model, Emax= to characterized the activ ity and calculate the pharm acodynamic parameters as a function of the change in the number of bacteria over time (Equation1) (113, 123). This model can be modified to account for a delay in growth and/or kill and saturation in the number of 33

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bacteria in the in vitro system (Equation 2) (183). All symbol de finitions are provided in Table 2-1. (Equation 1) (Equation 2) As can be seen by these equations and th e monophasic kill pattern (Figure 2-2), the bacteria are all assumed to have the same sus ceptibility. However, if these experiments are carried out over a long enough time-period a biphasic antibacterial effect is usually observed (Figure 2-3). Therefore, mode ls which account for differences in susceptibility have gained much popularity as they better ch aracterize the pharmacodynamics. Two-Population Models with Persistent Bacteria Many pharmacodynamic models have been de veloped which describe the bacterial population as two distinct subpopulations, one which is susceptible to drug and one which is not. In these models, the susceptible population is growing while th e persistent/res istant population may be dividing or in a state of hibernation. The presence of a pe rsistent/resistant population has been experimentally validated (13, 58, 97, 178) but it is difficult to say that either resistance or persistence is the rationale behi nd the biphasic profile of antimicrobial activity as it could be a combination of both. The difference between the tw o populations is that resistant bacteria have a genetic mechanism of resistance a nd grow on agar supplemented with antibiotic, while persistent bacteria remain sensitive to th e antibiotic once regrown. It has been suggested that if a large inoculum is used, then the biphasic profile is more likely to be attributed to resistance as the mutation rate is 10-7 -10-8 (178). If a smaller inoculum is used, e.g. the standard of ~106 CFU/mL, then the presence of persisters may be more likely than a genetically acquired 34

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resistance mechanism (136). Many authors have a pplied the persistent theo ry to model the kill kinetics of antimicrobials from time-kill experiments. A persistent model was devel oped during a comparison of the in vitro bactericidal kinetics of S-4661, a new carbapenem, to merope nem, imipenem, cefpirome, and ceftazidime using several bacterial strains which included, Escherichia coli Pseudomonas aeruginosa, and Staphylococcus aureus (193). This model places the bacteria in one of two states, susceptible and dividing or persistent (E qu and 4) ations 3 (193). (Equation 3) (Equation 4) A similar but slightly modified model was developed by using an additional term to account for the natural death rate on both the persis tent and susceptible b acteria (Equations 5-8) (136). This model also takes into account the tr ansition of susceptible cells into persisters once the maximum bacterial concentration is reached in the system, where ksr is equal to a proportionality constant times the total bacterial c oncentration in the system. The purpose of this experiment was to identify a robust model that could be used for seve ral drug/bug combinations with the promise of eventually aiding in dose optimization of new antimicrobials. This model was able to fit the kill-kinetics of several antimicrobials from different classes against Streptococcus pyogenes including the penicillin benzylpenicillin, the cep halosporin cefuroxime, the macrolide erythromycin, the fluoroqui nolone moxifloxacin, a nd the glycopeptide vancomycin. In this paper, several models were applied to the data which placed the antimicrobial effect on the growth rate (Equation 5), as an additive effect on the natural death rate (Equation 6), or as an effect on death separate from the natu ral death rate (Equation 7). The equation for the persister populati on is the same during the comparison of the models (Equation 35

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8). It should be noted that krs was fixed to zero and a mixture m odel was used so that the initial inoculum were either in logarithmic growth or a mixture of logarithmically growing bacteria and persisters. If the starting inoculum was a mix with both persisters and susc eptible bacteria, then it was estimated that 5% of the population were persisters. (Equation 5) (Equation 6) (Equation 7) (Equation 8) In these equations Drug is the Emax model with a hill factor. E quations 5-7 presented above for the antimicrobial effect fit the data equally well. Two-Population Models with Resistant Bacteria As previously mentioned, it is also possible to have two distinct populations within a bacterial culture, one susceptible to drug and one resistant. These populations may in fact display different profiles for growth and kill, presented below as a net effect model (Equations 9 and 10) (33). This model provided a better fit th an a model which had similar growth and death rate constants or one which allowed for adapta tion and the appearance of resistance. The purpose of model development was to characteri ze the antimicrobial effect of ciprofloxacin in vitro on both susceptible and resistant populations after exposure to concentrations equivalent to those observed in vivo arroflo in dosinmens. fter vaious cipxa cg regi (Equation 9) (Equation 10) 36

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In a subsequent study, two-populations mode ls were compared to examine which and how the parameters are affected by the antibiotic (39). The models comp ared included the net effect model (Equations 9 and 10), the growth inhibition model (Equations 11 and 12), the death stimulation model (Equations 13 and 14), and the MIC based mode l (Equations 15 and 16) (116). It was found that based on goodness-of-fit, bias of observed vs. predicted, precision of the estimates, and predictive performance that the net effect model and growth inhibition model were the superior models. Equation (11) Equation (12) Equation (13) Equation (14) Equation (15) Equation (16) Theoretically, it is possible to have seve ral populations of bact eria within a given inoculum. In the above MIC model, origina lly proposed by Meagher et. al., three different bacterial populations were assumed, i. e. three different values for SITm, the concentration needed to produce the median effect for C/MIC ( 116). However, the pharmacodynamics were adequately described with only two values, where SITm is either susceptible (SITmS) or intermediately susceptible (SITmR), with all other parameters remaining the same between the 37

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different populations (Equation 17 ) (116). Additionally, in this m odel, growth was a function of the bacterial load in the system and not a consta nt. This model was originally proposed to characterize the pharmacodynamics of ciprofl oxacin and model the effects of different ciprofloxacin dosing regimens and formulations, an extended release and an immediate release. (Equation 17) Adaptation Models Thus far models have been discussed that assume two distinct popul ations. It is also possible to model a bacterial popul ation which undergoes adaptive re sistance in the presence of an antimicrobial agent. For example, to explain the biphasic kill profile, a model was developed which assumed that adaptive resistance changed the ra te of bacterial kill from an initial rapid kill, 1, to a slower permanent kill, 2. This model was also developed for comparison of the pharmacodynamics of two different dosing regime ns of ciprofloxacin, a twice daily immediate release and an once daily extended release, by simulating in vivo concentrations in an in vitro model, i.e. concentrations that changed according to the halflife (Equations 18 and 19) (165). (Equation 18) (Equation 19) In the above model, the adaptation was placed on the kill rate constant. However, it is also possible to say that the adapta tion is due to a change in the su sceptibility and not the rate of kill, i.e. a change in the EC50 (Equations 20 and 21) (178). This model was developed to characterize the pharmacodynamics of meropenem against Pseudomonas aeruginosa. Although, like many other models, it is robust and has the potential to be appl ied to other drug/bug 38

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combinations (178). To ensure the presence of resistant population(s) at the start of the study, a large initial inoculum,108 CFU/mL, was used. (Equation 20) (Equation 21) Similar to the approaches us ed during model development in two-population models, the possibility of adaptation due to a change in the growth rate was also examined (Equation 22) (123). This model was developed to compar e the pharmacodynamics of two different dosing approaches wit con fusiond interminfusion. h ceftazidimetinuous inn aittent (Equation 22) Summary In vitro experiments to determine the antimicrobi al activity of a part icular agent often correlate well with the in vivo situation due to the fact the site of action is the bacteria. Killcurve experiments are particularly useful as they provide a detailed pharmacodynamic profile, a major advantage over the MIC approach. In fact the MIC may be misleading as two different dosing regimens may produce the sa me AUC/MIC ratio but different profiles of activity (Figure 2-4). Several examples have been given in lite rature using kill-curves to evaluate/select the optimal dosing regimen. A few examples include comparing continuous and intermittent infusions of ceftazidime (123), a comparison of an extended release and immediate release formulation of ciprofloxacin (116, 165), dose selection of levofloxacin against Bacillus anthracis (58), and optimizing the dosing regimen to preven t resistance development (33, 93). While most examples use in vivo plasma data combined with time-kill curves, it seems more meaningful to explore the PK/PD relationship ba sed on antibiotic concentrations at the site of infection, e.g. 39

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subcutaneous adipose tissue for complicated skin and skin structure infections, to make a dosing recommendation (54). Therefore, there are still means to improve antimicrobial dose optimization. Many semi-mechanistic models have b een proposed to model the pharmacodynamic activity of antimicrobial agents from time-kill experiments. As can be seen from a comparison between the models, they share many similarities and are not necessary entirely unique. More research is needed to fully understand th e mechanisms which lead to this biphasic pharmacodynamic profile. Currently, the models pres ented within this chap ter all seem justified and serve the purpose of thei r development. However, a better understanding of the pharmacodynamics may lead to improved dose optimization. 40

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Figure 2-1. Two hypothetical killin g profiles resulting in identical microbial burden after 24 h of antimicrobial exposure. Reprinted with permission from (178). 41

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Figure 2-2. Curve fits for four bacterial strains with the various constant concentrations (mg/L): (A) azithromycin against Streptococcus pneumoniae ATCC6303; (B) azithromycin against Streptococcus pneumoniae ATCC 49619; (C) azithromycin against Moraxella catarrhalis ATCC 8176; (D) azithromycin against Haemophilus influenzae ATCC 10211. A monophasic activity prof ile is displayed over 6 hours. Reprinted with permission from (183). 42

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Figure 2-3. Time-kill curves for Streptococcus pyogenes exposed to five antibiotics at concentrations ranging from 0 to 64 times the MIC. A biphasic activity profile is displayed over 24 hours with the excep tion of vancomycin which displays a monophasic profile over 24 hours. Reprinte d with permission from (136). 43

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Figure 2-4. Effect of dose schedule on efficacy of ciprofloxacin against Bacillus anthracis A ciprofloxacin exposure of an AUC24 of 16 mg h/liter (AUC24/MIC=256) was given as two equal doses at 12-h intervals or as a single dose at 24-h intervals. The twicedaily regimen prevented resistance emergence. The growth of an untreated control is also shown. Reprinted w ith permission from (58). 44

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Table 2-1. Definition of each symbol used throughout the chapter Symbol Definition Maximum kill rate constant EC50 Concentration needed to pr oduce half-the maximum effect C Concentration of antimicrobial H Hill factor N Number of bacteria Growth rate constant Nmax Maximum number of bacteria dg Delay in growth dk Delay in kill t Time NS Number of susceptible bacteria NR Number of persistent/resistant bacteria kSR Transfer rate constant of bacteria into the persiste nt/resistant stage kRS Transfer rate constant of bacteria into the susceptible stage Bmax Maximum number of viable bacteria in compartment 1 kdeath Natural bacterial death rate constant VGmax Maximum growth velocity MIC Minimum inhibitory concentration Nm Number of bacteria at which replication is half maximum SITm Median effect value of C/MIC (value at which the drug effect is half maximal) Maximum fraction increase of kdeath C r Concentration which indu ces adaptive resistance IC50 Concentration of the ad aptive resistance at which 1 is half maximal z Delay factor ke Elimination rate constant tla g Initial lag time for adaptive resistance kec r Rate constant for the decrease in the concen tration which induces ad aptive resistance C0 Initial antibiotic concentration Maximum adaptation factor Adaptation factor 45

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CHAPTER 3 CEFTOBIPROLE: A NOVEL CEPHALOSPO RIN WITH ACTIVITY AGAINST GRAMPOSITIVE AND GRAM-NEGATIVE PATHOGENS, INCLUDING MRSA1 Introduction The development and spread of resistance to currently available antibiotics is a world-wide concern. As resistance increases there is an overwhelmingly negative impact on mortality and health care costs. For example, it is estimated that it costs $4-7 billion annually in the US to treat resistant infections (187). Additionally, it has been shown that in intensive care patients with blood stream infections, improper antibiotic selection re sults in a mortality rate approximately double that of properly treated patients, 61.9% vs. 28.4% (87). Es pecially alarming is the high percentage of methicillin-resistant Staphylococcus aureus (MRSA) isolates for a number of reasons. One, this species is one of the most common pathogens in a wide-range of infections including blood stream (91), pneumonia (77, 114), a nd skin and soft tissue (74). Two, resistance has developed in this species to current last-d efense antibiotics includi ng vancomycin (170) and linezolid (78). Three, MRSA has become a virulent pathogen in both the health-care setting and the community. Therefore, there is definite medical need to continually develop new antimicrobial agents, especially those with MRSA activity. Ceftobiprole is a new broad-spectrum cephalosporin which displays a wide-range of activity against both Gram-positive and Gram-negative pathogens including several resistant species such as MRSA and penicillin-resistance Streptococcus pneumoniae (PRSP) (73, 82, 92, 155) (Table 3-1). It is approve d in Canada under the trade name Zeftera with the indication of 1 This chapter is copyrighted as: Barbour A, et al. Ceftobipr ole: a novel cephalosporin with activity against Gram-positive and Gram-negative pathogens, including methicillin-resistant Staphylococcus aureus (MRSA). In press. Int. J. Antim icrob. Agents (2009). Copyright Elsevier. 46

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complicated skin and skin structure infections (cSSSI) including non-limb threatening diabetic foot infections without osteomyelitis (90). It is currently under review by the FDA in the United States for approval. Pharmacokinetics Plasma Concentrations The current generally recommended dosing re gimen for ceftobiprole is a 500 mg dose every eight hours as a two hour i.v. infusion. The concentration-time profile for a single dose with this regimen is presented in Figure 3-1. A one hour infusion every twelve hours is recommended in cases with Gram-positive infections without diabetic foot infections (90). The major pharmacokinetic (PK) parameters for ceft obiprole are presented in Table 3-2 for the recommended 500 mg dose and for the extensively studied 750 mg dose. The Cmax for ceftobiprole with a 500 mg dose de livered intravenously (i.v.) ove r two hours is reported as 29.2 mg/L with an AUC0-8 of 90.0 mg*h/L (131). The AUC0for a 500 mg one hour infusion was 116 mg*hr/L. Ceftobiprole displays dose proportionality as demonstrated by the single rising dose study as no significant difference was observed in Vss and CLs or dose-normalized AUC and Cmax for doses between 125-1000 mg (164) (Figure 3-2). From a multiple dose study it was concluded that accumulation is negligible as the accumulation on days 1 and 8 for a 500 mg and 750 mg dose were 1.06.18 and 1.04.09 with a tw ice daily dosing regimen (163). The accumulation (Rss) for an eight hour dosing regimen should also be small based on a half-life of 3-4 hours and the formula, Rss=1/(1-e-ke*tau), where ke is the eliminati on rate constant and tau is the dosing interval. For example, if the hal f-life were 4 hours the ac cumulation would be 1.33. Finally, ceftobiprole displays a two-compartm ent body-model, which is demonstrated by a biphasic log concentrationtime profile (164). 47

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Protein Binding It has been shown for beta-lactams and other antimicrobials that only free drug is responsible for the pharmacological activity (138, 194) Therefore, it is important to accurately measure the plasma protein binding of each compound. In vitro experiments conducted in human plasma with physiologically relevant con centrations of ceftobipr ole, 0.5-100 mg/L, found the protein binding to be linear and ~16% measured by ultrafiltration (129). This is half the in vivo reported value of 38% (163). The protein binding was also determined in vivo in a microdialysis tissue distribution st udy and ranged from 17-32% with an average of ~22% (15). Volume of Distribution As typical of most beta-lactams, ceftobi prole displays a volume of distribution approximately equal extracellular flui d volume. This is due to the poor ability of beta-lactams to cross membranes making them a good therapeutic option for extracellula r infections. The Vdss has been reported as 15.5-21.7 L for a 500 mg 2 hour i.v. infusion (129, 131). It is independent of dose as shown by the single ascending dose and multiple dose studies where the volume of distribution ranged from 16.1 L to 19.8 L for doses ranging from 125-1000 mg given as a 0.5 hr i.v. infusion (163, 164). Tissue Distribution Microdialysis is a sampling technique which has proven suitable to determine free drug concentrations within the inters titial space fluid (ISF) of the tissue of interest (31, 127, 172, 182). The ability of ceftobiprole to penetrate into soft tissues was determined using microdialysis in healthy volunteers after a single dose (15). In th is study, two microdialysis probes were inserted into a thigh of each of the twelve subjects, one into the subcutaneous (s.c.) adipose tissue and one into the skeletal muscle. After each probe wa s calibrated by retrodialy sis (173), each subject received a single 2 hour i.v. infusion of 500 mg ceftobiprole. Ceftobiprole was found to 48

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penetrate into the ISF both of s ubcutaneous adipose tissue and skelet al muscle as the ratios of the area under the free concentration-time curve for tissue over plasma ( f AUCtissue/ f AUCplasma) was 0.49 and 0.69, respectively. Using radiolabelled-ceftobiprole in mice and rats it was found that ceftobiprole distributes rapidly into tissues with the hi ghest tissue to plasma ratio being 1.3 for kidney (90). It was also found it penetrates very little into the brain with a tissue to plasma ratio of 0.01 (90). Clearance and Metabolism In healthy volunteers administered 500 mg every 8 hours vi a 2 hr i.v. infusion, the amount of drug eliminated unch anged in the urine was 83%, with <7% repres enting the open-ring metabolite (131). At steady state the clearance of ceftobiprole, 4.98 L/hour for a 2 hour 500 mg infusion, was approximately equal to the maximum glomerular filtration rate multiplied by the fraction unbound suggesting clearance by glomerular filtration. In addition, the clearance of ceftobiprole was highly correlated to creatinine clearance, also i ndicating that this drug is eliminated by glomerular filtration (129). This was further supporte d by a probenecid study which eliminated the possibility of active tubular secretion and s ubsequently the possibility of drug-drug interactions through the pharmacokinetic changes in clea rance (129). Since this drug is predominately eliminated renally, drug interactions via the CYP enzymes are unlikely and confirmed with in vitro experiments with human microsomes and hepatocytes with CYP inducers and substrates (129). Half-life Ceftobiprole displays a half-life of ~3-4 hours, which is cons istent across all doses tested regardless of infusion time, with the exception of a reported half-life of 2.84 hours (P=0.055) for a 250 mg dose administered over 0.5 hours ( 129, 131, 163, 164). However, as expected, the half-life is significantly increased in patients with renal impairment with a reported half-life of 49

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11 hours in severe renal impairment (90). Theref ore, a dose adjustment is needed in patients with moderate renal impairment, 500 mg ever y 12 hours as a 2 hour i.v. infusion, and severe renal impairment, 250 mg every 12 hour s as a 2 hour i.v. infusion (90). Pharmacokinetics in Patients with Complicat ed Skin and Skin Structure Infections It is also important to dete rmine the PK in patients after the initial characterization in healthy volunteers, as they are not necessa rily the same. A phase II efficacy study was conducted to compare PK parameters in patien ts with cSSSI caused by Gram-positive pathogens and healthy volunteers each re ceiving a 30 minute i.v. infusi on of 750 mg (129, 162). In patients, the approximate steady state Cmax was 57.9.4 mg/L and the AUC0was 143.5mg*hr/L, which was comparable to the Cmax and AUC0in healthy volunteers of 60.6.99 mg/L and 165.8mg*hr/L, respectively. Drug Administration Ceftobiprole is administered as a 500 mg dose given via 2 hour i.v. infusion every 8 hours or 1 hour i.v. infusion every 12 hours in cases with documented Gram-positive infections excluding diabetic foot infection (90). The effi cacy of these dosing regimens was demonstrated in two large-scale tria ls (139, 140). It is delivered as th e water soluble prodrug, ceftobiprole medocaril, which is quickly and almost completely hydrolyzed in vivo to the active as can be seen by negligible prodrug plasma concentratio ns almost immediately after administration. In vitro experiments showed conversion to ceftobiprole is 38 seconds in human plasma (129). Type A esterases are thought to be res ponsible for this conversion as shown by inhibition studies with EDTA (129). Ceftobiprole can be administered according to standard dosing recommendations to both males and females and patients with hepatic impairment. In a study comparing gender differences in pharmacokinetics, systematic exposure (AUC0) was 15% higher in females than 50

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males. However, after the dose was normali zed on a mg/kg basis, there was no significant difference between the exposure in males and fema les and no dose adjustment was needed (161). In patients with hepatic impairment, no dose adjust ment is needed since the vast majority of the drug is eliminated renally. However, as previously mentioned patients with renal impairment may need a dose adjustment depending on the severity. Adverse Events The most common adverse events (AEs) am ong healthy volunteers and patients are presented in Table 3-3. Th e most common AE reported am ong healthy volunteers was dysgeusia, or taste disturbance (163, 164). This is likely due to the formation of diacetyl as the prodrug converts to the ceftobiprol e (Figure 3-3) and is supported by the fact that it primarily occurs during infusion as the rapid conversion is occurring. Additionally, it seems to be concentration dependent as all healthy voluntee rs receiving multiple 750 mg doses experienced this event. The following AEs not listed in the table occurred in one he althy volunteer; fatigue, feeling hot, pharyngitis, somnolence, and abnormal ur ine. In healthy volu nteers there were no clinically significant changes from baseline in clinical labs. In patients, the most common AE reported was nausea (139, 140). In this population dysgeusia was only reported in 30 patients, howev er, it was not reported in >5% of patients in the comparator study with ceftobiprole and vancom ycin plus ceftazidime. This is somewhat inconsistent as previous studies noted this as a common AE. In the two large-scale comparative studies the incidence and severity of adverse events were simila r in both arms, ceftobiprole vs. vancomycin and ceftobiprole vs. vancomycin plus ceftazidime, except hypersensitivity which occurred more in the vancomycin plus ceftazidi me arm. Also a total of 3 deaths occurred among the 932 patients in the ceftobiprole arms be tween the two studies but none were attributed to the study medication. 51

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Pharmacodynamics In Vitro Activity Ceftobiprole has demonstrated in vitro activity against a wide-range of Gram-positive and Gram-negative pathogens. The MIC90 of common pathogens for cSSSI and pneumonia, a possible second indication, are pres ented in Table 3-1. Especially noteworthy is the activity of ceftobiprole against severa l resistant pathogens incl uding MRSA, PRSP, and even heteroresistant, vancomycin-intermediate Staphylococcus aureus (VISA), MICs 2mg/L (56). The potency of ceftobiprole against these organisms lies within its inherent ability to bind to the PBPs which are associated with resistance in certain pathogens including PBP2x, PBP1a, and PBP2b associated with resistance in Streptococcus pneumoniae (51) and PBP2a of Staphylococcus aureus (50) and Staphylococcus epidermidis (82). The broad spectrum of activity of ceftobiprole can also be attributed to the ability to withstand hydrolysis by certa in beta-lactamases, displayi ng an MIC of 0.25 mg/L against Staphylococcus aureus with PC1 beta-lactamase, 0.25 mg/L and 0.5 mg/L against Klebseilla pneumoniae with TEM-26 and SHV-1, respectively, and 0.5 mg/L against Escherichia coli with TEM-1 (150). However, it should be noted that ceft obiprole is susceptible to hydrolysis by some beta-lactameses; e.g. ESBL CT X-M-15, carbapenemases VIM-2 and KPC-2, and some AmpC of Pseudomonas aeruginosa (150). Additionally, ceftobiprole does not bind sufficiently to PBP5 of Enterococcus faecium (82) which explains its poor activity against this pathogen, MIC90 of >32 mg/L (92). Also noteworthy, ceftobiprole is bacterialcidal as demons trated by an MBC/MIC ratio 4 with a majority of resistant pathogens includ ing MRSA, hVISA, and PR SP (56). It was also found to be bactericidal against Haemophilus influenzae at concentration of 2XMIC, MIC 2 mg/L, and several Gram-positive cocci at a concentration of 4 mg/L including Streptococcus 52

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pneumoniae viridans group streptococci, Staphylococcus aureus coagulase-negative staphylococci, and Enterococcus faecalis in time-kill studies (22, 57). Resistance Studies Once drugs hit the market and wide-spread use has occurred there is an opportunity for resistance to develop. Therefore, it is importa nt to evaluate the possibility of resistance development in order to make a recommendation for drug usage. This has been done with ceftobiprole using serial passage in subMIC concentrati ons. The potential for resistance development was low as after 50 passages; the highest MIC increase was 4XMIC (22, 23). This only occurred in one VISA vancomycin-intermediate Staphylococcus aureus strain of the ten Staphylococcus aureus strains tested (23) and in only one Haemophilus infuenzae stain of the eights strains tested (22). This wa s similar to previous findings using Staphylococcus aureus strains, three methicillin-resist ant and one susceptible, which f ound only a 2-fold increase in the MIC after six passages (82). Add itionally, no resistance was observed in vivo when lung homogenates from pneumococcal mice treated with ceftobiprole after inf ection with PRSP were plated for MIC comparison after treatment (12). The same was found with MRSA and VISA when homogenized tissues where plated and MICs determined from the aortic valve, spleen, and kidney after induced endocarditis (36). In Vivo -Animal Studies The in vivo pharmacodynamics of ceftobiprole have b een characterized in several animal models including mouse pneumococcal pneumonia, mouse Enterococcus faecalis peritonitis, mouse septicemia, mouse subcutane ous (s.c.) abscesses, and rabbit Staphylococcus aureus aortic valve endocarditis. In support of the lead indication of cSSSI ceftobiprole demonstrated good potency against MRSA and VISA in the mouse s.c. abscesses model (82). In this study, doses were administered 1 and 3 hours after infection by s.c. injection of the inoculum under the loose 53

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skin of the groin. The animals were killed three days post infection to determine the CFU/abscess and ceftobiprole proved to be more potent than competitors with a 5.12 log decrease in CFU compared to control animal s versus a decrease of 3.42 and 0.80 log CFU for vancomycin and linezolid against MRSA compar ed to controls. With VISA, ceftobiprole displayed a decrease of >4.79 CFU compared to a decrease of 0.13 and 0.64 log CFU for vancomycin and linezolid, respectively. For the potential indication of pneumonia it is also important to evaluate the pharmacodynamics of ceftobiprole in pneumococcal pneumonia (12). A study was conducted with neutropenic Swiss albino mice infected with 107 CFU into the lower respiratory tract. While there were no significant di fferences between ceftobiprole a nd ceftriaxone in this survival study, the doses used for ceftobiprole, 51 and 75 mg/kg/day, were much lower than the doses needed of ceftriaxone, 200 and 400 mg/kg/day, to produce a comparable survival rate against P40984, a ceftriaxone-resistant PRSP strain. The doses needed for ceftobiprole were less with P52181, a penicillin-cefotaxime-cetriaxone susceptible strain, 2.1-4.2 mg/kg/day, to produce a similar survival rate compared to ceftriaxone, 10-20 mg/kg/day. Additionally, ceftobiprole has shown good activity against a range of bacteria in a septicemia model. In Swiss albino mice infected with intraperitoneal inj ection, doses were given at 1 and 3 or 1, 3, and 5 hr after infection depending on the bacteria used. With MRSA, ceftobiprole was more potent, ED50 2.4 mg/kg, than cefepime, ceftr iaxone, meropenem, all with ED50s >25mg/kg, and vancomycin, ED50 6.7mg/kg (82). Ceftobiprole was also effective against several PRSP strains with ED50 0.6-1.1 mg/kg (82). Similarly, in mice infected with four strains of Enterococcus faecalis, including two vancomycin-resistant strains, by intraperitoneal injection the 50% protective dose was lower for ceftobiprole co mpared to ampicillin in all strains and was 54

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significantly lower in the beta-lactamase producing strain HH22(TX0921), 2mg/kg vs. >100mg/kg (10). The in vivo pharmacodynamics for ceftobiprole have also been explored in the rabbit endocarditis model with MRSA and VISA, showing it may have potential to treat deep-seated infections. With MRSA-76, cef tobiprole and vancomycin show ed a significant reduction of CFU/g in the aortic valve vege tation, spleen, and kidney compar ed to control animals. In endocarditis by VISA, animals treated with ceft obiprole demonstrated a significantly lower CFU/g than both the control animals and vancomyc in treated animals in aortic valve vegetation, spleen, and kidney (36). In Vivo-Pivotal Studies Ceftobiprole was evaluated for the treatment of cSSSI caused by Gram-positive bacteria and compared to vancomycin in a large-scal e study (140). This tr ial involved 282 patients receiving ceftobiprole 500 mg twice daily a nd 272 patients receiving vancomycin 1 g twice daily. There was no significant difference betw een the cure rates for ceftobiprole, 93.3%, compared to vancomycin, 93.5%. Interestingly, in this study it wa s found that in PantonValentine leukocidin (PVL)-posit ive MRSA, ceftobiprole had a hi gher cure rate, 93.1%, than vancomycin, 84.6%. This is clinically relevant b ecause the PVL genotype is associated with the more virulent community acquired-MRSA and maybe the cause behind increased ambulatory visits (83). The efficacy of ceftobiprole was also compar ed to vancomycin plus ceftazidime for treatment of both Gram-positive and Gram-negativ e cSSSI (139). This study enrolled patients 2:1 into the ceftobiprole arm so that a total of 485 patients and 244 were clinically evaluable for ceftobiprole and vancomycin plus ceftazidime, respectively. The clinical cure rates were 90.5% for ceftobiprole and 90.2% for vancomycin plus ceft azidime. It was also noted in this study that 55

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in the subgroup of diabetic patient s with foot infection, ceftobiprole was just as efficacious as the competitor, 86.2% and 81.8% clinical cure rate. Additionally, ceftobiprole was just as effective in severe infections; severity was based on C-re active protein, whether the infections involved fascia or muscle, and PVL-MRSA infection. Pharmacokinetics/Pharmacodynamics (PK/PD) PK/PD Characterization The PK/PD indices used for the characterization of antibiotics have been well established and most antibiotics are frequently placed into one of two categories (42) In one category, the time the free antibiotic concentra tion remains above a threshold value, the MIC, is usually indicative of efficacy. In the other category, efficacy is usually correlated to a ratio of exposure, Cmax or AUC, and the MIC. The efficacy of be ta-lactams, including ceftobiprole, in usually correlated to the f T>MIC and this relationship between the dos ing regimen and effect is usually found by performing dose fractionation studies. The PK/PD relationship of ceftobiprole was characterized in the neutropenic mouse thigh in fection model with several Gram-positive and Gram-negative strains (9). Twenty-four hours po st infection, the animal s were euthanized and the thighs were homogenized so that viable b acteria could be determined. For MSSA and MRSA the f T>MIC needed for stasis was 14.4-27.8% of the dos ing interval. This is slightly lower than the recommended 40-50% to achieve bacterial stasis with gram-positive organisms (42). For Gram-negative organisms in this experiment the f T>MIC was longer and ranged from 41.258.6%, which is close to th e usually recommended breakpoint for Gram-negatives, f T>MIC of 40% of the dosing interval (30). PK/PD for Dose Selection Once the PK/PD indices were established this information was used to optimize the dosing regimen. Dose selection was done using Monte Ca rlo simulation in two st udies. The first study 56

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used data from 12 healthy volunteers, 6 receivin g 500 mg and 6 receiving 750 mg doses (120). The population PK parameters were cal culated and based on a target of f T>MIC>40%, MCS were performed and a conservative dosing recommen dation was made of 750 mg twice daily. A second study was conducted using a much larger and more varied population to find the PK parameters, which included 150 subjects, 29 of which were from a phase II trial (107). In this study 2 regimens were examined 500 mg ever y 8 hours (0.5, 1, 2 hour infusions) and 500 mg every 12 hours (1 hour infusion). This study also examined the impact of renal function based on a creatinine clearance distribut ion from previous studies which used a similar population. The recommendation was made that in patients wi th cSSSI the dosing regimen should be 500 mg every 12 hours as a 1 hour i.v. infusion. This dosing regimen was selected for a pivotal comparative study with vancomycin against Gr am-positive bacteria (140). The final dosing recommendation for nosocomial pneumonia was 500 mg every 8 hours delivered as a 2 hour infusion. The appropriateness of this dose was examined in a microdialysis study which determined that free drug concentrations in the ISF of s.c adipose tissue and skeletal muscle remained above the MIC, for an MIC of 2 mg/L, for greater than 40% of the 8 hour dosing interval. For an MIC of 4 mg/L the f T>MIC was approximately 72% in plasma, 54% in skeletal muscle, and 35% in s.c. adipose tissue for an eight hour dosing regimen (15). Summary The pharmacokinetics of ceftobiprole are similar to other beta-lactams in that it displays a two-compartment body-model, dist ributes into extracellular fluid, does not cross membranes well, and is primarily cleared rena lly. It also displays a safety profile similar to other betalactams, with the exception of dysgeusia being a common AE. Additionally, the pharmacokinetics and clearance mechanisms leav e the potential for drug-interactions low and 57

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dose adjustment in special populations, i.e. re nally impaired, noncomplex. The potential for resistance development is low and therefore cef tobiprole is a good first-line therapeutic option against a variety of infections. This compound is not active against all pa thogens and is subject to hydrolysis by some ESBLs and carbapenemases. However, as curren t therapeutic options dwindle with resistance devel opment, ceftobiprole is a promis ing new cephalosporin with a wide-range of activity, including MRSA. 58

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Table 3-1. In vitro activity of Ceftobiprole against common skin and soft tissue and respiratory pathogens (73, 82, 92, 155) MIC90 MIC range Staphylococcus aureus Methicillin-Susceptible 0.5-1 0.12-2 Methicillin-Resistant 1-4 0.12-4 Methicillin Susceptible Coagulase Negative 0.25 0.012-1 Methicillin-Resistant Coagulase Negative 1-2 0.012-8 Streptococcus.pneumoniae Penicillin-Susceptible 0.015 0.012-0.3 Penicillin-Resistant 0.25-2 0.012-4 Viridans group streptococci penicillinresistant 0.25-1 0.012-32 Beta-hemolytic streptococci 0.015-0.06 0.012-0.25 Enterococcus faecalis 2-4 0.12->32 Enterococcus faecium >32 0.25->32 Haemophilus influenzae ampicillinsusceptible 0.06-1 0.015-1 Moraxella catarrhalis 0.12-1 <0.008-1 Escherichia coli 0.06-0.12 0.015-2 ESBL E. coli >32 0.03->32 Klebsiella pneumoniae 0.06->8 0.015-16 ESBL K. pneumoniae >32 0.015->32 Acinetobacter spp. >32 0.015->32 P. aeruginosa ceftazidime susceptible 8-16 0.12-16 59

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Table 3-2. Pharmacokinetics following single and multiple doses presented as mean (standard deviation) (129, 131, 162-164) 500 mg Dose SD 0.5hour infusion SS q12 hr 0.5hr infusion SD 1hr infusion SD 2hr infusion SS q8hr 2hr infusion N=11 N=6 N=18 N=28 N=27 Cmax 38.3(7.1) 44.2(10.8) 34.2(6.1) 29.2(5.5) 33.0(4.8) AUC089.9(6.7) 108(22.2) 116(20.2) 104(13.9) NC t1/2 3.54(0.40) 4.04(0.31) 2.85(0.55) 3.10(0.30) 3.3(0.3) CLs 5.69(0.41) 5.05(0.95) 4.46(0.84) 4.89(0.69) 4.98(0.58) Vss 17.9(2.0) 16.7(3.6) 11.0(2.9) 21.7(3.3) 15.5(2.3) 750 mg Dose SD 0.5hr infusion SS q12hr 0.5hr infusion SS q12hr 0.5hr patients N=30 N=6 N=22-25 Cmax 58.8(10.0) 60.6(10.0) 57.9(29.4)* AUC0151(20.9) 165(12.8) 165(39.5) T1/2 3.16(0.43) 4.11(0.41) 3.06(0.62) CLs 5.08(0.71) 4.84(0.34) 5.99(1.74) Vss 15.2(2.7) 16.1(2.2) 20.1(5.2) The infusion time in patients ranged from 2290 minutes. SD=single do se. SS=steady state. 60

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Table 3-3. Most common adverse events in healthy volunteers and patients (139, 140, 163, 164) Healthy Volunteers Patients Total Number of Subjects 42 932 Total Number of Subjects with at least one AE 21 507 Total Number of Subjects with at least one serious AEs 0 63 Dysgeusia 17 30 Nausea 10 113 Headache 10 68 Abdominal Pain 2 Vomiting 1 61 Diarrhea 1 62 Constipation 0 33 Hypersensitivity* 0 49 Infusion Site Reaction 1 48 *including rash and pruritus. not specifi cally listed. 61

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Figure 3-1. Mean concentration-time profile for a 500 mg two hour i.v. infusion in healthy volunteers (n=12). Error bars represent standard deviati on. Modified from (15). 62

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Dose (mg) 020040060080010001200 Vss (L) 5 10 15 20 25 30 Dose (mg) 020040060080010001200 CLs (L/hr) 0 2 4 6 8 10 Dose (mg) 020040060080010001200 Dose Normalized AUC (mg*hr/L) 0 10 20 30 40 Dose (mg) 020040060080010001200 Dose Normalized Cmax (mg/L) 0 2 4 6 8 10 12 14 Figure 3-2. A-Mean volume of distribution at steady state (Vss) vs. dose. B-Mean systemic clearance (CLs) vs. dose. CMean dose normalized AUC0vs. dose. D-Mean maximum concentration (Cmax) vs. Dose. Dose normalized to the 125 mg dose. Error bars represent stan dard deviation (164). 63

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Figure 3-3. Formation of diacetly (2,3-butan edione) during the conve rsion of ceftobiprole medocaril (top) to the active moiety ceftobiprole (bottom) (164). 64

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CHAPTER 4 IN VITRO MICRODIALYSIS OF CEFTOBIPROLE Objective The aim of this study was to determine the abil ity of ceftobiprole to cross the microdialysis (MD) membrane using two dose ranging, in vitro microdialysis experiments. The two experiments performed used the ex traction efficiency (EE) and re trodialysis (RD) methods. In both of these methods the recovery percent (R%) was determined. The R% had to be more than 10% if microdialysis was to be used fo r sampling ceftobiprole from soft tissues. Chemicals and Equipment Test Article Ceftobiprole (BAL9141) was provided by Johnson and Johnson. The compound was stored in the original shipping box and vial in the -70C freezer. Ceftobiprole-BAL9141: Provi ded by Johnson & Johnson Pharmaceutical Research and Development 920 U.S. Route 202 P.O. Box 300 Raritan, NJ 08869 Reagents All reagents were of HPLC grade unless otherw ise stated. They were obtained from the indicated sources or equivalent suppliers. Double distilled water Filtered in house by Corning AG-3 Acetonitrile Fish er Scientific A998-4 Lactated Ringers solution Baxter 2B2323 DMSO Fisher Scientific BP231-1 Formic Acid Fisher Scientific A118P-100 Equipment The following pieces of equipment or equivalent substitutes were used. 65

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Balance Mettler AE240 Vortex Kraft Apparatus Inc. Model PV-5 Micropipettes Eppendorf Research Pipette tips (1-200 L) Fisherbrand 22-707-500 Pipette tips (100-1000 L) Fisherbrand 21-197-8F Autosampler vials Sun Sri 200 046 Aluminum seals Sun Sri 200 100 Sonicator Fisher Scientific FS110H 15mL centrifuge tubes Corning 430052 HPLC Agilent 1100 Series Column Supelco C18 Discovery 4.6mm, 15 cm, 5,6m Analytical software Agilent Te chnologies-Agilent ChemStation Syringes Becton Dickinson 309603 Microcentrifuge Tubes Fisherbrand 05-408-129 Syringe Pump Harvard Apparatus Model 55-4150 Heated Stir Plate Fisherbrand Isotemp Thermometer Fisherbrand 76mm Immersion 14-997 Guard Column C18 2cm 30-40 micron (made in house) Microdialysis Probes CMA-60 P000002 Reagent Preparation Ceftobiprole Standards and Quality Control Solutions BAL9141 was provided as pure powder. 10 mg we re weighed out and dissolved in 10 mL of 0.1 % formic acid in DMSO. The 1000 g/mL stock solution was diluted to a secondary stock of 100 g/mL with lactated Ringers solu tion. From here the working standards were prepared by serial dilution with lactated Ringe rs solution. The standard curve ranged from 1000.049 g/mL. Quality controls (QCs) of 0.098, 3.13, and 50 g/mL were used for the low, mid, and high QCs, respectively. The standards and qu ality controls were prepared using the same dilution scheme (Table 4-1). HPLC Mobile Phase 950 mL of double distilled wa ter was mixed with 50 mL of acetonitrile and degassed by sonication. 66

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0.1% Formic Acid in DMSO 0.114 mL of 88% formic acid was added to a 100 mL volumetric flask and filled with DMSO. Sample Preparation Calibration Solutions for Microdialysis Six calibration solutions of BAL9141 (25, 12.5, 6.25, 3.13, 1.56, 0.78 g/mL) were prepared. This was done by preparing a 1mg/ mL stock solution of BAL9141 in 0.1% formic acid in DMSO. Then a 100 g/mL solution was prepared using lactated Ringers solution. From here serial dilutions were perfor med with lactated Ringers solution to make all other solutions. The concentrations selected were chosen because the expected maximum concentration in soft tissues was ~30 g/mL. Dialysate Samples During the sampling period approximately 30L of sample were collected. The sample was divided into two equal aliquots of 12L and then each aliquot was diluted with 24L of lactated Ringers solution to obtain a sufficien t sample volume for HPLC analysis. The samples taken from the calibration tube and/or the syringe were also diluted 2:1 with lactated Ringers solution. Therefore, to get the true concentrat ions the values obtained were multiplied by three. Apparatus Setup Before the experiments were started each MD probe was checked for functionality. To do so, the inlet of the MD probe was connected to a syringe containing blank lactated Ringers solution. The probe was flushed manually. The pr obe was functional and ready to use when no liquid drops appeared on the MD probe membrane. The solution should only exit the probe from the outlet tubing. If droplets appear on the membrane, the probe was not used. 67

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To control temperature the sampling device wa s assembled on a heated stir plate and was maintained at 37oC. During setup, a 5mL syringe was fille d either with blank lactated Ringers solution (EE method) or analyte solution (RD method) and the encl osed air was cleared from the syringe. The syringe was put in place on the syringe pump and fastened. The pump was then connected to the inlet of the probe and run at a flow rate of 1.5 L/min for 15min to allow for equilibration. The probe itself was in a 15mL centrifuge tube c ontaining either blank lactated Ringers solution (RD method) or an alyte solution (EE method). Attention was paid so that the membrane of the probe is completely covered with fluid and that it did not touch the wall of the tube. The dialysate was collected in a microcentrifuge tube cove red with parafilm, which helped to fix the outlet tubing from the microdialysis probe in place and a void evaporation during sampling. Sample Analysis HPLC/UV Set Up The HPLC system was the Agilent 1100 series which included a DAD detector (G1315B), an autosampler (G1329A), a column oven (G1316A), a degasser (G1379A), and a quaternary pump (G1311A). The work station for data retention was an hp Compaq p4. The use of a guard column was optional. HPLC Pump Conditions Mobile Phase: 95% Distille d Water, 5% Acetonitrile Flow rate: 1.0 mL/min Retention Time: ~3.5 min Autosampler Conditions Injection Volume: 20l Run time: 8 min 1 injection per vial (blanks may be injected more than once) 1 vial per sample 68

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Temperature: 4C Detector Conditions Wavelength: 300nm Analysis Procedure The test samples were run with a calibration cu rve and 3 sets of quality control standards at 3 levels (low, medium, and high) placed throughout the run. A blank injection of lactated Ringers solution and a blank injection of 0.1% formic acid in DMSO were included. Microdialysis Introduction Microdialysis (MD) is an extremely useful tool for antibiotic sampling because the samples are taken directly from soft tissues, the most common site of infection, and because only the free, pharmacologically active drug is able to pass through the probe membrane. In this technique, the microdialysis probe is placed into the tissue of interest a nd continuously perfused with a physiological solution (perfusate). Ba sed on diffusion, the drug passes from the tissue into the probe and is collected (dialysate). Id eally, an absolute equilibrium between the tissue and perfusate will be established. In reality, due to the fact that the MD probe is perfused at a constant flow rate of 1.5L/min, an absolute equ ilibrium will not be reache d. The ability of the drug to pass through the membrane and establish equilibrium at this fl ow rate will be established. It is termed the recovery (R ) and this value has to be know n to back-calculate the actual concentration at the sampling site, Ctissue, from the concentration in the dialysate, Cdialysate. This is done by using the following equation: 1% 100 RC Cdialysate tissue In microdialysis, the sampling time is determ ined by the flow rate. A higher flow rate would lead to a shorter sampling time since th ere is a minimum volume requirement. However, 69

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the recovery is decreased because there is not enough time for equilibration between the solution inside the probe and the surrounding media to occu r. Therefore, a compromise has to be made between sample volume and flow rate. Depending on the sensitivity of the assay, the sample volume should not be smaller than 20 L. Therefore, at a flow rate of 1.5 L/min and a sampling time of 20min, 30L are collected. The equilibration period is determined by th e dead volume of the MD probe tubing which can be calculated from the manufacturers sp ecifications. Since this experiment will be performed using six different con centrations, all of th e tubing has to be completely flushed before the sampling procedure can start. The eq uilibration time is the pr oduct of dead volume multiplied by flow rate. Extraction Efficiency Method (EE) In the EE method, blank lactated Ringers so lution was pumped through the MD probe at a flow rate of 1.5 L/min. The MD probe was then placed into the calibration tube containing analyte solution, starting with th e lowest concentration. Drug diffused from the calibration tube into the MD probe, and the dialysate was collected for analysis. Each sample was collected for 20min after the end of a 15min e quilibration period. To ensure that the prepared solution was the concentration expected within the calibration tube two samples were taken from this tube, one before the sampling period and one after. It wa s important to sample fr om the calibration tube since it was critical to know th e actual concentration in the tube to perform the calculations. Additionally, the two samples can be compared to see if the concentration within the calibration tube was consistent throughout the sampling pe riod. The same procedure was done for the remaining five samples. After the highest concentration was completed th e probe was flushed for one hour with blank lactated Ringe rs solution. All experiments we re performed in triplicate. The percent recovery, R%, for the EE method was calculated as follows: 70

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perfusate dialysateC C R 100% Retrodialysis Method (RD) In the RD method, the syringe contained th e analyte solution that was pumped through the MD probe at a flow rate of 1.5 L/min. The MD probe was placed into a calibration tube that was filled with approximately 10mL of blank lact ated Ringers solution. The analyte diffused out of the probe into the calibration tube. The lo ss of analyte through the membrane was then determined from the Cdialysate. Samples were taken for 20min after the end of the 15min equilibration period. To ensure that the prepared solution was th e concentration expected within the syringe, a sample was taken from the syri nge after the sampling period. Additionally, two samples were taken from the calibration tube, one before and one after the sampling period, to see if the concentration within the tube was consistent thr oughout sampling. Again, the lowest concentration was sampled first. In this me thod, the calibration tube, which contains a small amount of analyte after the sampling period, had to be exchanged with a new tube containing fresh blank lactated Ringers solution. The sa me procedure was done for the remaining five samples. After the highest concentration was sampled the probe was flushed for one hour with blank lactated Ringers solution. All experiment s were performed in triplicate. The percent recovery, R%, for the RD met hod was calculated as follows: perfusate dialysateC C R 100100% Results Method Validation Results A calibration curve of 0.049-100 g/mL was used. Quality controls of 0.098 g/mL, 3.13 g/mL, and 50 g/mL for low, mid, and high re spectively, in triplicate were incorporated. 71

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This method provided reasonable accuracy and precision (Table 4-2). The analysis was performed with weighted linear regression (1/X2). The slope for the standards was 15.39 and the intercept was -0.03. Also, the R2 value was 0.999996. The retention time of ceftobiprole was approximately 3.5 minutes. In vitro Microdialysis Results In this experiment two in vitro microdialysis methods were us ed, the extraction efficiency (EE) and the retrodialysis (RD) methods. Both methods are acceptable to characterize how the compound interacts with the MD membrane a nd if the compound can freely pass through the membrane. These in vitro experiments were done as a preliminary study to an in vivo experiment. There are some funda mental differences in the set up of both experiments which can explain the difference in R%. The retrodialysis method is the same method which will be used in the in vivo experiment for MD probe calibration. See Table 4-3 for results. Conclusions This experiment confirmed that ceftobiprole has the ability to freely cross the microdialysis membrane. The R% was well over 10% and therefore, microdialysis may be used as a sampling technique to obtain a PK profile. 72

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Table 4-1. Standard pr eparation of BAL9141 Starting Concentration (g/mL) Volume (mL) Final Concentration (g/mL) Total Volume (mL) 1000 0.2 100 2 100 1 50 2 50 1 25 2 25 1 12.5 2 12.5 1 6.25 2 6.25 1 3.13 2 3.13 1 1.56 2 1.56 1 0.78 2 0.78 1 0.39 2 0.39 1 0.20 2 0.20 1 0.098 2 0.098 1 0.049 2 73

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Table 4-2. Method validati on accuracy and precision Quality Controls Conc Observed Conc Mean Observed SD CV% Accuracy % Mean Accuracy % A 0.098 0.088 0.090 0.01 7.43 89.80 91.50 A 0.098 0.097 99.00 A 0.098 0.084 85.71 B 3.13 3.10 3.07 0.22 7.24 99.04 98.00 B 3.13 3.27 104.47 B 3.13 2.83 90.42 C 50 52.29 52.44 0.96 1.84 104.58 104.88 C 50 53.47 106.94 C 50 51.56 103.12 Conc=Concentration (g/mL) 74

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Table 4-3. In vitro microdialysis results Concentration (g/mL) EE% SD R% SD 0.78 91.08 23.72 72.72 28.76 1.56 86.38 15.25 79.62 5.37 3.13 86.44 14.75 83.00 5.90 6.25 89.06 8.29 81.25 2.70 12.5 86.50 12.16 80.70 2.39 25 89.21 7.57 77.06 5.44 All samples mean (SD) 88.25 (12.15) 79.06 (11.03) 75

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CHAPTER 5 HPLC/UV METHOD VALIDATION OF CEFTOB IPROLE IN LACTATED RINGERS SOLUTION Objective The objective of this series of experiments was to valid ate an HPLC/UV method for the determination of ceftobiprole in lactated Ri ngers solution using good laboratory practices (GLP). The assay was designed to be used in an in vivo microdialysis study of ceftobiprole in humans. The assay was validated after in vitro studies deemed ceftobiprole suitable for use with the microdialysis sampling technique. Validation Procedure One standard curve and three of each QC c oncentration were assayed on each analytical day for three days to find the lower limit of quantification (LOQ) and linear range using inter/intra-batch accuracy and precision. The acceptance criteria were defined as accuracy between 80-120% at the (LOQ) and 85-115% for all other standards and QCs. Precision was defined as relative standard deviation and must be <20% at the LOQ and <15% at all other concentrations. The accuracy% was calculated as follows: 100* ][ ][ % Expected Measured Accuracy The following parameters were also invest igated during the validation: freeze/thaw stability of quality control samples and stock st andard solution, refrigeration stability of quality control samples, room temperature stability of quality control sample s and stock standard solution, robustness of the method, a nd assay selectivity. For a set of samples to be considered acceptable two-thirds of samples must meet acceptance criteria. 76

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Results Reproducibility of the Calib ration Curve Parameters The 3 calibration curves generated during th e determination of interand intra-day precision and accuracy were linear with an average slope of 16.815 0.6688. Consistently good correlation coefficients (r2>0.9999) were obtained in th ese experiments. A 1/X2 weighting scheme was used. This option provided a similar correlation coefficient to the linear model and a y-intercept closer to 0. Lower Limit of Quantification The limit of quantification (LOQ) was identified as 0.1 g/ml. It was defined as the lowest concentration of quality controls used in this validation for which the accuracy% was between 80-120%. Intra-batch Variability for Quality Control Samples Intra-batch evaluation of the analyte was perf ormed on three different days. Intra-batch variability on day 1 was 3.78%, 2.57%, 0.345% and 0.569% for the 0.1, 0.2, 20, and 40 g/ml quality control samples, respectively (n=3, Day 1). Accuracy for day 1 of all samples ranged from 101.1% to 110.3% (Day 1, Table 5-1 for averag es). Intra-batch variability on day 2 was 10.7%, 5.07%, 1.91% and 1.66% for the 0.1, 0.2, 20, and 40 g/ml quality control samples, respectively (n=3, Day 2). Accuracy for day 2 of all samples ranged from 90.94% to 114.4% (Day 2, Table 5-1 for averages). Intra-batch variability on day 3 was 9.09%, 3.33%, 1.39%, and 0.894% for the 0.1, 0.2, 20, and 40 g/ml quality contro l samples, respectively (n=3, Day 3). Accuracy for day 3 of all samples ranged fr om 88.49% to 106.1% (Day 3, Table 5-1 for averages). No QC sample fell out of range. 77

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Inter-batch Variability for Quality Control Samples Inter-batch variability was 8.06%, 7.07%, 2.89%, and 2.75% for the 0.1, 0.2, 20, and 40 g/ml quality control samples, respectively (T able 5-2). Mean accuracy was between 101.7% and 104.3% (Table 5-2). The accuracy range base d on individual QCs is already stated above. Freeze-thaw Stability Three cycles of freeze/thawing were performe d on the LOQ, low, mid, and high quality controls (0.1, 0.2, 20, and 40 g/ml, n=3) betw een 24May07 and 25May07. The QCs were also injected with the standard curve before freezi ng to ensure correct preparation. The following time table was followed: Freeze 1: 5:15 pm 24May07 Thaw 1: 8:26 pm 24May07 Freeze 2: 9:31 pm 24May07 Thaw 2: 11:30 am 25May07 Freeze 3: 12:37 pm 25May07 Thaw 3: 2:47 pm 25May07 The samples were stable for two freeze/thaw cy cles (Table 5-3). One of the 0.2 g/ml QC samples fell out of acceptance criteria after the third freeze/thaw cycle with an accuracy of 80.881%. The ranges for accuracy are 94.99%-111.0%, 86.51%-103.3%, and 80.32%-94.89% for the 1st, 2nd, and 3rd, freeze/thaw cycles respectively. Ther efore, it is concluded that the QCs are stable for 2 freeze thaw cycles. The freeze/thaw stability of the st ock standard solution was also tested due to the fact that ceftobiprole is diluted in a differe nt matrix (0.1% formic acid in DMSO) than the QC samples. It is important that ceftobiprole is stable in this DMSO solution because th e stock standard cannot be prepared fresh daily due to the limited amount of sample. To test its freeze/thaw stability, standard curves were compared and analyzed as quality control samples. The standard curve that was prepared fresh from the powdered compound on 21May07 is used as the true standard curve 78

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and all subsequent standard samples are analyzed as QCs. The standard curves prepared on 24May07, 28May07, 29May07, 04Jun07, and 11Jun07, and 13Jun07 were analyzed. Additionally, the stock standard solution wa s thawed on 08Jun07 but the samples were not analyzed due to poor chromatograph y. This results in a total of 7 cycles over 23 days and shows that the stock standard was stable over this time (Table 5-4). The inter-b atch accuracy of all samples individually ranged from 88.41%-118.4% (thi s sample was at the LOQ). All individual samples were within acceptance criteria. Only accuracy was compared to validate the stock standard stability. If degradation were occu rring the accuracy% would be out of acceptance criteria. Stability at Room Temperature The stability of ceftobiprole stock standard solution and QCs were tested at room temperature. To do so a standard curve and se t of QCs were prepared. Then after a defined length of time a second set of QCs were prepared from the stock standard left out on the benchtop, and injected onto the colum n. The concentrations of these QC samples were determined using the standard curve injected previously. Th e stock standard was shown to be stable for 5.5 hours at room temperature (Table 5-5). The accuracy of each individual QC sample ranged from 89.86%-108.51%. To test the stability of ceftobiprole in lactated Ringers solution a standard curve and a set of QCs were prepared. Then an aliquot of each of the QCs was injected with the standard curve while the remaining portion was left at room temperature. At a defined length of time, another aliquot was taken from the portion at room temperature and loaded into the autosampler. It should be mentioned that degradation at room te mperature is much greater than degradation at 4C, the temperature of the autosampler. The quality controls were shown to be stable for 3 79

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hours at room temperature (Table 5-6). The accuracy of each individual QC sample ranged from 89.15%-104.2%. Refrigeration Stability of QCs To test the stability of QC samples at 4C the set of QC prepared on 21May07 was reinjected 24 and 48 hours later. The standard curve from 21May07 was used to calculate the concentration of the QCs after storage. The accuracy of each individual QC sample after 24 hours ranged from 91.57% to 104.31%. The accur acy of each individual QC sample after 48 hours ranged from 96.89% to 113.63% (Table 5-7). Freezer (long-term) Stability Long-term freezer stability has been demonstrat ed for 32 days of ceftobiprole in lactated Ringers solution. An aliquot of each sample prepared on 27Sep07 was frozen at -70C and analyzed on 29Oct07. The standard curve from 27Sep07 was used for analysis. The QC-2-0.2 g/mL sample was originally out of range. A confirmation injection was done on 30Oct07 and the sample was within acceptance criteria. Th is value was used in the calculations for the summary table (Table 5-8). Robustness To test the ability of this method to endure changes a different column was used to test accuracy and precision. Column ID 89216-02 was used instead of column ID 86248-02, which was used for most other validation experiment s. The intra-batch precision was 7.61%, 7.34%, 2.12%, and 1.19% for the 0.1, 0.2, 20, and 40 g/ml quality control samples, respectively (n=3) (Table 5-9). Accuracy ranged from 96.64%-113.1% for individual samples. 80

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Chemicals and Equipment Test Article Ceftobiprole (BAL9141) was provided by Johnson and Johnson. The compound was stored in the original shipping box and vial in the -70C freezer. Johnson & Johnson Pharmaceutical Research and Development 920 U.S. Route 202 P.O. Box 300 Raritan, NJ 08869 Reagents All reagents were of HPLC grade unless otherw ise stated. They were obtained from the indicated sources or equivalent suppliers. Double distilled water Filtered in house by Corning AG-3 Acetonitrile Fish er Scientific A998-4 Lactated Ringers solution Baxter 2B2323 DMSO (Dimethylsulfoxide) Fisher Scientific BP231-1 Formic Acid Fisher Scientific A119P-10 Equipment and Disposables Balance Mettler AE240 Vortex Kraft Apparatus Inc. Model PV-5 Micropipettes Eppendorf Research Pipette tips (1-200 L) Fisherbrand 22-707-500 Pipette tips (100-1000 L) Fisherbrand 21-197-8F Autosampler vials Sun Sri 200 046 Aluminum seals Sun Sri 200 100 Sonicator Fisher Scientific FS110H Centrifuge tubes (15 mL) Corning 430052 Microcentrifuge tubes Fisherbrand 05-408-129 HPLC System Agilent 1100 Series Work Station hp Compaq p4 Column Supelco C18 Discovery 4.6mm, 15 cm, 5,6m Analytical software Agilent Te chnologies-Agilent ChemStation Guard Column C18 2cm 30 -40 micron (made in house) Manual Crimpers Fisher 03-375-7 Volumetric flask Pyrex 5640 Microsyringes Tyco Healthcare 8881501400 81

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Plastic Cannula BD 303345 Graduated Cylinder Pyrex 2982 Reagent Preparation Ceftobiprole Stock Standard Solution A 1 mg/mL stock standard solution of ceftobi prole was prepared by weighing out 10 mg of ceftobiprole and dissolving it in 10 mL 0.1% fo rmic acid in DMSO. This was done by adding the ceftobiprole to a 10 mL volumetric flask and f illing with the solvent. A secondary stock of 100 g/mL was prepared using a microsyringe and adding 0.1 mL of stock standard solution to 0.9 mL of lactated Ringers solu tion. All standard solutions we re prepared fresh daily, except the stock standard solution. The 1mg/mL stock is stored at -70C unt il needed. Ceftobiprole Working Standard Solutions After the 100 g/mL secondary stock solution was prepared, the working standards were prepared with serial dilutions using lactated Ringers solution (Table 5-10). The highest concentration in the standard calibration curve was 50 g/mL. Ceftobiprole QC Samples Three sets of quality controls (QC) were prepared, each set contained a limit of quantification, low, mid, and high QC. The high QC should be between 75-90% of the highest standard. The mid QC should be 40-50% of the highest standard and the low QC should be no more that 2x the limit of quantitation (LOQ). Additionally, there should be one QC at the limit of quantification. From the stock solution of 1 mg/mL a solution of 100 g/mL was prepared. This was done using a microsyringe. From here dilutions were made to get the desired concentrations for the QCs (Table 5-11). Thes e dilutions were performed using a pneumatic pipette. The starting volume and total volume could vary as long as the ratio remained the same 82

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so that the same final concentrations are obtai ned. All quality control solutions should be prepared fresh daily. In this dilution scheme (Tab le 5-11) the concentrations of 40, 20, 0.2, and 0.1g/mL were used as the high, mid, low, and LOQ QCs respectiv ely, as the standard cu rve concentration range was 50-0.098 g/mL. HPLC Mobile Phase 950 mL of distilled water were mixed with 50 mL of acetonitrile. The mobile phase was degassed. The final volume of mobile phase prepared could vary as long as the ratio of distilled water to acetonitrile remain ed the same, 95:5. 0.1% Formic Acid in DMSO 0.1 mL of 90% formic acid was added to a 100 mL volumetric flask and filled with DMSO. HPLC Wash Solution 500 mL of double distilled wate r was mixed with 500 mL acetonitrile. The wash solution was degassed. The final volume of mobile phase prepared could va ry as long as the ratio of distilled water to acetonitrile remained the same. Sample Preparation All samples that have lactated Ringers solution as the matrix were directly injected onto the HPLC column. However, sample s obtained from microdialysis, both in vivo and in vitro, needed to be diluted with lactated Ringers solution to obtain a sufficient sample volume for HPLC analysis. This was done by dividing the sa mple into two equal aliquots of 12 L each and adding 24 L of lactated Ringers solution. By dividing the sample a b ack-up was available. The sample results found from the analysis needed to be multiplied by three to get the true concentration. 83

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Assay Procedure HPLC/UV Set Up The HPLC system used was the Agilent 1100 series which included a DAD detector (G1315B), an autosampler (G1329A), a column oven (G1316A), a degasser (G1379A), and a quaternary pump (G1311A). The work station us ed for data retention was an hp Compaq p4. See Figure 5-1 for a typical chromatogram for ceftobiprole. HPLC Pump Conditions Mobile phase: 95% Distille d Water, 5% Acetonitrile Flow rate: 1.0 mL/min Retention time: ~3.5 minutes Autosampler Conditions Injection Volume: 20 L Run time: 8 minutes 1 injection per vial (blanks may be injected more than once) 1 vial per sample Temperature: 4C Detector Conditions Wavelength: 300nm Analysis Procedure Each batch of test samples was run with a calibration curve. Additionally, each run contained 3 sets of quality control standards at 4 levels (LOQ, low, medium, and high) placed randomly throughout the run. With each run a blank injection of lactated Ringe rs solution was made at the start to ensure system equilibration. Blank lactated Ringers solution injections were made periodically throughout run. After every 20 injections the column underwent a brief wash. This involved a blank lactated Ringers solution injection with the wash so lution running for 15 mi nutes as the mobile phase. Next the column was allowed to equilibrate by making another blank lactated Ringers solution injection and running the or iginal mobile phase for 15 minutes. 84

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System Suitability Three injections of the 50 g/mL standard we re made. The CV% for these injections was less than 5%. The symmetry was 0.8 and 1.2. The retention time for ceftobiprole was 3.6min 0.4 min. Summary An HPLC-UV method for the an alysis of ceftobiprole in la ctated Ringers solution was developed for the analysis of microdialysis samples. The ca libration curve range, 0.1-50 mg/L, is appropriate based on the expected in vivo concentrations. The co mpound is stable under the conditions which will be encountered during an in vivo clinical study. 85

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Table 5-1. Intra-batch variability of quality control samples (n=3 per day and per concentration) QC Concentration (g/ml) 0.1 0.2 20 40 Day 1 (17May07) Mean 0.11 0.21 20.3 40.7 SD 0.00403 0.00548 0.0699 0.232 CV (%) 3.78 2.58 0.345 0.569 Accuracy (%) 106.6 106.3 101.4 101.8 Day 2 (18May07) Mean 0.10 0.22 21.5 43.0 SD 0.0107 0.0111 0.408 0.715 CV (%) 10.7 5.07 1.90 1.66 Accuracy (%) 100.2 109.1 107.3 107.4 Day 3 (21May07) Mean 0.10 0.19 20.5 41.4* SD 0.00892 0.00634 0.285 0.370* CV (%) 9.09 3.34 1.39 0.894 Accuracy (%) 98.14 95.03 102.4 104.5 Data was generated on 17May07, 18May07, and 21May07. *Based on n=2. 86

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Table 5-2. Inter-batch variab ility of quality control samples (n=9 per concentration) Days 1-3 0.1 0.2 20 40* (17,18, 21 May 2007) Mean 0.10 0.21 20.7 41.73 SD 0.00820 0.0146 0.599 1.15 CV (%) 8.06 7.07 2.89 2.75 Accuracy (%) 101.7 103.5 103.7 104.3 Data was generated on 17May07, 18May07, and 21May07. *Based on n=8 due to sample oading error. l 87

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Table 5-3. Freeze/thaw stability of QCs Concentration (g/ml) 0.1 0.2 20 40 Cycle 1 Mean 0.10 0.20 19.3 39.0 SD 0.00688 0.00631 0.305 0.412 CV (%) 6.60 3.19 1.58 1.06 Accuracy (%) 104.3 98.97 96.70 97.45 Cycle 2 Mean 0.10 0.18 18.66 38.23 SD 0.00327 0.00378 0.677 0.653 CV (%) 3.30 2.14 3.63 1.71 Accuracy (%) 99.63 98.53 93.31 95.58 Cycle 3 Mean 0.09 0.17 17.71 37.14 SD 0.00461 0.00887 0.195 0.724 CV (%) 5.39 5.16 1.10 1.95 Accuracy (%) 85.47 85.83 88.56 92.85 D ata was generated on 24May07 and 25May07. 88

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Table 5-4. Freeze/thaw stability of cef tobiprole stock standard solution Expected 0.1 0.2 0.39 0.78 1.56 3.13 6.25 12.5 25 50 Mean 0.11 0.20 0.38 0.75 1.50 3.01 6.08 12.26 24.76 49.73 SD 0.0402 0.0787 0.156 0.310 0.621 1.24 2.48 4.98 9.84 1.58 CV (%) 37.7 39.1 41.2 41.4 41.4 41.1 40.9 40.6 39.7 3.18 Accuracy (%) 109.1 100.5 97.1 96.1 96.1 96.2 97.2 98.1 99.1 99.5 Data was generated on 24May07, 28May07, 29May07, 04Jun07, and 11Jun07, and 13Jun07. 89

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Table 5-5. Room temperature stability of cef tobiprole stock standard solution after 5.5 hours (n=3) Concentration (g/mL) 0.1* 0.2 20 40 Mean 0.10 0.19 19.1 39.8 SD 0.0149 0.0111 0.993 2.03 CV (%) 15.3 5.96 5.20 5.11 Accuracy (%) 97.94 93.39 95.50 99.50 Data was generated on 04Jun07. *Based on n=2 due to poor chromatography of one QC sample. 90

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Table 5-6. Room temperature stabi lity of ceftobiprole QCs after 3 hour Concentration (g/mL) 0.1* 0.2 20 40 Mean 0.10 0.19 19.00 39.81 SD 0.00364 0.00795 0.126 0.387 CV (%) 3.62 4.27 0.665 0.971 Accuracy (%) 100.6 93.06 95.00 99.53 Data was generated on 14Jun07. *Based on n= 2 due to poor chromatography of corresponding QC sample which was injected with the standard curve 91

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Table 5-7. Refrigeration (4C) stability of QC samples over 24 and 48 hours (n=3) Concentration (g/ml) 0.1 0.2 20 40* 24 hours Mean 0.10 0.20 20.27 41.11 SD 0.0018 0.0127 0.379 0.213 CV (%) 1.78 6.51 1.87 0.562 Accuracy (%) 101.4 97.9 101.3 102.8 48 hours Mean 0.11 0.21 20.01 40.98 SD 0.0002 0.0168 0.371 0.653 CV (%) 0.185 7.98 1.85 1.14 Accuracy (%) 112.9 105.0 100.1 102.5 Data generated on 22May07 and 23May07 using the standard curve prepared on 21May07. *n=2 due to sample loading error 92

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Table 5-8. Freezer stability of QC samples over 32 days (n=3) Concentration (g/mL) 0.1 0.2 20 40 Mean 0.10 0.19 19.99 38.73 SD 0.015 0.0091 0.28 3.75 CV (%) 14.7 4.78 1.41 9.67 Accuracy (%) 100.4 95.50 99.96 96.84 Data generated on 29Oct07 using the standard curve from 27Sep07 for 32 day stability. 93

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Table 5-9. Interbatch variability of ceftobiprole using a different column to test robustness (n=3) Concentration (g/mL) 0.1 0.2 20 40 Mean 0.10 0.21 20.27 40.81 SD 0.00795 0.0154 0.429 0.486 CV (%) 7.61 7.33 2.12 1.19 Accuracy (%) 104.4 105.3 101.3 102.0 Data generated on 28May07. 94

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Table 5-10. Standard prep aration of ceftobiprole Starting Concentration (g/mL) Starting Volume (mL) Final Concentration (g/mL) Total Volume (mL) 100 1 50 2 50 1 25 2 25 1 12.5 2 12.5 1 6.25 2 6.25 1 3.13 2 3.13 1 1.56 2 1.56 1 0.78 2 0.78 1 0.39 2 0.39 1 0.20 2 0.20 1 0.098 2 95

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Table 5-11. Quality control sample preparation of ceftobiprole Starting Concentration (g/mL) Starting Volume (mL) Final Concentration (g/mL) Total Volume (mL) 100 1.6 80 2 80 1 40 2 40 1 20 2 20 0.8 8 2 8 0.8 3.2 2 3.2 1 1.6 2 1.6 1 0.8 2 0.8 1 0.4 2 0.4 1 0.2 2 0.2 1 0.1 2 0.1 1 0.05 2 96

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Figure 5-1. Typical chroma togram for ceftobiprole. Compounds showing vi sible absorption at 300 nm are shown. The X-axis is in minutes. 0 1 2 3 4 5 6 7 mAU 0 20 40 60 80 100 120 g ( ) 1.731 1.814 2.051 2.279 2.371 3.488 5.647 5.949 0 1 2 3 4 5 6 7 mAU 0 20 40 60 80 100 120 g ( ) 1.731 1.814 2.051 2.279 2.371 3.488 5.647 5.949 0 1 2 3 4 5 6 7 mAU 0 20 40 60 80 100 120 g ( ) 1.731 1.814 2.051 2.279 2.371 3.488 5.647 5.949 97

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CHAPTER 6 SOFT TISSUE PENETRATION OF CEFTOBIPROLE IN HEALTHY VOLUNTEERS DETERMINED BY IN VIVO MICRODIALYSIS2 Introduction Ceftobiprole, the active compound in ceft obiprole medocaril, is a promising new cephalosporin with activity against both Gram -negative and Gram-positive bacteria. This includes good activity against methicillin-resistant Staphylococcus aureus (MRSA) with reported MIC90 values of 2 mg/L (92) and 4 mg/L (82) and penici llin-resistant Streptococcus pneumoniae (PRSP) with an MIC90 of 2 mg/L (82). Currently, ceftobipr ole is under regulatory review and is only approved in Canada and Switzerland. Two dosing regimens are re commended, 500 mg as a 2 hour i.v. infusion every 8 hours in cases with gram-positive and/or gram-negative infections including diabetic foot infecti ons and 500 mg as a 1 hour i.v. infusion every 12 hours in cases of documented Gram-positive infections only excluding diabetic foot infections (90). This study focuses on the more general dosing regimen, i.e. the 2 hour 500 mg infusion every 8 hours, and references to the dosing interval refer to eight hours. This prolonged infusion time, 2 hours, was chosen in an attempt to prolong the time the concentration remains above the MIC. Traditionally, plasma samples have been taken to determine the pharmacokinetic (PK) properties of a compound and make efficacy predications based on pharmacokinetic/pharmacodynamic relationships. Ho wever, these concentrations are sometimes presented as total concentrations while only th e free drug is pharmacologically active (138, 194). Also, free concentrations at the site of action/infection are much more relevant to determine efficacy (121, 179) and exploring the concentrati on at the site of action has been recommended 2 This chapter is copyrighted as : Barbour A, et al. Soft tissu e penetration of ceftobiprole in healthy volunteers determined by in vivo microdial ysis. In press. Antimicrob Agents Chemother (2009). Copyright American Society for Microbiology. 98

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by regulatory agencies (34, 37, 66). One technique that has proven useful for the measurement of free drug concentrations in the in terstitial space fluid (ISF) of subc utaneous (s.c.) adipose tissue and skeletal muscle is mi crodialysis (52, 53, 85, 103, 126, 158). The aim of this study is to examine the pene tration of ceftobiprole from plasma into the ISF of s.c. adipose tissue and skeletal muscle using microdialysis and determine if efficacy breakpoints of relevant pathogens are met. Materials and Methods This study was performed in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. Pr ior to study initiation approval was received from the local ethics committee, the Institutional Review Board (IRB) at UF/Shands. All volunteers were consented verbally and in writing prior to participation in the study a nd written consent was obtained. Healthy Volunteers This study included 15 healthy volunteers (9 males and 6 fema les) between the ages of 20 and 34. Health was determined based on physical examination, medical history, vital signs, 12lead ECG, clinical laboratory te sts (serum chemistry, hematology, and urinalysis), BMI, negative hepatitis B surface antigen, negative hepatitis C antibodies, negative human immunodeficiency antibodies, and normal renal function based on serum creatinine and the Cockcroft-Gault equation. Subjects also had a negative urine drug test and alcohol breath test at screening and admission and were nonsmokers. Females in the study had a negative pregnancy test at screening and admission and were postmenopausal, sterile, abstinent, or practicing an effective measure of birth control. Add itionally, subjects did not use any other medication one week prior to the study drug administration until after the last blood dr aw with the exceptions of acetaminophen for pain, hormonal contraceptive medica tions, or hormonal replacement drugs. 99

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Microdialysis Microdialysis is a sampling technique which is based on simple diffusion of free analyte through the semipermeable membrane at the tip of a microdialysis probe. This technique has been explained in detail previously (172). Once in the ISF of the tissue of interest the flexible probe is continuously perfused with a physiological solution at a low flow rate by use of a syringe pump. The equilibrium between the probe and the tissue is incomplete and therefore the probes must be calibrated once in place, typically by retrodialysis (173). In this technique, a low concentration of the analyte is perfused thr ough the microdialysis probe and the disappearance into the tissue is measured from the dialysate. Th is recovery value is later used to calculate the true tissue ISF concentration. The recovery value is ca lculated as recovery%=100(Cdialysate/Cperfusate *100); where Cperfusate is the analyte concentrati on flowing into the probe and Cdialysate is the concentration of the analyte leaving the probe. Study Design Pilot Study Pilot study subjects were admitted to the Ge neral Clinical Resear ch Center (GCRC) at Shands Hospital the morning of the study and un derwent only the calibration procedures. After the site of probe insertion was cleaned and disinfected, two microdialysis probes (CMA 60, CMA Microdialysis AB, Solna, Sweden) were implanted without anesthesia into the same thigh by a study physician, one into the skeletal muscle and one into the s.c. adipose tissue. The probes were perfused with lactat ed Ringers solution for 30 minutes at a flow rate of 1.5 L/min. The pilot study subjects then received cef tobiprole via the microdialysis probes at a concentration of 200 mg/L and a flow rate of 1.5 L/min for 60 min. A sample was collected during the last 30 min to determine the indivi dual recovery% values. The probes were then 100

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flushed with blank lactated Ri ngers solution for three hours a nd samples were collected every 30 min. Main Study Subjects in the main study (6 male, 6 female) were admitted to the GCRC the evening before dosing. On the morning of dosing, two microdi alysis probes were implanted and each was calibrated via retrodialysis as described above After a four hour washout period, subjects received a single 666.7mg dose of ceftobiprole medocaril (Johnson & Johnson Pharmaceutical Research and Development, Raritan, NJ, USA), corresponding to 500 mg ceftobiprole, as a two hour i.v. infusion. The microdialysis probes were perfused with lactated Ringers solution at a flow rate of 1.5 l/min by a syringe pump from the start of the washout phase until after the 24 h sample was collected. Dialysate samples were collected in 20 min in tervals from pre-dose through 12 hours after the start of the infusion and at 16 and 24 hours. Blood samples for PK determinations were collected at pre-dose, 40 min, 1 h, 1 h 40 min, 2 h, 2 h 20 min, 3 h, 4 h, 6 h, 8 h, 12 h, 16 h, and 24 h. Blood samples for protein binding determination were collected at 2 h and 12 h. Blood sampling occurred from the oppos ite arm that the drug was administered and K2EDTA tubes were used for collection. Analysis Methods Sample Analysis-Microdialysis Samples The dialysate samples were stored at -80C until analysis at the University of Florida, Department of Pharmaceutics (Gainesville, FL ) and analyzed using a validated HPLC-UV method. The limit of quantification (LOQ) for this method was 0.1 g/mL. An Agilent 1100 series HPLC with an UV detector was used with a reverse phas e column (Supelco C18 Discovery). The mobile phase consisted of wate r and acetonitrile (95:5). The flow rate was 1 mL/min. The injection volume was 20 L and th e detection wavelength was 300 nm. The true 101

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tissue ISF concentrations were calculated from th e dialysate concentrations and adjusted with the recovery value. The calculation was as follows: CISFtissue=100*Cdialysate*recovery%-1. Sample Analysis-Plasma Samples Plasma samples were stored at -80C until shipment with dry ice to SFBC Analytical Laboratories, North Wales, PA. They were analyzed there using a va lidated LC/MS/MS method for ceftobiprole with K2EDTA and citric acid. The LOQ was 0.050 g/mL. A Perkin-Elmer 200 HPLC autosampler (4C) and pump were used. A gradient elution with two mobile phases (A1:5:95 formic acid/methanol/water and B-1:50: 50 formic acid/methanol/water) on a reverse phase column (Synergi 4 Polar-RP, 50 x 2 mm) was used. The tandem mass spectrometer (PE Sciex API 4000 Series) with a tur bo ionspray interface was set to monitor ceftobiprole at m/z 535-308 and m/z 539-312 for the internal standard (ceftobiprole-d4). Plasma samples were prepared by adding 50 L of sample to 50 L of internal standard, mixing, then adding 200 L of 0.1% formic acid in acetonitrile and 300 L of 10% perchloric acid. The samples were then vortexed for one minute and centrifuged at 3000r pm for 15 minutes. Protein binding was determined by ultrafiltration. Data Analysis Total plasma concentrations were adjusted based on individual pr otein binding prior to PK analysis to determine the free plasma con centrations. PK analysis was performed using commercially available software (WinNonlin 5.2, Pharsight Corporation, Mountain View, CA, USA) by noncompartmental analysis. The AUC0-last was calculated using the linear trapezoidal rule. The AUC0was calculated as AUC0-last + Clast/ z. The elimination rate constant, z, was calculated using linear regression of the concentration-time data. The points chosen for calculation of z were based on the best fit of the term inal phase and visual inspection. The 102

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AUCs were compared using Wilcoxons matched paired tests. A two-sided P<0.05 was considered significant. Results The aim of this study was to assess the tissue penetration of ceftobiprole into the ISF of skeletal muscle and subcutaneous adipose tissue. A pilot study was firs t conducted to test the feasibility of using microdialysis with ceftobiprole and to determ ine the washout period needed to ensure that no drug was remaining in the tissu es and the microdialysis system at the time of dosing. The mean recovery values ( SD) in the pilot study were 64.1%.6 and 47.5%.3 for s.c. adipose and muscle tissue respectively. In the pilot study, one probe malfunctioned after insertion and therefore the mean recovery value fo r the muscle is calculated from two samples. From the pilot study it was determined that the re covery was high enough to continue to the main study and a four-hour washout period should be allotted after calibra tion, prior to dosing. The mean protein binding between all subjects was 21.7%.6. The mean recovery values in muscle and s.c. adipose tissue for the main study were 58.3%.1 and 59.4%.4, respectively, and the measured concentrati ons were adjusted accordingly. The mean concentration-time profiles for plasma, free plas ma, free skeletal muscle ISF, and free s.c. adipose tissue ISF are presented in Figure 5-1. The pharmacokinetic parameters are summarized in Table 5-1. The mean f AUC0(SD) ratios of tissue ISF compared to plasma were 0.69.13 and 0.49.28 for skeletal muscle and s.c. adipose tissue, respectively. The results show that there is a significant difference between the f AUC in plasma and the AUCs of both soft tissues. Additionally, the AUC of skeletal muscle is significantly higher than the AUC of s.c. adipose tissue. 103

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Discussion This study shows that ceftobiprole distributes into the interstitial space fluid (ISF) of s.c. adipose tissue, f AUCs.c.adipose/ f AUCplasma 0.49.28, and skeletal muscle, f AUCmuscle/ f AUCplasma 0.69.13. The degree of tissue penetration with ceftobiprole correlates well other cephalosporins such as cepodoxime (103), cefixime (103), cefpirome (85, 158), and cefaclor (52) (Table 6-2). There was a si gnificant difference between the f AUC of plasma and the f AUC of both tissues and between the f AUC of muscle and the f AUC of s.c. adipose tissue. The differences in penetration ratios can be due to several factors includi ng the perfusion of the particular tissue, local capillary density (52), the degree of tissue binding, the possibility of active transporters (53), loss of drug from the peripheral compartments (94), and physiochemical properties of the compound (53), such as lipophilic ity. Therefore, it is important to measure the free, active drug in each tissue and not make the assumption that free plasma levels equal free tissue ISF levels, even in well perfused tissues. The pharmacokinetics determined in this study are in good agreement with previously summarized results (129). The half-life, clearance, Cmax, and AUC of 2.61 hr, 5.15 L/hr, 25.8 mg/L, and 98.0 mg/L*hr, respectively, were all within one standard deviation of the previously reported parameters with the same dosing regimen (129, 130). The Vss of 14.6 L is lower in this study than the reported value of 21.7 L for a single dose. However, it is in agreement with the multiple dose Vss of 15.5 L. The volume of distribution suggests that this compound distributes to the ISF which is common with this antibiotic cl ass. This property is advantageous because the ISF is often the location of infectious pathogens. The major advantage to the microdialysis tech nique is the ability to measure the free drug at the site of action, usually the I SF of soft tissues in regards to sk in and skin structure infections. It is this concentrati on that should be used to measure if efficacy breakpoints are met. For 104

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lactams the time the free concentration remains above the minimum inhibitory concentration ( f T>MIC) is thought to predict efficacy. It has been shown in neutropenic animals that efficacy is established if the concen tration remains above the MIC for at least 40-50% of the dosing interval (42, 43, 46), i.e. 3.2-4 h of an 8 h dosing interval. The MIC90 for ceftobiprole against MRSA (92) and PRSP (82) has been reported as 2 mg/L. The concentrations in the ISF of both skeletal muscle and s.c. adipose tissue remained above 2 mg /L for at least 50% of the dosing interval and, therefore, this dosing regimen should be effi cacious with these subcutaneous soft tissue pathogens. Also, sufficient concentrations ar e achieved to meet the efficacy breakpoint in organisms with an MIC90 of 4 mg/L in skeletal muscle, 53.6%.62 %f T>MIC. In s.c. adipose tissue, the time the concentra tion remains above the MIC is cl ose to 40% of an 8 h dosing interval, 35.1%.2 % f T>MIC, and it has been suggested that th e time free concentration needs to remain above the MIC is less than 40% for Staphylococcus aureus and Streptococcus pneumoniae (46). It is important to remember that further studies should be conducted in patients to see the relationship be tween the host response, free cef tobiprole concentration at the site of action, and clinic al outcome. Additionally, ceftobiprole has demonstrated similar clinical cure rates compared to vancomycin in Gram -positive complicated skin and skin structure infections and vancomycin plus ceftazidi me in both Gram-positive and Gram-negative complicated skin and skin structure infections in large-scale pivotal studies (139, 140). This study demonstrates that ceftobiprole distributes into the ISF of soft tissues in healthy volunteers. This finding and ceftobiproles wi de-range of activity make it a promising new single agent for the treatment of complicated skin and skin structure infections. 105

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Figure 6-1. Mean ceftobiprole conc entration in plasma (circles), skeletal muscle ISF (squares), and s.c. adipose tissue ISF (triangles) over twelve hours. Free plasma concentration (dashed line) was calculated based on the plasma protein binding of each individual patient. 106

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Table 6-1. Noncompartmental pharmacokinetic analysis PK parameter Plasma (total) Plasma (free) S.C. Adipose Muscle Cmax (mg/L) 25.82.96 20.22.63 9.614.74 14.03.22 Tmax (mg/L) 1.920.15 ND 2.250.21 2.250.14 t1/2 (hr) 2.610.33 ND 2.560.39 2.610.52 AUC0-last (hr*mg/L) 97.10.3 76.0.81 34.39.0 50.60.9 AUC0(hr*mg/L) 98.00.5 76.9.94 36.59.4 53.21.5 CL (L/hr) 5.150.53 ND ND ND Vz (L) 19.43.61 ND ND ND Vss (L) 14.62.17 ND ND ND AUCISF/ f AUCplasma 0.490.28 0.690.13 ND: Not Determined 107

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Table 6-2. Soft tissue penetration of four cephalosporins determined by microdialysis Cefpodoximea Cefiximea Cefpirome b Cefpiromec Cefpirome d Cefaclore Cefaclor f Cefaclorg AUCplasma 22.4 25.6 17.6 13.7 22.1 f AUCplasma 17.7 9.0 275.0 230.7 175.0 13.2 10.3 16.6 f AUCmuscle 15.4 7.3 130.0 80.0 9.49 7.02 11.53 f AUCs .c.adipose 218.5 117.0 87.2 f AUCmuscle/ f AUCplasma 0.89 0.84 0.56 0.46 0.73 0.67 0.70 f AUCs.c.adipose/ f AUCplasma 0.79 0.51 0.50 All AUCs are in mg/L*hr. Data presented as mean values from each study. a. Dosed orally 400 mg. AUC0presented. f AUC calculated based on protein binding (103). b. Dosed i.v. over 15 minutes 2 g. AUC0-4 presented. Data from healthy volunteers only (158). c. Dosed i.v. over 10 minutes 2g. AUC0-8 presented (85). d. Dosed i.v. over 12 hours 2g (only 10 hours observed). AUC0-8 presented (85). e. Dosed orally 500mg IR. AUC0presented. f AUC calculated based on protein binding (52). f. Dosed orally 500mg MR. AUC0presented. f AUC calculated based on protein binding (52). g. Dosed orally 750mg MR. AUC0presented. f AUC calculated based on protein binding (52). 108

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CHAPTER 7 PHARMACODYNAMC PROPERTIES OF CEFTOBIPROLE AGAINST MRSA Introduction Antimicrobial pharmacodynamics are typica lly defined by the minimum inhibitory concentration (MIC). The MIC is the lowest concentration that completely inhibits visible growth of the organism after 18 h of inc ubation at 35C with a starting inoculum of approximately 5x105 colony forming units (CFU)/mL. In turn, the clinical target for antimicrobial agents are normally evaluated on th e basis of one of the following PK/PD indices; the time free drug concentration in plasma is above the MIC ( f T>MIC) expressed as a percentage of the dosing interval, the ratio of maximum concentration to MIC (Cmax/MIC), and the ratio of the area under the twenty -four hour concentration-time curve to MIC (AUC0-24/MIC). There are some major limitations to these MIC based PK/PD indices. For example, the MIC does not show the time course of the antibiotics e ffect and it has a two-fold variability. Another approach that has been successfully used to study the PD of antibiotics is time-kill analysis. Time-kill curves display the change in the number of bacteria over time by using a range of static or dynamic concentrations. Once this experiment is perfor med a mathematical model can be developed to determine the PD parameters. Beta-lactams typically fit an Emax model (5). The PD parameters derived from time-kill experiments with this model can then be combined with in vivo PK data in an integrated PK/PD model that describes th e antibiotics activity as a function of time and concentration. Ceftobiprole is currently under FDA review with the primar y indication of complicated skin and skin structure infections. This co mpound is delivered as a water-soluble prodrug, ceftobiprole medocaril. Ceftobiprole displays a wide-range of activity against both Gram109

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positive and Gram-negative pathogens including se veral resistant species such as MRSA and penicillin-resistance Streptococcus pneumoniae (PRSP) (73, 82, 92, 155). It is the goal of this series of experiments to perform time-kill experiments to characterize the activity of ceftobiprole against methicillin-resistant Staphylococcus aureus (ATCC33591). A modified Emax model will be developed and validated to determine the pharmacodynamic parameters. Materials and Methods Study Conduct The MICs for this study were determined in compliance to the Clinical and Laboratory Standards Institute (CLSI) approved standard methods using the macrodilution study design. Time-kill curves also followed CLIS methods but the complete design of these experiments is not yet standardized. The methods used in th is experiment followed those of a previous publication and are described below (183). Preparation of Ceftobiprole A ceftobiprole stock solution, 1.28 mg/mL was prepared by weighing 12.8 mg of ceftobiprole (Johnson and Johnson Pharmaceutical Re search and Development) and dissolving it in 10 mL of 0.1% formic acid in DMSO. The stabili ty of ceftobiprole in this stock 1 solution has been shown to be at least 23 days at -70C with at least 7 freeze/thaw cycles. From this stock 1 solution, further dilutions for the MIC determin ation and time-kill curv es were made using Mueller-Hinton Broth (MHB). Preparation of Sterile Br oth and Normal Saline Mueller-Hinton broth (Becton Dickinson BBL) was prepared according to the manufacturers instructions and autoclaved prio r to use for 10 minutes at 121 C. Normal saline 110

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was prepared by weighing out 9g of sodium chlo ride and dissolving it in 1L double distilled water. It was then autoclaved for 20 minutes at 121 C. Inoculum Preparation The inoculum was prepared from colonies incubated overnight on sheeps blood agar plates (Remel). The microorganisms were suspe nded in sterile normal saline to a concentration equivalent to a 0.5 value in the McFarland Equivalence Turbidity Standard (Remel Microbiology Products) as measured with a turbidimeter which equals 1x108 CFU/mL. For the MIC 0.01 mL of the initial inoculum were added to each we ll containing 2mL of solution for a final initial inoculum of 5x105 CFU/mL. For time-kill curves, 200 L of the suspension were inoculated into the in vitro model to achieve a final initial inoculum of approximately 1X106 CFU/mL. The culture flasks in the time-kill experiments were incubated for 2 hours to allow the bacteria to reach the logarithmic growth phase pr ior to the addition of ceftobiprole. MIC Determination The MIC was determined using two-fold diluti ons in 24-well plates with an inoculum of approximately 5X105 CFU/mL and antibiotic concentrations started at 0.06 mg/L and ranging to 32 mg/L. The plates were read after 20 hours of incubation at 37C, and the MIC was defined as the lowest concentration of the antibiotic allowing no visible growth. Dete rminations of the MIC were performed six times (3 plates with 2 readings per plate). Additionally, each MIC determination contained a positiv e control (only bacteria, no antib iotic) and a nega tive control (no bacteria or antibiotic ) to validate the results. In Vitro Infection Model with Constant Antibiotic Concentration This model was used to investigate the effect of constant concentr ations of ceftobiprole against MRSA as a function of time. The in vitro infection model consisted of a 50-mL canted neck, vented cap, tissue culture fl ask containing 20 mL of the MH B. The bacteria were exposed 111

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to a series of concentrations of ceftobipr ole based on the MIC (0.25-16XMIC) for 24 hours. Samples were taken at predefined time points as defined below. Bacterial Quantification Samples (20 l) were collected from the in vitro model at the following time points: zero, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, 16, 20, and 24 hours. Bacter ial counts were determined by plating serial dilutions of the samples on appropriate agar plates. The dilu tions (10X) are made in sterile normal saline. Aliquots (50 l in five 10 L drops) of each dilu tion were plated in duplicate and an average was taken. Sheeps blood agar plates were used (Remel Blood Agar (TSA w/Sheep Blood) plates). The plates were incubated at 37 C overnight before reading. The procedure was repeated at least 3 times per c oncentration. Positive controls (with bacteria, no drug) are run simultaneously in order to assess the method. Fo llowing incubation, colonies are counted on all readable plates that showed up to approximately 250 colonies/50 L sample, 50 colonies/10 L droplet. The LOQ of this method was deemed as 3000 CFU/mL, or 15 CFU/50 L sample. This LOQ was chosen so that at least one 10X dilu tion was made to avoid residual antimicrobial activity after sampling. The data was entered in to Microsoft Excel spreadsheets. Data points below the LOQ were excluded. Stability of Ceftobiprole in Mueller Hinton Broth (MHB) The stability of ceftobiprole in MHB was determined by sampling at time 0, 8, 16, and 24 hours after the addition of antibio tic to the time-kill curve experi ment. One hundred microliters was obtained from each concentration and fro zen until analysis. Prior to analysis, 200 L of acetonitrile was added to precipitate any protei ns. The samples were then centrifuged at 3000g for 15 minutes. The supernatant was analyzed using the analytical conditions described in Chapter 5 with a standard curve ranging from 2mg/L to 64mg/L and quality controls of 6mg/L, 112

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24mg/L, and 48mg/L in triplicate. Standards a nd quality controls were prepared in MHB from the stock 1 solution and underwent the protein pr ecipitation procedures. The degradation was assumed to be first order. Data Analysis The measured kill curves were analyzed using an appropriate model with nonlinear regression in NONMEM VI using the ADVAN6 subr outine. Pharmacodynamic parameters were determined (growth rate, maximum kill rate, EC50, and others depending on the model). Results MIC Determination The MIC was determined to be 2mg/L in all six replicates. No growth of bacteria was observed in the negative control and growth was observed in the positive control, validating the experiments. These results are in ag reement with the commonly reported MRSA90 of ceftobiprole, 1-4 mg/L (73, 82, 92, 155). Time-Kill Curves The results from the time-kill curve e xperiments are presented in Figure 7-1. Ceftobiprole induced rapid bacteria l killing with concentrations e qual to or above the MIC. Ceftobiprole concentrations above the MIC allowed for mi crobial growth, although at a concentration of 1 mg/L the growth was slightly inhibite d for a period of time. Stability of Ceftobiprole in MHB Ceftobiprole was found to be degrading th roughout the time-kill experiment. Samples from the flasks containing concentrations rang ing from 2-32 mg/L were analyzed. The lower concentrations (0.5 and 1 mg/L) were below the LOQ of the analytic method after dilution with acetonitrile for protein precipitation and, therefore, were not analy zed. The results are presented 113

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in Figure 7-2. A first-order degradation was assu med and an average degr adation rate from all concentrations was used in the modeling step, i.e. 0.0149 hr-1. Pharmacodynamic Model Development Figure 7-1 displays that during the time-kill experiment a maximum is reached in growth and the kill-kinetics display a biphasic profile. During growth a maximum is reached at a certain point due to environmental factors, i.e. lim ited space and nutrients, and the bacteria can no longer increase in concentration. One common theory used to explain the biphasic profile of antimicrobial activity is the two-subpopulation m odel (39, 96, 136). In this model, there are two bacterial populations present, a drug susceptible population and re sistant/persistent population. This idea was used to model the time-kill curv es of ceftobiprole with MRSA. The kill of susceptible bacteria due to the antibiotic is typically described by an Emax model. In this model the effect is represente d by the following equation: where Kmax is the maximum effect, C is the conc entration of ceftobiprole, and the EC50 is the concentration needed to produce half the maximu m effect. An additional term maybe added, and was in this instance, to account for the steepness of the slope termed the hill factor (H): Often the antimicrobial effect is not displayed immediately once drug is added to the in vitro system. This delay in kill (DEK) can be char acterized by adding an additional parameter (dk) and multiplying the drug effect by the following factor (183): 114

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Additionally, due to the fact th at the antibiotic was degradi ng throughout the experiment the following first-order equation was used to accoun t for the changing ceftobiprole concentrations throughout the experiment: C=Starting Concentration e(-degradation rate*time) The differential equations for the change in the nu mber of susceptible (s) and resistant/persistent (r) populationith respect to re as follows: s w time a Where 1-(S+R/Nmax) is used to describe the satu ration in bacterial concentration due to growth and Ksr and Krs are the transfer rate constant s of the bacteria betw een the susceptible and resistant stages. The above two-subpopulation model was able to de scribe the data well and the parameters are presented in Table 7-1. Interexperimen tal variability was accounted for by using an exponential error model on the Kmax and EC50 parameters. Additionally, an additive residual error model was used on the log-transforme d data, i.e. a proportional model on the nontransformed data. Data from two kill curv es, out of the 48, were deemed outliers and excluded from the final data set. This was due to analyst error of omitting to change the pipette tips at the forth dilution step on one experimental day resulting in bacterial carry-over. The bacterial concentrations for this particular day we re higher than the othe r five replicates. The excluded kill-curves were the growth c ontrol and the 0.25XMIC concentration. The concentrations equal to or grea ter than the MIC were not effect ed as the number of dilutions 115

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steps was always less than or equal to four. Th e fit of the model was assessed by examination of the diagnostic plots and individual fits (Figures 7-3,7-4,7-5,7-6). Pharmacodynamic Model Validation This model was validated using case deletion diagnostic in which the experimental data from one day of experiments was removed fr om the data set and the parameters were recalculated. The parameters from the validati on were compared to those calculated form the full data set (Table 7-1). While the parameters are fairly consistent between the modified data sets and the original data set, minimization wa s only successful in one instance out of the six attempts and parameters were not able to be obtained from one NONMEM run. This resulted in only five sets of parameters available for co mparison with the parameters obtained from the original data set. However, the parameters that were obtained were comparable to the full data set and the model was considered validated. Conclusions Ceftobiprole displays antimicrobial activity against MRSA. Time-kill curves are an appropriate technique to assess the pharmacodynamic profile of cef tobiprole as the antimicrobial effect over time is assessed. Additionall y, a two-subpopulation model, which included a susceptible population and a resistant/persistent population, was used to fit the time-kill curve data. This model and the calculated pharmacodynamic parameters may now be used to assess a specific dosing regimen when combin ed with pharmacokinetic data. 116

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Table 7-1. Pharmacodynamic parameters based on time-kill curves and CDD Results Parameter Full Data Set Curve 1 Deleted Curve 2 Deleted Curve 3 Deleted Curve 4 Deleted Curve 5 Deleted KS (hr-1) 0.913 0.871 0.92 0.823 0.876 0.774 Nmax (CFU/mL) 1.13*1010 1.03*1010 1.22*1010 1.33*1010 9.70*109 5.43*109 Kmax (hr-1) 1.71 1.68 1.67 1.76 1.05 1.26 EC50 (mg/L) 1.17 1.22 1.17 2 1.52 1.94 H 5.13 9.34 4.88 12 7.34 6.2 DK 0.515 0.496 0.551 0.361 0.522 0.856 Ksr (hr-1) 0.122 0.0996 0.13 0.15 0.0895 0.0028 Krs (hr-1) 0.0359 0.0349 0.0337 0.0203 0.0403 0.0417 117

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Bacteria (CFU/mL) Time (hour) Figure 7-1. Time-kill curves of Ceftobipr ole against MRSA performed over 24 hours. 118

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Figure 7-2. Degradation of Ceftobiprole in MHB with MRSA at 37C. 0 20 40 60 80 100 120 0 8 1624%Starting ConcentrationTime (hr) 2mg/L 4mg/L 8mg/L 16mg/L 32mg/L 119

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Figure 7-3. Diagnostic plot of obser ved CFU/mL vs. population predicted. 120

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Figure 7-4. Diagnostic plot of the natural log observed CFU/mL vs. individual predicted. 121

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Figure 7-5. Diagnostic plot of weighted residuals vs individual predicted. 122

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Figure 7-6. Individual fits of the model population predicted and i ndividual predicted curves for time-kill experiments. Dependent variable s (circles), population predicted (dashed line), individual predicted (solid line). 123

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CHAPTER 8 POPULATION PHARMACOKINETICS AND MONTE CARLO SIMULATIONS FOR THE EVALUTION OF THE CURRENTLY RECOMMENDED DOSING REGIMEN OF CEFTOBIPROLE Introduction The FDA has recognized that model-based drug development provides an opportunity to streamline the drug development process (68). There have been numerous cases in which model-based development has saved money and tim e by aiding in dose selection, clinical trial design, or support of a given dosing regimen (118). In antimicrobial drug development, and drug development in general, pharmacokinetic models ar e based on plasma concentrations. However, it would be better to base these models on drug concentrations at the site of acti on. Additionally, to truly characterize the antimicrobial eff ect over time, time-kill experiments should be performed. Therefore, the most rationale appr oach for dose evaluation would be to use free, active concentrations at the site of action for PK model development and data from time-kill curve experiments for PD model development. An integrated PK/PD model could then be used to calculate the predicted target attain ment rate of a given dosing regimen. It is the goal of this chap ter to use modeling and simulati on techniques to evaluate the one of the currently recommended dosing regimens of ceftobiprole, 500m g administered as a two-hour i.v. infusion every eight hours. This will be done by developing a pharmacokinetic model to simultaneously simulate free concentrati on-time curves in three different tissues, i.e. plasma, skeletal muscle ISF, and s.c. adipose tissue ISF, based on plasma and microdialysis data. This information will then be used to predict the target attainment rate using two different endpoints, the traditional f T>MIC and the endpoint of 1-log kill at 24 hours. 124

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Materials and Methods Population Pharmacokinetic Model Development The details of the microdialys is study are presented in chap ter 6. Plasma data from the microdialysis experiment was adjusted for i ndividual protein binding and compiled with the microdialysis data, which also represents free concen trations, to make the full data set for use. A model was developed using NONMEM VI with the ADVAN6 subroutine. This subroutine allowed the differential equations to be user supp lied. Interindividual variability was included in the model using an exponential er ror model if deemed appropriate, i.e. if incorporation of an additional parameter revealed a significant drop in the objective function. A drop of 3.84 was used representing a 0.05 level of significance. A proportional plus additive model was used to describe the residual error. Mode l fit was assessed by visual inspect ion of the diagnostic plots. The model was validated by performing a bootstrap analysis using 1000 r uns with the aid of wings for NONMEM. The possibility of covariates was explored by using the GAM analysis in Xpose4 and visual inspection of the correlation matrix between ETA s (interindividual variability) and possi ble covariates. Probability of Target Attainment Time above MIC approach: Once the populat ion PK model was finalized and validated, NONMEM was used to simultaneously simulate the pharmacokinetic profiles for free plasma, free skeletal muscle ISF, and free s.c. adipose tissue ISF fo r 1000 subjects, 500 females and 500 males. Then the f T>MIC was calculated at steady state by simulating three consecutive doses, 500mg every 8 hours delivered as two-hour i.v. infusions, and using the last dosing interval for the calculation of the f T>MIC. To calculate a clinically releva nt target attainment probability, a MRSA MIC distribution obtained fr om patients with bactereamia was used (86). The target attainment rate for the f T>MIC of 30% and 40% of the dosing in terval were both calculated. 125

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Time-kill curves: Using the PD model developed in chapter 7, the 1000 simulated concentration-time profiles of all three tissues were inserted into Emax model. Then, 1000 simulations were performed to yield the antimicr obial effect over 24 hours. The probability of target attainment was assessed based on a 1-log kill at 24 hours from the starting inoculum. The starting inoculumused in the simulation was an average of the starting inoculums from the six separate time-kill experiments, i. e. 48 starting inoculums total. In order to assess the target attainment rate using a populatio n of bacteria, not just the single experimental strain from the time-kill curve experiments, the MIC distribution was converted to an EC50 distribution. Again, the ta rget attainment rate was assessed based on a 1-log kill at 24 hours. The MIC was converted to the EC ing the following equation (122): 50 us In this equation, time is set at 20 hours, Nt is the concentration at which growth is visible (107 CFU/mL), N0 is the starting inoculum (5*105 CFU/mL), and the remaining parameters are fixed from the time-kill curve experiments. This method makes the major assumption that although the EC50 changes, the remaining PD parameters do not change. This may not necessarily be true. After calculating the new EC50 values, the simulations were performed again to find the probability of target attain ment based on a 1-log kill at twenty-four hours. Results Population Pharmacokinetic Model Development A simple two-compartment body model with elimination from the central compartment was able to accurately fit the data (Figure 8-1). This model was developed using free concentrations in all tissues. The deferen tial equations for this model are as follows: 126

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In the above equations, K0 represents the infu sion rate and was included in the model during dosing only. To obtain concentrations, instead of amounts, a scaling factor was used. For the central compartment the scaling factor is the vol ume of distribution of the central compartment (Vc). However, for the microdialysis data, the sc aling factor would be th e volume of distribution of the peripheral compartment (Vp). Due to the fact that at steady state K12*Vc=K21*Vp, Vp was replaced by K12*Vc/K21. Al so, since free concentrations in plasma do not equal free concentrations in tissue ISF an additional parame ter was added to the model to account for this, termed the distribution factor for muscle or adipose (DFM or DFA). Therefore, the equations for the free concentration in plasma, skeletal musc le, and s.c. adipose tissue respectively are: Interindividual variability was accounted for by using an exponential error model on the following parameters; K12, Vc, and DFA. Once the base model was established, a bootstrap analysis was performed for model validation. However, from the bootstrap, it was seen that K12 displays a high degree of fluctuation, with a 90% confidence interval of 12.3-110, and the single run parameter estimate was approximately half the mean from the 1000 runs. Therefore, this parameter was fixed to the single run estimate, 21.6 hr-1. Justification for fixing this parameter was based on calculating the terminal phase of the average concentration time-curve (Beta) using 127

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the microconstants and comparing that value to the value obtained for the elimination rate constant ( z) from the noncompartmental analysis. These values should be approximately equal. Additionally, the volume of distri bution (Vss) of beta-lactams is approximately equal to total body water. Therefore, using the equation Vss= Vc*(1+K12/K21) and substituting the calculated parameters, a volume of distribution approximate ly equal to total body water was obtained as expected. After K12 was fixed the bootstrap analysis was performed again (Table 8-1). After a stable final base model was establ ished, age, weight, he ight, and sex were examined as possible covariates. Typically, wei ght is observed as a covariate on the volume of distribution. However, due the small number of subjects, 12, a nd the fact that only healthy volunteers were selected for the microdialysis study, the only significant covariate revealed from the GAM analysis and visual inspection of the pl ots of interindividual variability (etas) vs. possible covariates was sex on the distribution factor for s.c. adi pose tissue (Figure 8-2). This factor was added to the mode l by the following equation, where in the data set males are represented by 0 and females by 1: DFA=THETA( 6)+(1-SEX)*THETA(7). The addition of the parameter led to a decrease of the objective function of 16, 210 194. The fit of this final covariate model was exam ined by visual inspection of the diagnostic plots (Figures 8-3, 8-4, 8-5, 8-6, 87, 8-8). Again a bootstrap analys is was performed to validate the final covariate model and the parameters from the single run were used for simulations (Table 8-2). Probability of Target Attainment Time above MIC: The time above MIC was calculated at st eady state from 1000 simulated subjects. The probability of target a ttainment in each tissue at steady state for each MIC and overall probability of target attainment for each tissue is presented in Tables 8-3 and 84 for a target of f T>MIC of 30% and 40% of the dosing interv al, respectively. The two slightly 128

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different targets were examined since 40% is th e typical target for beta -lactams (42); however, in vivo animal studies have shown that with ceftobiprole agains t MRSA a lower target maybe acceptable (46). Time-kill curves: The probability of target attainment was calculated by combining the pharmacokinetic data from the simulation of 1000 subjects with the pharmacodynamic model and again performing 1000 simulations. The probab ility of target attain ment was based on the endpoint of 1-log kill at 24 hours. The probability of target at tainment in each tissue was as follows: 99.90% in plasma, 99.90% in muscle, and 88.50% in adipose tissue. An example of a clinical success and failure is presented in Figure 8-9. In order to obtain a bacterial susceptibili ty distribution encountered clinically, the MIC values were converted to EC50 values. At each EC50 value 1000 simulations were performed using the same PK input (Table 85). From Table 8-5 it can be s een that this dosing regimen is efficacious against highly susceptible organisms. A different dosing regimen may be needed against pathogens with a low suscepti bility to ceftobiprole, especially to obtain the target in s.c. adipose tissue. The results obtained using this technique should be in terpreted cautiously, however, since using the MIC to calculate an EC50 results in step-wise increases in the EC50, which is not a true representation of the populati on susceptibility. Additionally, the simulations assume that while the EC50 is different the other pharmacodynamic parameters remain the same. Conclusions The free concentration of ceftobiprole was de termined in three tissues, plasma, skeletal muscle ISF, and s.c. adipose tissue ISF. The c oncentration in these tissues is important due to the fact that they represent the relevant site of action. A model was then developed to predict the concentration of all tissues si multaneously. To evaluate effi cacy two different pharmacodynamic endpoints were used, f T>MIC and 1-log kill. Based on the data obtained from the pharmacokinetic 129

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and pharmacodynamic studies performed both endpoints supported the generally recommended dosing regimen of 500mg every eight hours admini sters as a two-hour i.v. infusion. More timekill curve studies are needed to obtain a suscep tibility distribution for ceftobiprole against MRSA. However, converting an MIC distribution to an EC50 distribution and calculating the target attainment rate of achie ving a 1-log kill at 24 hours suggests that different dosing regimen may be needed with organisms that have a lower susceptibility. These results should be interpreted cautiously as some ma jor assumptions are made. 130

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Figure 8-1. Two-compartment body model with e limination from the central compartment and drug delivery via i.v. infusion. 131

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ETA1 -0.10.2 0.00.6 607080 -0.30.1 -0.10.2 ETA2 ETA3 -1.00.0 0.00.6 SEX HT 160175 607080 WT -0.30.1 -1.00.0 160175 2026 2026AGE Figure 8-2. Plots of interindividual variability vs. possible covariates. 132

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Figure 8-3. Dependent variables vs. population predicted values (mg/L). 133

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Figure 8-4. Dependent variables vs. individual predicted values (mg/L). 134

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Figure 8-5. Weighted residuals vs. population predicted values. 135

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Figure 8-6. Individual fits of the covariate model population pred icted and individual predicted curves for free plasma. Dependent variable s (circles), populati on predicted (dashed line), individual predic ted (solid line). 136

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Figure 8-7. Individual fits of the model population predicted and i ndividual predicted curves for skeletal muscle. Dependent variables (cir cles), population predicted (dashed line), individual predicted (solid line). 137

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Figure 8-8. Individual fits of the model population predicted and i ndividual predicted curves for s.c. adipose tissue. Dependent variables (c ircles), population pred icted (dashed line), individual predicte d (solid line). 138

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Figure 8-9. Example of a success and a failure ba sed on achieving 1-log kill at 24 hours. Data obtained from the simulation of antibioti c effect over 24 hours in adipose tissue using the experimentally obtained EC50 value. 1.0E+03 1.0E+04 1.0E+05 1.0E+06 1.0E+07 1.0E+08 0.005.0010.0015.0020.0025.0030.00Bacteria (CFU/mL)Time (hour) Failure Success 139

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Table 8-1. Results from bootstra p of base model (1000 runs) PK Parameter Single Run Bootstrap 90%CI K12 (hr-1) 21.6 21.6 N/A K21 (hr-1) 2.98 3.04 2.44-3.83 K10 (hr-1) 3.17 3.17 2.57-3.88 Vc (L) 1.91 1.93 1.65-2.25 DFM 0.667 0.671 0.61-0.761 DFA 0.46 0.465 0.355-0.579 Interindividual Variability K12 0.0271 0.0249 0.028-0.0519 Vc 0.0171 0.0138 0.00296-0.0317 DFA 0.36 0.333 0.15-0.551 Residual Variability Sigma 1 0.0324 0.0312 0.024-0.039 Sigma 2 0.0579 0.0548 0.0264-0.0902 140

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Table 8-2. Results from bootstrap of covariate model (1000 runs) PK Parameter Single Run Bootstrap 90%CI K12 (hr-1) 21.6 21.6 N/A K21 (hr-1) 3.04 3.10 2.46-3.96 K10 (hr-1) 3.14 3.14 2.53-3.87 Vc (L) 1.93 1.95 1.64-2.31 DFM 0.668 0.672 0.601-0.762 DFA 0.362 0.350 0.197-0.538 Sex on DFA 0.193 0.231 0.0124-0.436 Interindividual Variability K12 0.027 0.0248 0.00453-0.0523 Vc 0.0172 0.0139 0.00305-0.0318 DFA 0.207 0.150 0.0208-0.387 Residual Variability Sigma 1 0.0315 0.0305 0.024-0.0378 Sigma 2 0.0605 0.0548 0.0259-0.0919 141

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Table 8-3. Probability target attainment for f T>MIC of >30% at steady state MIC (mg/L) 0.25 0.5 1 2 4 Fraction MIC Distribution 0.24 2.20 26.10 70.73 0.73 Plasma 100 100 100 100 100 Muscle 100 100 100 100 100 S.C. Adipose 100 100 100 98.50 80.70 Overall Attainment Plasma 100 100 98.80 Muscle S.C. Adipose All values expect the MI C are in percentages. 142

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Table 8-4. Probability target attainment f T>MIC of >40% at steady state MIC(mg/L) 0.25 0.5 1 2 4 Fraction MIC Distribution 0.24 2.20 26.10 70.73 0.73 Plasma 100 100 100 100 100 Skeletal Muscle 100 100 100 100 100 S.C. Adipose 100 100 99.90 97.00 73.10 Overall Attainment Plasma 100 100 97.66 Muscle S.C. Adipose All values except the MIC are in percentages. 143

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Table 8-5. Probability of target attainme nt based on 1-log kill at 24 hours (3 doses) MIC (mg/L) 0.25 0.5 1 2 4 EC50 (mg/L) 0.26 0.52 1.04 2.09 4.17 Fraction MIC Distribution 0.24 2.20 26.10 70.73 0.73 Plasma 99.90 99.90 99.90 99.70 72.30 Muscle 99.90 99.90 99.90 95.80 24.20 S.C. Adipose 99.90 99.60 91.90 57.80 13.70 Overall Attainment Plasma 99.56 96.45 67.40 Muscle S.C. Adipose All values except the MIC and EC50 are in percentages. 144

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CHAPTER 9 CONCLUSIONS Ceftobiprole is promising new cephalosporin with activity against a wide-range of both Gram-positive and Gram-negative pathogens, including several resistance species such as MRSA and PRSP. The generally recommended dosing regimen of ceftobiprole is 500mg administered as a two hour i.v. infusion every eight hours. However, in cases of documented Gram-positive infections, excluding diabetic f oot infections, 500mg administer ed as a one hour i.v. infusion every twelve hours is recommended. It was the goal of this project to evaluate the efficacy of the more empiric, general dosing regimen of 500mg administered as a two-hour i.v. infusion every eight hours. Traditionally, plasma samples have been used as the PK input in PK/PD indices for the evaluation of efficacy with antimicrobial agen ts. However, with antimicrobials such as ceftobiprole, with the lead indication of cSSSI, it is more rationa le to use free, pharmacologically active concentrations at the site of action for efficacy evaluation, i.e. the ISF of subcutaneous (s.c.) soft tissues. Therefore, a microdialys is study was conducted in healthy volunteers to determine the free concentration-time profile in pl asma, the ISF of s.c. adipose tissue, and the ISF of skeletal muscle. The data from this study was used to develop a pharmacokinetic model so that the concentration in all three tissues could be predicted simultaneously. It was determined that a two-compartment body-model w ith elimination from the central compartment fit the data accurately. Additionally, due to the f act that free concentrations in the ISF were not equal to free plasma concentrations, a distribution factor for each soft tissue was included in this model. The major PD parameter used for antimicrobials is the MIC. This parameter, however, has many limitations. Mainly, the MIC does not show the antimicrobial activity over time. 145

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Additionally, the MIC does not show the extent of kill, it has a two-fold variability, and it does not show the presence of resistant/persistent bacteria, which may be pres ent at a concentration below visual detection. Therefore, it seems more rationale to perform time-kill curve experiments to characterize the antimicrobial ac tivity. It these experiments an antimicrobial profile is obtained over time and a ma thematical model, typically an Emax model, is developed so that the pharmacodynamic parameters can be calcul ated. Time-kill curves were performed with MRSA ATCC 33591 and ceftobiprole. A two-s ubpopulation PD model, which included a drug susceptible population and a dr ug resistant/persisten t population, was developed and the PD parameters were calculated. In this model a dditional terms were included to account for a saturation in growth and a time delay in antimicrobial effect. Once the PK and PD models were developed a nd validated, simulations were performed to predict the efficacy of the specified dosing regimen using two-different pharmacodynamic endpoints. The first method involve d using the traditional PD para meter, the MIC, and a target of f T>MIC of 30% or 40% of the dosing interval. Simulations were pe rformed to create a data set with the PK profiles of 1000 subj ects from all three tissues s imultaneously over 24 hours, i.e. three subsequent doses. A MIC di stribution obtained from literature determined that this dosing regimen meets the PK/PD target in all three tissues at steady state. In plasma and skeletal muscle it was predicted that with 1000 subj ects the target woul d be reached 100% of the time. In s.c. adipose tissue it was determined that the target would be reached approximately 98% of the time using the target of f T>MIC of 40%. The second method involved using the PD parameters obtained from the time-kill experiment and modeling to evaluate the efficacy of the specified dosing regimen. The same simulation that created the PK profiles for 1000 subj ects was used as the PK input into the PD 146

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model. Then 1000 PD profiles were simulated an d efficacy was evaluated based on the target of at least a 1-log kill at 24 hours. The probability of target a ttainment in each tissue was as follows: 99.90% in plasma, 99.90% in muscle, and 88.50% in adipose tissue. Based on this data the dosing regimen was deemed efficacious. However, this is based on the susceptibility of only one strain of MRSA. In order to get an accura te representation of a bacterial population, a distribution of susceptibilities is needed. This was accomplished by using the MIC distribution to create an EC50 distribution by calculating the EC50 based on the MIC. Again simulations were performed 1000 times based on each new EC50 using the same 1000 simulated PK profiles as input into the PD model. It was found that this dosing regimen is efficacious in all three tissues with pathogens which are highly susceptible to ceftobiprole. However, with pathogens which are less susceptible a different dosing regimen may need to be considered. The overall target attainment based on a target of 1-log kill at 24hours was as follows: 99.56% for free plasma, 96.45% for skeletal muscle, and 67.40% for s.c. adipos e tissue. It is importa nt to interpret these results cautiously for several r easons. One reason is that us ing the MIC to create an EC50 distribution is not entirely accurate due to the fact that the MIC is only available in two-fold increments and the EC50 can be any number inbetween two MIC values. For example, the EC50 does not have to be 1.04 or 2.09 mg/L but it ca n be 1.17 mg/L as it was found to be in the calculation of the PD parameters from the timekill experiments presented in Chapter 7. Also, by using the MIC to calculate the EC50 and then performing simulations based on the PD model the major assumption is made that although the EC50 value changes, all other PD parameters remain the same. This may or may not be true. Finally, the PK determined from the microdialysis study was done in healthy volunteers. The PK in patients and the distribution of ceftobiprole into the ISF of inf ected tissues may be different. 147

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148 In conclusion, based on the experiments performed, the currently recommended general dosing regimen of 500mg admini stered as a two-hour i.v. in fusion every eight hours is efficacious based two pharmacodynamic endpoints, a f T>MIC of 40% of the dosing interval at steady state and a 1-log bacterial ki ll at 24 hours following three subseque nt doses.

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BIOGRAPHICAL SKETCH April Marie Barbour was born March 2, 1982, in Dearborn, MI, to Raymond and Lori Barbour. She has one sibling, Christina June Barbour, who was born March 15, 1983. April grew up in Southgate, MI, and graduated high school from Southgate Anderson High School in 2000. She attended Wayne State University in Detroit, MI, from the fall of 2000 through the summer of 2002 and transferred to the State University of New York at Plattsburgh in the fall of 2002. She graduated from the State University of New York at Plattsbu rgh in May 2005 with a bachelor of science in biochemistry. Apr il started graduate school in August 2005 at the University of Florida, College of Pharmacy, Department of Pharmaceutics. Her advisor throughout her graduate work was Dr. Hartmut De rendorf. She graduated in May 2009 with a doctorate of philosophy in pharm aceutical sciences. 166



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For Chapter 6, copyright information. Guidelines for Authors Posting your articles to your institutional repositories ASM grants authors the right to post their accepted manuscripts in publicly accessible electronic repositories repositories established by a government or noncommercial entity. harge on the ASM Journals and PMC websites 6 months after final publication, ASM recommends that when submitting the accepted manuscript to PMC or institutional repositories, the author specify that the posting release date for the manuscript be no earlier than 6 months after the final publication of the typeset article by ASM. Posting your articles in full on personal or employer websites or universi prior permission, provided that proper credit is given to the original ASM publication. Making copies of your articles in full Corresponding authors are entitled to 10 free downloads of their papers. Additionally, all authors may make up to 99 copies of his/her own work for personal or professional use (including teaching packs that are distributed free of charge within your own institution). For orders of 100 or more copies, you should online journal sites. Republishing/adapting portions of your article ASM also grants the authors the right to republish discrete porti ons of his/her article in any other copyright You may obtain permission from Rightslink For technical questions about using Rightslink, please contact Customer Support via phone 877 622 5543 (toll free) or 978 777 9929, or email Rightslink customer care customercare@copyright.com