© 2015 alexander voelkner
TRANSCRIPT
PHARMACOKINETIC AND PHARMACODYNAMIC CHARACTERIZATION OF THE PLEUROMUTILIN ANTIBIOTIC RETAPAMULIN
By
ALEXANDER VOELKNER
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2015
© 2015 Alexander Voelkner
To my parents
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ACKNOWLEDGMENTS
I would like to express my sincere gratitude to Dr. Hartmut Derendorf to give me
this opportunity, but also for his guidance and support throughout my doctoral studies. I
truly enjoyed my time at his lab and working for Dr. Derendorf has been an
extraordinary learning experience. I would like to thank my supervisory committee
members, Dr. Christoph Seubert, Dr. Sihong Song, Dr. Anthony Palmieri III and Dr.
Kenneth Rand, for their support and guidance. Moreover, I would like to thank the
administrative staff of the Department of Pharmaceutics, Pat Khan, Kimberly Howell,
Vivian Lantow and Sarah Foxx and the staff at UF’s Clinical Research Center for their
support. I also had the great privilege to work with my interns Maurice, Laura, Justus,
Trang, Sebastian, Theresa, Jacqueline and Rosalie. They did an outstanding job and
without their help, I would not have been able to complete my research.
Finally, I would like to thank all the graduate students and post-docs in the
Department of Pharmaceutics, especially Frederico Martins and my wife Nivea, who
helped tremendously with completing my in vivo study. Last but not least, special thanks
go out to my parents and my German-Brazilian family for their support.
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TABLE OF CONTENTS
page
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF TABLES ............................................................................................................ 9
LIST OF FIGURES ........................................................................................................ 11
LIST OF ABBREVIATIONS ........................................................................................... 13
ABSTRACT ................................................................................................................... 16
CHAPTER
1 INTRODUCTION .................................................................................................... 18
Significance and Background ................................................................................. 18 Hypothesis and Specific Aims ................................................................................. 22
Specific Aims .................................................................................................... 22
Aim 1. Development and validation of a bioanalytical method to quantify retapamulin ............................................................................................. 22
Aim 2. In vitro microdialysis recovery determination of retapamulin ........... 22
Aim 3. Clinical microdialysis feasibility study.............................................. 23 Aim 4. In vivo microdialysis study .............................................................. 23
Aim 5. In vitro time-kill experiments ........................................................... 23
Aim 6. Development of a PK/PD model ..................................................... 24
2 LC-MS/MS METHOD DEVELOPMENT AND VALIDATION TO DETERMINE RETAPAMULIN IN NORMAL SALINE .................................................................... 25
Objective ................................................................................................................. 25 Experimental Procedure ......................................................................................... 25
Laboratory and Study Equipment ..................................................................... 25
Test article ................................................................................................. 25 Reagents.................................................................................................... 25 Equipment and disposables ....................................................................... 25
Reagent Preparation ........................................................................................ 26
Normal saline ............................................................................................. 26 Retapamulin stock solution ........................................................................ 27 Retapamulin working solutions .................................................................. 27 Tiamulin stock solution ............................................................................... 27 Tiamulin working solutions ......................................................................... 27
Retapamulin calibration standards ............................................................. 27 Tiamulin internal standard solution ............................................................ 28
Retapamulin quality control samples ......................................................... 28
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LC-MS/MS mobile phase ........................................................................... 28
LC-MS/MS washing solution ...................................................................... 28 Sample Preparations ........................................................................................ 28
LC-MS/MS Conditions ...................................................................................... 29 Quantification and QC ...................................................................................... 29 Assay Validation ............................................................................................... 30 Data Analysis ................................................................................................... 30
Results .................................................................................................................... 31
Linearity, Accuracy, Precision and Lower Limit of Quantification ..................... 31 Intra- and Inter-day Variability for Quality Control Samples .............................. 31 Freeze-thaw, Short-term, Long-term and Stock Solution Stability .................... 31 Dilution Integrity ................................................................................................ 32
Summary ................................................................................................................ 32
3 IN VITRO MICRODIALYSIS EXPERIMENTS OF RETAPAMULIN ........................ 37
Objective ................................................................................................................. 37 Experimental Procedure ......................................................................................... 37
Laboratory and Study Equipment ..................................................................... 37 Test article ................................................................................................. 37 Reagents.................................................................................................... 37
Equipment and disposables ....................................................................... 37 Reagent Preparation ........................................................................................ 39
Normal saline ............................................................................................. 39 Retapamulin stock and working solution .................................................... 39 Retapamulin calibration standards and quality controls ............................. 39
Tiamulin internal standard solution ............................................................ 39 LC-MS/MS mobile phase and washing solution ......................................... 39
Microdialysis Experiments ................................................................................ 40 Microdialysis calibration solutions .............................................................. 40
Microdialysis system .................................................................................. 40 Extraction efficiency method (EE) .............................................................. 40 Retrodialysis method (RD) ......................................................................... 41
Sample Preparation and Analysis .................................................................... 41 Results .................................................................................................................... 42
Calibration Curve and QCs ............................................................................... 42 In Vitro Microdialysis ........................................................................................ 42
Summary ................................................................................................................ 43
4 IN VITRO ANTIBACTERIAL ACTIVITY OF RETAPAMULIN .................................. 46
Objective ................................................................................................................. 46 Material and Methods ............................................................................................. 46
Antimicrobial Agent .......................................................................................... 46
Microbial Strains ............................................................................................... 46 Reagents .......................................................................................................... 46
Equipment and disposables ............................................................................. 47
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Preparation of Solutions and Broth ................................................................... 48
Sterile saline .............................................................................................. 48 Mueller-Hinton broth II ............................................................................... 48
Retapamulin primary and secondary stock solutions ................................. 48 MIC Determination ........................................................................................... 48 Retapamulin Adsorption on 24 Well Plate ........................................................ 49 Static Time-kill Curve ....................................................................................... 50 Retapamulin Stability in Mueller-Hinton Broth .................................................. 51
Results .................................................................................................................... 51 MIC Determination ........................................................................................... 51 Retapamulin Adsorption on 24 Well Plate ........................................................ 51 Retapamulin Stability in Mueller-Hinton Broth .................................................. 52 Static Time-kill Curves ...................................................................................... 52
Data Analysis ................................................................................................... 52 Summary ................................................................................................................ 52
5 RETAPAMULIN FEASIBILITY STUDY ................................................................... 59
Objective ................................................................................................................. 59 Material and Methods ............................................................................................. 59
Retapamulin Solution ....................................................................................... 59
Materials ........................................................................................................... 59 Equipment and Disposables ............................................................................. 59
Clinical Feasibility Study ................................................................................... 60 Results .................................................................................................................... 62
Patient Demographics and Baseline Characteristics ........................................ 62 In Vivo Recovery .............................................................................................. 62
Washout Period ................................................................................................ 63
Safety Assessment ........................................................................................... 63 Summary ................................................................................................................ 63
6 IN VIVO PHARMACOKINETICS OF RETAPAMULIN ............................................ 67
Objective ................................................................................................................. 67 Material and Methods ............................................................................................. 67
Antimicrobial Agents ......................................................................................... 67 Materials ........................................................................................................... 67 Equipment and disposables ............................................................................. 68 In Vivo Pharmacokinetic Study ......................................................................... 69
Anesthetization .......................................................................................... 69 Microdialysis probe implantation ................................................................ 70 Microdialysis probe stabilization ................................................................. 70 Retrodialysis .............................................................................................. 71 Baseline sample collection ......................................................................... 71
Topical administration of ointment ............................................................. 71 IV bolus administration ............................................................................... 72
Microdialysis and blood sample collection ................................................. 72
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Protein binding and Centrifree recovery ..................................................... 72
Sample preparation and analysis ............................................................... 73 Results .................................................................................................................... 74
Plasma Protein Binding and Recovery ............................................................. 74 Retapamulin Concentrations in Plasma and Skin ............................................. 74
IV bolus ...................................................................................................... 74 Topical application after tape-stripping ...................................................... 75 Topical application on intact skin ............................................................... 75
Summary ................................................................................................................ 75
7 PHARMACOKINETIC AND PHARMACODYNAMIC ANALYSIS ............................ 82
Objective ................................................................................................................. 82 Material and Methods ............................................................................................. 82
Non-compartmental Analysis ............................................................................ 82 Population Pharmacokinetic Analysis ............................................................... 83
Semi-mechanistic Pharmacodynamic Model .................................................... 83 Allometric Scaling ............................................................................................. 84
Results .................................................................................................................... 84 Non-compartmental Analysis ............................................................................ 84 Population Pharmacokinetic Analysis ............................................................... 85
Semi-mechanistic Pharmacodynamic Model .................................................... 88 Allometric Scaling ............................................................................................. 89
Summary ................................................................................................................ 92
8 DISCUSSION AND CONCLUSION ...................................................................... 106
LIST OF REFERENCES ............................................................................................. 113
BIOGRAPHICAL SKETCH .......................................................................................... 129
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LIST OF TABLES
Table page 2-1. Working solutions retapamulin ............................................................................... 33
2-2. Working solutions tiamulin ..................................................................................... 33
2-3. Calibration standards retapamulin .......................................................................... 33
2-4. Quality control samples retapamulin ...................................................................... 33
2-5. Mass transition parameters .................................................................................... 34
2-6. Intra-day variability of retapamulin ......................................................................... 34
2-7. Inter-day variability of retapamulin ......................................................................... 34
2-8. Stability results for retapamulin .............................................................................. 35
3-1. Calibration solutions for in vitro retapamulin microdialysis ..................................... 44
3-2. Calibration curve standards and QCs for in vitro microdialysis .............................. 44
3-3. In vitro microdialysis recovery results for retapamulin ............................................ 44
4-1. Pipetting scheme for retapamulin MIC determination ............................................. 54
4-2. Dilution scheme for retapamulin static time-kill curve experiments against a clinical MSSA isolate .......................................................................................... 54
4-3. Dilution scheme for retapamulin static time-kill curve experiments against MRSA ATCC 43300 ........................................................................................... 54
4-4. Dilution factors for plating the clinical MSSA isolate ............................................... 54
4-5. Dilution factors for plating the MRSA ATCC 43300 strain ...................................... 55
4-6. Contingency table of MICs for retapamulin against a clinical MSSA isolate and MRSA ATCC 4330 ............................................................................................. 55
4-7. Stability test of retapamulin in Mueller-Hinton broth II at 37˚C ............................... 55
5-1. Demographic and Baseline Characteristics ........................................................... 65
5-2. Mean in vivo recovery ............................................................................................ 65
7-1. Non-compartmental pharmacokinetic analysis for retapamulin after IV bolus administration ..................................................................................................... 94
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7-2. Non-compartmental pharmacokinetic analysis for retapamulin after topical application on tape-stripped skin ........................................................................ 94
7-3. Non-compartmental pharmacokinetic analysis for retapamulin after topical application on intact skin .................................................................................... 95
7-4. Population pharmacokinetic parameter estimates.................................................. 95
7-5. Parameter estimates for the MSSA and MRSA PD model ..................................... 96
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LIST OF FIGURES
Figure page 2-1. Mean calibration curve of retapamulin ................................................................... 36
2-2. Representative chromatogram of retapamulin ....................................................... 36
3-1. Mean recoveries of retapamulin at different concentrations using extraction efficiency and retrodialysis ................................................................................. 45
4-1. Labeling-scheme for the 24-well plate used for retapamulin MIC-determination. ... 56
4-2. Spot inoculation on sheep-blood agar plates for colony enumeration after serial dilution ................................................................................................................ 56
4-3. MIC frequency distribution of retapamulin against the tested MSSA and MRSA strains. ................................................................................................................ 57
4-4. Stability of retapamulin in Mueller-Hinton broth II at 37˚C ...................................... 57
4-5. Retapamulin time-kill curves against the tested MSSA and MRSA strains ............ 58
5-1. In vivo recovery of retapamulin determined by retrodialysis ................................... 66
5-2. Mean (SD) skin concentrations of retapamulin during the washout period ............ 66
6-1. Plasma protein binding in humans and rats ........................................................... 77
6-2. Unbound plasma and skin ISF concentration profiles of retapamulin after intravenous administration .................................................................................. 78
6-3. Unbound plasma and skin ISF concentration profiles of retapamulin after tape-stripping and topical application.......................................................................... 79
6-4. Unbound skin ISF concentration profiles of retapamulin after topical application on intact skin....................................................................................................... 80
6-5. Flowchart with time and events of the in vivo PK study .......................................... 81
7-1. Scheme of the final population pharmacokinetic model ......................................... 96
7-2. Individual unbound concentration profiles in plasma .............................................. 97
7-3. Individual unbound concentration profiles in skin ................................................... 98
7-4. Prediction-corrected VPCs for iv bolus administration ........................................... 99
7-5. Prediction-corrected VPCs for topical route of administration ................................ 99
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7-6. Basic goodness-of-fit plots ................................................................................... 100
7-8. Basic goodness-of-fit plots from the MSSA PD model ......................................... 101
7-9. VPCs for the MSSA PD model stratified for MICs ................................................ 102
7-10. Basic goodness-of-fit plots from the MRSA PD model ....................................... 103
7-11. VPCs for the MRSA PD model stratified for MICs .............................................. 104
7-12. Simulated human PK and PD profiles for retapamulin. ...................................... 105
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LIST OF ABBREVIATIONS
AIC Akaike information criterion
ANCOVA Analysis of covariance
ANOVA Analysis of variance
AUC Area under the curve
AUC0-t Area under the curve from time zero to time t
AUC0-∞ Area under the curve from time zero to infinity
BA Bioavailability
BE Bioequivalence
BSA Body surface area
CDC Center for Disease Control and Prevention
CFU Colony forming units
CI Confidence interval
CLSI Clinical and Laboratory Standards Institute
CL Clearance
CLtot Total clearance
Cmax Peak plasma concentration
Cmax/MIC Peak plasma concentration over minimum inhibitory concentration
Css Concentration at steady state
CV Coefficient of variation
dg Delay in onset of growth
dgs Delay in onset of growth of susceptible bacteria
dk Delay in onset of kill
dks Delay in onset of kill of susceptible bacteria
EC50 Concentration which induces the half-maximal drug effect
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EE Extraction efficiency
EMA European Medicines Agency
Emax Maximum effect
FDA Food and Drug Administration
fu Fraction unbound
h Hill factor
ISF Interstitial space fluid
IRB Institutional review board
IDSA Infectious Disease Society of America
IV Intravenous
k0 Zero-order absorption rate constant
k12 Transfer-rate constant from central to peripheral compartment
k21 Transfer-rate constant from peripheral to central compartment
k10 Elimination-rate constant
ka First-order absorption-rate constant
kd Death-rate constant
ks Bacterial growth-rate constant
ksr Transfer-rate constant from susceptible to resting state
krs Transfer-rate constant from resting to susceptible state
LC-MS/MS Liquid chromatography coupled with tandem mass spectrometry
MHB Mueller-Hinton broth
MIC Minimum inhibitory concentration
MD Microdialysis
MRSA Methicillin-resistant Staphylococcus aureus
MSSA Methicillin-susceptible Staphylococcus aureus
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MRT Mean residence time
N Number of bacteria
N0 Starting number bacteria
NCA Non-compartmental analysis
OFV Objective function value
PBP2a Penicillin-binding protein 2a
PD Pharmacodynamics
PK Pharmacokinetics
PPB Plasma protein binding
PopPK Population pharmacokinetics
RSE Residual standard error
S. aureus Staphylococcus aureus
SC Stratum corneum
SD Standard deviation
SE Standard error
SSSI Skin and skin structure infection
t1/2 Half-life
TEWL Transepidermal water loss
T>MIC Cumulative percentage of time where plasma concentrations are above the minimum inhibitory concentration
tmax Time of peak plasma concentration
Vc Volume of distribution in the central compartment
Vd Volume of distribution
Vss Volume of distribution at steady state
Vz Volume of distribution in the terminal phase
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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
PHARMACOKINETIC AND PHARMACODYNAMIC CHARACTERIZATION OF THE
PLEUROMUTILIN ANTIBIOTIC RETAPAMULIN
By
Alexander Voelkner
December 2015
Chair: Hartmut Derendorf Major: Pharmaceutical Sciences
Retapamulin, an antibiotic from the pleuromutilin class, is approved to treat
impetigo, a skin disease frequently caused by Staphylococcus aureus and
Streptococcus pyogenes. It inhibits the bacterial protein synthesis by binding to the 50s
subunit of the bacterial ribosome and has a unique mechanism of action. Currently,
retapamulin is marketed as topical ointment for use in adults and pediatric patients.
Pharmacokinetic data on retapamulin is limited due to low systemic exposure
after topical application. No pharmacokinetic parameters have been established for
retapamulin and concentrations at the site of action have yet to be evaluated. To
characterize the pharmacokinetics, dermal concentrations of retapamulin where
quantified by microdialysis and compared to plasma concentrations.
The pharmacodynamics of retapamulin were assessed using in vitro time-kill
curve experiments against methicillin-susceptible Staphylococcus aureus (MSSA).
Although retapamulin is indicated to treat MSSA infections only, the activity against
methicillin-resistant Staphylococcus aureus (MRSA) was also investigated and
compared to that of MSSA.
17
Pharmacokinetics were evaluated with non-compartmental and compartmental
analysis and integrated with a semi-mechanistic pharmacodynamic model to quantify
and predict retapamulin’s concentration-effect relationship under different dosing
regimens.
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CHAPTER 1 INTRODUCTION
Significance and Background
Bacterial infections of the epidermis, dermis and hypodermis are defined as skin
and skin structure infections (SSSIs). They comprise a wide range of clinical
manifestations and can be broadly classified as uncomplicated and complicated.
Uncomplicated SSSIs (uSSSIs) include superficial abscesses, erysipelas, cellulitis,
furuncles and impetiginous lesions. In contrast, complicated SSSIs (cSSSIs) involve
deep tissue infection, such as necrotizing fasciitis and myositis, or require significant
surgical intervention, e.g. ulcers, burns and major abscesses1–9. Staphylococcus aureus
(SA), a gram-positive bacteria, is the most common pathogen in SSSIs with regional
differences and varying prevalence (34.9%10, 44.6%11, 81%12). Nearly half of those SA
isolates were methicillin-resistant S. aureus (MRSA)11,12.
An estimated 7-10% of hospitalizations were due to SSSIs13–15. SA-SSSI hospital
admissions increased by 29%16 from 2000 to 2004 and by 123% between 2001 and
200917. Annual hospitalization costs due to SA-SSSI in 2008 were $4.84 billion and the
average associated cost in 2009 was $11,62217. Moreover, the number of annual
ambulatory care visits from 2001 to 2003 were 11.4 million18 and 34.8 million between
2006 and 201019. It was also reported that outpatient visits increased by 50% in from
1997 to 200520.
Retapamulin, a pleuromutilin antibiotic, is approved to treat superficial
uncomplicated skin infections caused by S. aureus and Streptococcus pyogenes21–23. It
is marketed as topical ointment (Altabax™ in USA and Altargo™ in Europe) for use in
adults and pediatric patients older than nine months. Retapamulin has a unique
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mechanism of action. It binds to the ribosomal 50S subunit, inhibits peptidyl transferase
activity and interferes with the binding of the initiator tRNA substrate to the ribosomal P-
site24,25. The drug is bacteriostatic against S. aureus at concentrations ranging from
0.03-0.25 mg/L26,27 and lacks clinically relevant target-specific cross-resistance24,28. No
resistance was observed during clinical trials following five days of treatment29–31.
Since retapamulin is applied topically, systemic exposure is low and availability of
pharmacokinetic data is limited6,32. After single topical application on 800 cm2 of intact
skin in healthy adults, systemic concentrations were very low and only 3% of the plasma
samples were above the limit of quantification (LOQ 0.5 ng/mL). On the other hand,
median Cmax in plasma was 3.5 ng/mL (range 1.2-7.8 ng/mL) after seven days of
application and 82% of the samples were quantifiable. The median Cmax in plasma
following a single dose and 7 days of application to 200 cm2 of abraded skin was 11.7
ng/mL (range 5.6-22.1 ng/mL) and 9.0 ng/mL (range 6.7-12.8 ng/mL) and 97-100% of
the samples were above LOQ25.
In another trial, plasma samples were obtained from 380 adults and 136 pediatric
patients who received Altabax™ twice daily. The median concentration was 0.8 ng/mL
and 11% of the plasma samples were quantifiable. The maximum concentrations were
10.7 ng/mL in adults and 18.5 ng/mL in pediatric patients25.
Plasma clearance was reported to be high in rats, dogs and monkeys (1-2 h).
Bioavailability was low (1-2%) following oral administration in rats. Retapamulin showed
extensive biliary excretion and plasma levels in rats and monkeys were reported to be in
the high ng/mL after oral administration of 450 mg/kg1. The drug distributed rapidly
following IV administration of radiolabelled (14C)-retapamulin in rats. Protein binding was
20
reported to be 75-94% in the order monkey<rat<human1. Volume of distribution and
clearance in humans has not been determined25. In vitro human microsome studies
suggested that the major metabolizing enzyme of retapamulin is cytochrome P450 3A4.
The major metabolic pathways were mono and di-oxygenation and N-demethylation25.
Retapamulin is heavily metabolized and about 100 metabolites were detected in
plasma, urine, faeces and bile of rats1.
Microdialysis use dates back to the early 1960s, where it was used to measure
neurotransmitter release in rodents. It was used in preclinical studies and eventually
adopted for clinical use, with first human PK studies in the early 1990s. Nowadays, it
allows to continuously measure unbound drug concentrations in virtually every tissue,
with minimal trauma33. The method itself involves the implantation of a small
microdialysis probe into the tissue, which is then constantly perfused to sample
exogenous or endogenous solutes from the extracellular space34. Solute exchange is
driven by passive diffusion against a concentration gradient and depends on perfusion
flow-rate, pore diameter of the membrane, membrane surface area, temperature, nature
of the tissue and physicochemical properties of the analyte35. Dialysate can be collected
at specific time intervals to determine the analyte concentration. Due to the constant
flow of perfusate, a complete equilibrium between perfusate and extracellular fluid
cannot be achieved, thus analyte recoveries are less than 100%. Therefore, the
microdialysis probe recovery needs to be assessed. Several calibration methods can be
used, such as low-flow-rate method, no-net-flux, dynamic no-net-flux and retrodialysis
by drug or calibrator33,36–38. For topically applied drugs, where systemic exposure is
limited, microdialysis can be useful to determine drug concentrations at the site of
21
action. Dermal microdialysis is a semi-invasive technique, which can directly quantify
free, unbound drug concentrations within the dermis. The method is also suited for
evaluating the local exposure of topical products in the skin, subcutaneous tissue and
muscle under various test conditions.39–41
To optimize antimicrobial therapy and select appropriate dosing regimens, the
PKPD relationship of anti-infectives needs to be well understood. The minimum
inhibitory concentration (MIC) has been used as a PD marker to guide dosing and drug
selections. The quantitative relationship between the concentrations of an anti-infective
drug and its antibacterial effect is labelled as PK/PD index42. The resulting PK/PD
indices are the area-under-the-curve over MIC (AUC/MIC), maximum concentrations
over MIC (Cmax/MIC) and time above MIC (T>MIC)43,44 are frequently used as target
parameters for dosing decisions. However, the MIC is a static parameter and provides
no information about the time course of an antibacterial drug as it only determines the
number of bacteria at a single time point. Furthermore, the MIC approach represents a
threshold concentration, which implies the maximum antibacterial effect at the MIC and
no effect below the MIC. PK/PD models based on time-kill curves evaluate the
antibacterial activity and bacterial growth as a function of time and antibiotic
concentration45. They provide a better understanding of the processes within the
bacterial system and help describe the killing kinetics, bacterial susceptibility, adaptation
and resistance development46–48. Subsequently, these PK/PD models can be useful in
making informed dosing decisions and therefore help to optimize antibacterial therapy
and is also acknowledged by regulatory agencies49,50.
22
Hypothesis and Specific Aims
Retapamulin ointment is efficacious to treat uncomplicated skin and skin
structure infections caused by S. aureus. It penetrates the skin and elicits a
bacteriostatic effect at the target site. The main objective of the proposed research was
to evaluate the PK of retapamulin using microdialysis and investigate its PD against S.
aureus with time-kill curve experiments. A mathematical model, integrating
concentration and pharmacological response over time helps to optimize drug therapy
and predict the antibiotic effect at the site of infection.
Specific Aims
Aim 1. Development and validation of a bioanalytical method to quantify retapamulin
Analytical methods are critical for the successful conduct of preclinical and/or
clinical pharmacology studies. To quantify in vitro and in vivo retapamulin samples, a
sensitive LC-MS/MS method will be developed and validated. Chromatographic and
mass spectrometry conditions will be optimized for retapamulin and an internal
standard. As defined in the FDA guidance, the method will be tested for selectivity,
accuracy, precision, linearity in a given concentration range, sensitivity, reproducibility
and stability. Acceptance criteria will be the same as defined in the FDA guidance.
Aim 2. In vitro microdialysis recovery determination of retapamulin
In vitro recovery experiments should be performed prior to any in vivo studies.
These experiments are essential, as they will determine if a drug is dialyzable, exhibit
any non-specific binding to the probes and has similar recovery rates at various
concentrations. All experiments will be conducted with a linear microdialysis catheter in
triplicates. The dialysis and retrodialysis methods will be employed in order to determine
23
non-specific binding of retapamulin. Recovery will be tested at low, medium and high
concentrations, which will cover the expected in vivo concentration range. Additives
may be tested and added to improve recovery.
Aim 3. Clinical microdialysis feasibility study
Three subjects will be enrolled to investigate the feasibility of using microdialysis
as a technique to determine skin concentrations of retapamulin in healthy volunteers.
The in vivo recovery as well as the washout period of retapamulin from skin will be
assessed. This study will determine if the compound is a candidate for this technique
and will help to finalize the study design and procedures for a future microdialysis study
in humans with retapamulin.
Aim 4. In vivo microdialysis study
Fifteen Wistar rats will be used to determine the pharmacokinetics of retapamulin
in plasma and in skin. Three treatment groups, with five animals in each, will be
investigated. For the first groups, an intravenous bolus will be administered to
investigate plasma pharmacokinetics and drug distribution into the skin. In the second
and third group, retapamulin ointment will be applied to intact skin and onto strip
abraded skin. Recovery will be measured prior to drug administration and microdialysis
samples collected to describe the pharmacokinetics of retapamulin in skin tissue.
Aim 5. In vitro time-kill experiments
The pharmacodynamic time course of retapamulin, at different concentrations,
against S. aureus, will be investigated. First, the MIC of retapamulin will be evaluated
using the broth microdilution technique. Then, time-kill experiments will be conducted
with drug concentrations ranging from 0.125-16x MIC. Blood agar plates will be
incubated and cell forming colonies (CFUs) counted.
24
Aim 6. Development of a PK/PD model
The pharmacokinetic (PK) and pharmacodynamic (PD) data will be analyzed
using the non-linear mixed effect modeling software NONMEM® 7.3 (ICON
Development Solutions) and the statistical computation software R version 3.1. PK
parameters, such as drug clearance, apparent volume of distribution, maximum
concentration, time to maximum concentration and area-under-the-concentration curve
(AUC) will be established. A model to describe the drug response vs. time will be
developed, as well, and integrated into the PK model.
25
CHAPTER 2 LC-MS/MS METHOD DEVELOPMENT AND VALIDATION TO DETERMINE
RETAPAMULIN IN NORMAL SALINE
Objective
The objective was to develop and validate a sensitive bioanalytical assay to
quantify retapamulin in normal saline. The assay was used to determine retapamulin
concentrations for the in vitro and in vivo microdialysis experiments. Method
development and validation was performed in accordance with the FDA guidance
((CVM), 2013) and using good laboratory practices (GLP).
Experimental Procedure
Laboratory and Study Equipment
Test article
Micronized Retapamulin (lot #WG0223980-140411001) was obtained from Ark
Pharm, Inc. The compound was stored at room temperature and protected from light.
Reagents
Unless otherwise stated, all reagents were LC-MS grade and obtained from the
specified sources.
Tiamulin, Sigma-Aldrich #34044
Acetonitrile (ACN), Fisher #A998-4
Dimethylsulfoxide (DMSO), Fisher #BP231-1
Methanol (MeOH), Fisher #A456-1
Triple distilled water (TDW), in house, Pharmaceutics Department
Sodium Chloride (NaCl), Fisher #S271-500
Formic Acid (FA), Fisher #A119P-1
Equipment and disposables
Eppendorf Research Pipettes, volume: 2-20 µL, 10-100 µL, 20-200 µL, 100-1000 µL
Eppendorf Research Plus Pipette, volume: 0.1-10 µL
26
Fisherbrand Pipet Tips
Fisherbrand microcentrifuge tubes, 0.5 mL amber vials
Fisherbrand microcentrifuge tubes, 1.5 mL amber vials
Corning 15 mL centrifuge tubes
Corning 50 mL centrifuge tubes
Sun Sri Autosampler Vial 12x32 mm, 300 µL, conical
Sun Sri 11 mm aluminum seals
Perkin Elmer 1.8 mL Screw Thread Vials 12x32 mm
Pyrex Media-lab bottles, 500 mL
Pyrex volumetric flask, 1,000 mL
Millipore nylon membrane filter type 0.2 µm
Fisher Scientific Hotplate
Fisher Scientific Mini Vortexer
Mettler Toledo AB104 balance
Perkin Elmer Series 200 Pump
Perkin Elmer Series 200 Autosampler
AB Sciex API 4000 LC/MS/MS
Waters Atlantis T3 2.1x150 mm HPLC column (S/N013333145140)
Waters Atlantis T3 2.1x10 mm Guard Cartridge
Reagent Preparation
Normal saline
Normal saline (0.9% m/V NaCl) was prepared by weighing out 9 g of NaCl and
dissolving it in 1,000 mL of triple distilled water in a volumetric flask. The solution was
27
then sonicated for 10 minutes and filtered through a Millipore nylon membrane filter (0.2
µm).
Retapamulin stock solution
The stock solution was prepared by weighing out 10 mg of retapamulin and
dissolving it in 10 mL DMSO, to obtain a 1 mg/mL solution. It was stored in a freezer at -
80˚C for not longer than 60 days.
Retapamulin working solutions
Working solution were prepared from the 1 mg/mL stock solution and methanol,
using serial dilutions (Table 2-1). All retapamulin working solutions were stored in a
freezer at -80˚C until needed.
Tiamulin stock solution
Tiamulin primary stock solution was prepared by adding 410 µL of DMSO into a
glass vial of 100 mg of tiamulin (specific gravity ~ 1.1 g/cm3). The glass vial was
vortexed. Then 50 µL of the tiamulin-DMSO solution (200 mg/mL) were mixed with 950
µL DMSO in a 1.5 mL amber micro centrifuge vial, to yield a 10 mg/mL tiamulin stock
solution. It was then stored in a refrigerator at 2-8˚C.
Tiamulin working solutions
The 10 mg/mL stock solution was used to prepare tiamulin working solutions
using serial dilutions (Table 2-2). Methanol was used as diluent and all working
solutions were stored at 2-8˚C.
Retapamulin calibration standards
Calibration standards were freshly prepared, in normal saline, on the day of
analysis from the retapamulin working solutions (Table 2-3). During method
development, a loss of signal and non-linear behavior was observed when calibration
28
standards were prepared in normal saline by serial dilution. However, when calibration
standards were prepared from the working solutions, signal response was linear.
Tiamulin internal standard solution
The internal standard solution was prepared freshly on the day of the
experiments. To yield a 25 ng/mL internal standard solution, 25 µL of a 1 µg/mL tiamulin
working solution was diluted with 975 µL of methanol in a 1.5 mL amber micro
centrifuge vial.
Retapamulin quality control samples
Quality control solutions (QCs) were obtained by diluting retapamulin working
solutions with normal saline (Table 2-4). QCs for lower limit of quantification (LLOQ; 0.5
ng/mL), low quality control (LQC; 1.5 ng/mL), medium quality control (MQC; 75 ng/mL)
and high quality control (HQC; 200 ng/mL) were prepared fresh daily.
LC-MS/MS mobile phase
Reservoir A (0.1% formic acid in H2O) was prepared by mixing 500 mL of triple
distilled water with 570 µL of 88% formic acid. Reservoir B (0.1% formic acid in ACN)
was obtained by adding 570 µL formic acid to 500 mL ACN. Mobile phases were filtered
through a Millipore nylon membrane filter (0.2 µm) and subsequently degassed with
helium for 10 min.
LC-MS/MS washing solution
375 mL of ACN and 125 mL of MeOH were mixed, filtered and degassed to
obtain the washing solution.
Sample Preparations
Frozen samples were thawed and allowed to equilibrate at room temperature.
Samples were then vortexed and an aliquot of 20 µL pipetted into a Sun Sri
29
Autosampler Vial to which 10 µL of internal standard were added. Prior to injection into
LC-MS/MS, all samples were vortexed again and checked for air bubbles.
LC-MS/MS Conditions
The LC system consisted of a Perkin Elmer Series 200 autosampler and a Perkin
Elmer Series 200 pump. Separation was performed using a Waters Atlantis T3 2.1x150
mm HPLC column, coupled with a Waters Atlantis T3 2.1x10 mm Guard Cartridge. The
mobile phases were delivered under isocratic conditions, with a ratio of 65:35 of mobile
phase A (0.1% FA in H2O) and B (0.1%FA in ACN), at a flow rate of 0.3 mL/min.
Injection volume was 10 µL.
The LC system was coupled with an AB Sciex API 4000 triple-quadrupole mass
spectrometer. Analyte and IS were ionized in positive electrospray mode and quantified
using multiple reaction monitoring (MRM). Optimized mass spectrometric parameters
were as follows: dwell time collision gas flow 5 psig, curtain gas flow 20 psig, IonSpray
nebulizer gas 35 psig, TurboIonSpray heater gas 20 psig, TurboIonSpray probe voltage
5,500 V and temperature 550˚C. Mass transitions from the protonated precursors to the
ion products are listed in Table 2-5. Hardware management and data acquisition was
handled using the Analyst Software version 1.4.
Quantification and QC
Peak area ratios of analyte and IS were used for quantification. Calibration
curves were calculated using linear least-square regression analysis and a 1/X2
weighting. Duplicates of LQC, MQC and HQC were placed within a sample batch for
quality control. Analytical runs were not rejected if at least five out of six calibration
standards, including the LLOQ and the highest concentration, where within ±15% of
30
their nominal concentration and if at least one QC at each concentration and not less
than 75% of all the QCs were within ±15% of their nominal levels.
Assay Validation
Linearity over the inspected concentration range was assessed based on
correlation coefficient (r2 ≥0.9). Intra-day and inter-day accuracy and precision were
investigated on three different days. Calibration curves and five replicates of LLOQ,
LQC, MQC and HQC were analyzed on each day. Accuracy and precision of the
standards had to be within ±15% of their nominal concentration, except for the lower
limit of quantification (LLOQ) with an allowance of ±20% deviation and if at least five out
of six standards, including the LLOQ and the highest concentration, met the criteria.
Short-term, freeze thaw, long-term and stock solution stability was determined.
For all stability tests, three replicates of each LQC and HQC were analyzed and
compared with the results of freshly prepared samples. For stock solution stability, three
aliquots of each retapamulin and tiamulin stock were compared with those made from
fresh stock solution. Samples were considered stable if the deviation was ≤10% from
their nominal concentration.
Dilution integrity was evaluated with analyte concentrations above the ULOQ
(250 ng/mL) and at the HQC level. Three replicates of each 4xULOQ and HQC
concentration were then analyzed after ten-fold dilution and compared against their
nominal concentrations.
Data Analysis
Microsoft Excel 2013, R version 3.1.2, RStudio version 0.98.1087, and the
ggplot2 package were used for data collection, statistical analysis and plot generation.
31
Results
Linearity, Accuracy, Precision and Lower Limit of Quantification
All three calibration curves were linear over the tested concentration range 0.5-
250 ng/mL (Figure 2-1). The mean slope±SE of the linear regression equation was
0.0221±0.0006, with a mean intercept±SE of -0.0018±0.0006 and a good coefficient of
determination (r2=0.997). The average±SE retention times were 3.44±0.02 minutes for
retapamulin and 3.41±0.02 minutes for tiamulin, respectively. Calibration standard’s
accuracy (%) and precision (CV %) were 92.7-102.9% and 1.5-7.8%, respectively. The
lower limit of quantification was 0.5 ng/mL. A representative chromatogram for
retapamulin and tiamulin is depicted in Figure 2-2.
Intra- and Inter-day Variability for Quality Control Samples
Intra-day accuracy and precision was ranging from 90.0-114.6% and 1.0-13.1%,
respectively (Table 2-6). Inter-day accuracy and precision were 100.4-103.7% and 7.1-
13.2% (Table 2-7).
Freeze-thaw, Short-term, Long-term and Stock Solution Stability
Retapamulin was stable at room temperature for 18h and for 86 days when
stored at -80˚C. After three freeze-thaw cycles, the concentrations at both LOQ and
HQC were still measured within ±10% of their nominal concentrations. For stock
solution stability, the area under the curve of fresh prepared retapamulin and tiamulin
stock solutions were compared with those stored for 60 days at -80˚C. All stability
results are compiled in Table 2-8.
32
Dilution Integrity
The samples used to test dilution integrity were within the acceptance range of
±15%. The accuracies after ten-fold dilution of 4xULOQ (100 ng/mL) and HQC (20
ng/mL) were 101.5% and 98.9%; precision was 1.2% and 2.8%, respectively.
Summary
A selective and sensitive bioanalytical method for the quantitative determination
of retapamulin using LC-MS/MS was developed and evaluated as per FDA guidance.
The method was reproducible and suitable to analyze retapamulin samples in saline,
ranging from 0.5 to 250 ng/mL. Retapamulin was stable under the tested conditions.
Overall, the developed method provides the means to carry out in vitro microdialysis
experiments and in vivo pharmacokinetic sample analysis.
33
Table 2-1. Working solutions retapamulin Starting Concentration (µg/mL)
Starting Volume (mL) Final Concentration (µg/mL)
Total Volume (mL)
1,000 0.1 100 1 100 0.1 10 1 10 0.1 1 1 1 0.025 0.25 1
Table 2-2. Working solutions tiamulin Starting Concentration (µg/mL)
Starting Volume (mL) Final Concentration (µg/mL)
Total Volume (mL)
10,000 0.1 1,000 1 1,000 0.1 100 1 100 0.01 1 1
Table 2-3. Calibration standards retapamulin Standard Name
Starting Concentration (µg/mL)
Starting Volume (mL)
Final Concentration (ng/mL)
Total Volume (mL)
R6 100 0.025 250 1 R5 100 0.01 100 1 R4 10 0.05 50 1 R3 10 0.01 10 1 R2 1 0.04 1 1 R1 1 0.02 0.5 1
Table 2-4. Quality control samples retapamulin QC Name Starting
Concentration (µg/mL)
Starting Volume (mL)
Final Concentration (ng/mL)
Total Volume (mL)
HQC 100 0.02 200 1 MQC 10 0.075 75 1 LQC 1 0.06 1.5 1 LLOQ 1 0.02 0.5 1
34
Table 2-5. Mass transition parameters MRM
Transition m/z
Dwell Time (ms)
Collision Energy (V)
Declustering Potential (V)
Entrance Potential (V)
Collision Exit Potential (V)
Retapamulin 518.3 → 216.1
500 37 60 15 13
Tiamulin 494.5 → 192.2
500 29 60 15 13
Table 2-6. Intra-day variability of retapamulin (n=5) LLOQ
(0.5 ng/mL) LOQ (1.5 ng/mL)
MQC (75 ng/mL)
HQC (200 ng/mL)
Day 1 Mean 0.45 1.50 85.36 201.20 Accuracy (%) 90.0 100.0 113.8 100.6 CV (%) 13.1 8.2 3.5 12.5 Day 2 Mean 0.50 1.53 75.80 207.60 Accuracy (%) 100.3 102.1 101.1 103.8 CV (%) 4.7 5.9 3.0 2.3 Day 3 Mean 0.57 1.49 72.14 197.60 Accuracy (%) 114.6 99.2 96.2 98.8 CV (%) 8.2 9.2 10.7 1.0
Table 2-7. Inter-day variability of retapamulin (n=15) LLOQ
(0.5 ng/mL) LOQ (1.5 ng/mL)
MQC (75 ng/mL)
HQC (200 ng/mL)
Mean 0.51 1.51 77.77 202.13 Accuracy (%) 101.6 100.4 103.7 101.1 CV (%) 13.2 7.4 9.5 7.1
35
Table 2-8. Stability results for retapamulin Storage condition Level Mean stability
sample (ng/mL) CV (%) Change (%)
Short-term 18h room temperature
LQC 1.32 4.5 -6.1
HQC 220.5 1.1 2.0 Freeze-thaw Three cycles at -
80˚C LQC 1.6 5.5 0.4
HQC 219 3.6 5.12 Long-term 86 days at -80˚C LQC 1.5 13.2 -6.4 HQC 210.5 5.2 -3.9 Stock 60 days at -80˚C Retapamulin 1.13x106* 4.5 6.9 Tiamulin 4.69x105* 8.4 6.3
* Area under the curve
36
Figure 2-1. Mean calibration curve of retapamulin (n=3). A linear regression model is
used with 1/X2 as weighting factor. Linearity was displayed across the tested concentration range (r2=0.997).
Figure 2-2. Representative chromatogram of retapamulin (50 ng/mL, left panel) and the
internal standard tiamulin (right panel).
0
2
4
6
0 50 100 150 200 250
Retapamulin Concentration (ng/mL)
Inte
nsity
37
CHAPTER 3 IN VITRO MICRODIALYSIS EXPERIMENTS OF RETAPAMULIN
Objective
The aim of this experiment was to evaluate the in vitro microdialysis recovery of
retapamulin under various conditions. In addition, these in vitro experiments also help to
determine the feasibility of an in vivo study. Two techniques, extraction efficiency (EE)
and retrodialysis (RD), were used to measure recovery and binding characteristics of
retapamulin.
Experimental Procedure
Laboratory and Study Equipment
Test article
Micronized Retapamulin (lot #WG0223980-140411001) was obtained from Ark
Pharm, Inc. The compound was stored at room temperature and protected from light.
Reagents
Unless otherwise stated, all reagents were LC-MS grade and obtained from the
specified sources.
Acetonitrile (ACN), Fisher #A998-4
Dimethylsulfoxide (DMSO), Fisher #BP231-1
Methanol (MeOH), Fisher #A456-1
Triple distilled water (TDW), in house, Pharmaceutics Department
Sodium Chloride (NaCl), Fisher #S271-500
Formic Acid (FA), Fisher #A119P-1
Equipment and disposables
Eppendorf Research Pipettes, volume: 2-20 µL, 10-100 µL, 20-200 µL, 100-1000 µL
Eppendorf Research Plus Pipette, volume: 0.1-10 µL
Fisherbrand Pipet Tips
38
Fisherbrand microcentrifuge tubes, 0.5 mL amber vials
Fisherbrand microcentrifuge tubes, 1.5 mL amber vials
Corning 15 mL centrifuge tubes
5 mL BD Luer-Lok syringe, non-sterile
Sun Sri Autosampler Vial 12x32 mm, 300 µL, conical
Sun Sri 11 mm aluminum seals
Pyrex petri dish
Pyrex volumetric flasks, volume: 10 mL, 200 mL
Pyrex Media-lab bottles, 500 mL
Millipore nylon membrane filter type 0.2 µm
Harvard Apparatus Model 22 Multiple Syringe Pump
µdialysis 66 Linear Catheter
Fisher Scientific Hotplate
Fisher Scientific Mini Vortexer
Mettler Toledo AB104 balance
Perkin Elmer Series 200 Pump
Perkin Elmer Series 200 Autosampler
AB Sciex API 4000 LC/MS/MS
Waters Atlantis T3 2.1x150 mm HPLC column (S/N013333145140)
Waters Atlantis T3 2.1x10 mm Guard Cartridge
Parafilm
39
Reagent Preparation
Normal saline
9 g of NaCl were dissolved in 1,000 mL triple distilled water to obtain normal
saline (0.9% m/V). After sonication for 10 min, the solution was filtered.
Retapamulin stock and working solution
Stock solution was prepared as described in chapter 2, by weighing out 10 mg of
retapamulin and dissolving it in 10 mL DMSO. Then, 100 µL of the retapamulin stock
solution (1 mg/mL) were diluted with 900 µL of methanol, to yield a 100 µg/mL working
solution.
Retapamulin calibration standards and quality controls
Six calibration standards were freshly prepared from the retapamulin working
solutions according to table 2-3. The quality control solutions LQC (1.5 ng/mL), MQC
(75 ng/mL) and HQC (200 ng/mL) were prepared using the dilution scheme described in
table 2-4.
Tiamulin internal standard solution
Internal standard solution was prepared freshly on the day of the experiments as
described in chapter 2. 25 µL of a 1 µg/mL tiamulin working solution was diluted with
975 µL of methanol in a 1.5 mL amber micro centrifuge vial, to obtain internal standard
solution (25 ng/mL).
LC-MS/MS mobile phase and washing solution
Reservoir A (0.1% formic acid in H2O) and reservoir B (0.1% formic acid in ACN)
were obtained by adding 570 µL formic acid to 500 mL triple distilled water and ACN,
respectively. Washing solution was made by mixing 375 mL of ACN with 125 mL of
40
MeOH. Before degassing with helium, the fresh prepared mobile phases and washing
solution were filtered through a 0.2 µm Millipore nylon membrane filter.
Microdialysis Experiments
Microdialysis calibration solutions
The in vitro microdialysis recovery of retapamulin was determined by extraction
efficiency (EE) and retrodialysis (RD) at three different concentrations (5, 50 and 100
ng/mL). Preparation of the calibration solutions was done in a 200 mL volumetric flask
by adding working solution to 200 mL of normal saline (Table 3-1).
Microdialysis system
A µdialysis 66 linear mircrodialysis catheter, with 30 mm membrane length and
20kDa cut-off, was used for the in vitro experiments. The probe was connected to a 5
mL BD Luer-Lok syringe. Perfusion rate was kept at 1.5 µL/min using a Harvard
Apparatus Model 22 multiple syringe pump. The three different retapamulin
concentrations, ranging from 5 ng/mL to 100 ng/mL, were tested in ascending order. All
in vitro microdialysis experiments were carried out at 37°C and run in triplicates.
Extraction efficiency method (EE)
For recovery determination using extraction efficiency, the 5 mL syringe was
filled with blank saline and connected to the microdialysis catheter. Prior to the start of
the experiments, the probe was flushed for 20 min to remove air bubbles and check
proper functioning. Then it was placed into a petri dish, filled with 30 mL of retapamulin
solution (reservoir) and covered with parafilm to prevent evaporation. After a 30 min
equilibration period, approximately 45 µL dialysate was collected in a microcentrifuge
tube for 30 mins. Two 45 µL aliquots from the reservoir were also taken at the beginning
and at the end of the experiment.
41
Recovery determined by extraction efficiency was calculated by the equation:
𝑅% = 𝐶𝑑𝑖𝑎𝑙𝑦𝑠𝑎𝑡𝑒
𝐶𝑟𝑒𝑠𝑒𝑟𝑣𝑜𝑖𝑟∗ 100% (3-1)
where R% is recovery in percent, Cdialysate is the retapamulin concentration in the
dialysate and Creservoir is the average drug concentration in the reservoir.
Retrodialysis method (RD)
In the retrodialysis experiment, the 5 mL syringe was filled with retapamulin
solution and connected to the microdialysis catheter. The probe was flushed for 20 min
before the start of the experiment to remove air bubbles and check functionality. It was
then placed into a petri dish, filled with 30 mL of blank saline and covered with parafilm
to prevent evaporation. Similar to the EE experiment, the probe was equilibrated for 30
min and approximately 45 µL dialysate was collected in a microcentrifuge tube over 30
mins. Before the start and after the experiment was finished, two 45 µL aliquots were
taken from the 5 mL drug-containing syringe.
Retrodialysis recovery was calculated by the equation:
𝑅% = 100% ∗ (1 −𝐶𝑑𝑖𝑎𝑙𝑦𝑠𝑎𝑡𝑒
𝐶𝑠𝑦𝑟𝑖𝑛𝑔𝑒) (3-2)
where R% is recovery in percent, Cdialysate is the retapamulin concentration in the
dialysate and Csyringe is the average drug concentration in the syringe.
Sample Preparation and Analysis
Samples were analyzed on the same day of the in vitro experiments. The
microcentrifuge tubes containing the samples were vortexed and 20 µL pipetted into
Sun Sri Autosampler vials. Next, 10 µL of IS was added, the autosampler vials capped
and vortexed again. Double blank, blank, six calibration standards and duplicates of
LQC, MQC and HQC were prepared and placed throughout the run. Analytical runs
42
were not rejected if at least five out of six calibration standards were within ±15% (±20%
for LLOQ) and if four out of six QCs, with at least one QC at each level, were within
±15% of their nominal concentrations. LC-MS/MS conditions were the same as
specified in chapter 2. In order to determine the actual drug concentration at the
sampling site, Ctissue, the concentration in the dialysate, Cdialysate, has to be back-
calculate using the following equation:
𝐶𝑡𝑖𝑠𝑠𝑢𝑒 = 100% ∗ (𝐶𝑑𝑖𝑎𝑙𝑦𝑠𝑎𝑡𝑒
𝑅%) (3-3)
Microsoft Excel 2013, R version 3.1.2, RStudio version 0.98.1087, and the
ggplot2 package were used for data collection, statistical analysis and plot generation.
Results
Calibration Curve and QCs
The slope of the calibration curve after linear regression, with 1/X2 weighting,
was 0.0208±0.0006 (estimate±SE) with an intercept of 0.0138±0.0006 (estimate±SE)
and a coefficient of correlation r2=0.996. Accuracy of calibration standards was between
91.5% and 109%. The accuracy of the QCs was 98-108.3% and precision at the LQC,
MQC and HQC level was 4.6%, 5.1% and 7.8%, respectively. Inclusion criteria
(accuracy and precision within ±15% and ±20% for LLOQ) were met for all calibration
standards and QCs (Tables 3-2).
In Vitro Microdialysis
The recovery results from the in vitro microdialysis experiments determined by
the extraction efficiency and retrodialysis method are summarized in Table 3-3.
Recovery for the three concentrations tested ranged from 83.8-96.5 for EE and 95.0-
97.7% for RD, respectively. Overall recoveries were 90.1% for the extraction efficiency
43
method and 96.0% for the retrodialysis method, suggesting that there is no difference
between the two methods (ANCOVA, p=0.0711) and that retapamulin can freely pass
the membrane.
Summary
The in vitro microdialysis experiments confirmed that retapamulin was dialyzable
in saline. Recovery was high for both extraction efficiency and retrodialysis method and
no significant difference was found between the methods. Therefore, microdialysis can
be used as a sampling technique to obtain pharmacokinetic profiles of retapamulin.
44
Table 3-1. Calibration solutions for in vitro retapamulin microdialysis Starting Concentration (µg/mL)
Starting Volume (mL) Final Concentration (ng/mL)
Total Volume (mL)
100 0.2 100 200 100 0.1 50 200 100 0.01 5 200
Table 3-2. Calibration curve standards and QCs for in vitro microdialysis Name Concentration
(ng/mL) Calculated concentration (ng/mL)
Accuracy (%)
R1 0.5 0.502 100.4 R2 1 0.915 91.5 R3 10 9.92 99.2 R4 50 50.7 101.4 R5 100 109 109 R6 250 243 97.2 LQC 1.5 1.48 98.7 LQC 1.5 1.58 105.3 MQC 75 75.6 100.8 MQC 75 81.2 108.3 HQC 200 196 98.0 HQC 200 207 103.5
Table 3-3. In vitro microdialysis recovery results for retapamulin (n=3) EE RD Concentration (ng/mL)
R% SD% CV% R% SD% CV%
5 83.8 8.1 9.7 95.2 1.3 1.4 50 96.5 6.8 7.1 97.7 0.8 0.8 100 90.0 8.4 9.3 95.0 2.8 2.9 Total 90.1 8.7 9.7 96.0 2.1 2.1
45
Figure 3-1. Mean recoveries of retapamulin at different concentrations using extraction
efficiency and retrodialysis.
0
10
20
30
40
50
60
70
80
90
100
110
5 50 100
Concentration (ng/mL)
Me
an
Re
co
ve
ry (
%)
Method
Extraction efficiency
Retrodialysis
46
CHAPTER 4 IN VITRO ANTIBACTERIAL ACTIVITY OF RETAPAMULIN
Objective
The goal of this study was to assess the in vitro antibacterial effect of retapamulin
against a clinical methicillin-susceptible Staphylococcus aureus (MSSA) isolate and to
test if the drug is also effective against the methicillin-resistant Staphylococcus aureus
(MRSA) ATCC 43300 strain. Retapamulin’s pharmacodynamics were investigated by
minimum inhibitory concentration (MIC) and static time-kill curve experiments, at varying
concentrations, for both strains.
Material and Methods
Antimicrobial Agent
Micronized Retapamulin (lot #WG0223980-140411001) was obtained from Ark
Pharm, Inc. The compound was stored at room temperature and protected from light.
Microbial Strains
Methicillin-susceptible Staphylococcus aureus (MSSA), clinical isolate provided by UF Shands microbiology lab
Methicillin-resistant Staphylococcus aureus (MRSA) ATCC 43300, in house collection
Cryopreserved bacterial cultures were activated by incubating them on sheep-
blood agar plates for three days. The same subcultured isolate was used throughout the
MIC and time-kill curve experiments.
Reagents
Acetonitrile (ACN), Fisher #A998-4
Dimethylsulfoxide (DMSO), Fisher #BP231-1
Methanol (MeOH), Fisher #A456-1
Triple distilled water (TDW), in house, Pharmaceutics Department
Sodium Chloride (NaCl), Fisher #S271-500
Muller-Hinton broth II (Becton Dickinson, #212322)
47
Equipment and Disposables
Remel sheep-blood agar plates
Eppendorf Research Pipettes, volume: 2-20 µL, 10-100 µL, 20-200 µL, 100-1000 µL
Eppendorf Research Plus Pipette, volume: 0.1-10 µL
Fisherbrand Pipet Tips
Mettler Toledo AB104 balance
Labline Model 460 CO2 culture incubator
Steris Amsco Renaissance 3021 autoclave
Fisher culture flasks (50 mL, vented caps)
Fisher glass tubes
Millipore nylon membrane filter type 0.2 µm
Abbott Lab A-JUST turbidimeter
Remel Microbiolgy Products McFarland equivalence turbidity standard
Corning 24- and 96-well plates
Fisher sterile disposable loops
Fisherbrand microcentrifuge tubes, 0.5 mL amber vials
Corning 15 mL centrifuge tubes
5 mL BD Luer-Lok syringe, non-sterile
Sun Sri Autosampler Vial 12x32 mm, 300 µL, conical
Sun Sri 11 mm aluminum seals
Fisher Scientific Hotplate
Fisher Scientific Mini Vortexer
Perkin Elmer Series 200 Pump
Perkin Elmer Series 200 Autosampler
48
AB Sciex API 4000 LC/MS/MS
Waters Atlantis T3 2.1x150 mm HPLC column (S/N013333145140)
Waters Atlantis T3 2.1x10 mm Guard Cartridge
Parafilm
Preparation of Solutions and Broth
Sterile saline
Sterile saline was prepared by dissolving 9 g of NaCl in 1,000 mL of triple
distilled water. The solution was then autoclaved for 30 minutes at 121˚C.
Mueller-Hinton broth II
Mueller-Hinton broth II (cation-adjusted) was prepared according to the
manufacturer’s instructions: 22 g of the powder were suspended into 1 L of triple
distilled water, mixed thoroughly and heated with frequent agitation. It was then
autoclaved at 121˚C for 30 minutes.
Retapamulin primary and secondary stock solutions
Primary stock solution (1 mg/mL) was prepared by weighing out 10 mg of
retapamulin and dissolving it in 10 mL of DMSO. The suspension was vortexed until
drug was completely dissolved. Secondary stock solution (50 µg/mL) was made by
mixing 250 µL of primary stock solution with 4.75 mL triple distilled water. The
secondary stock solution was sterilized by filtration (filter pore size 0.22 µm).
MIC Determination
All experiments were conducted according to the Clinical and Laboratory
Standards Institute’s M07-A9 method (“Methods for Dilution Antimicrobial Susceptibility
Tests for Bacteria That Grow Aerobically”). MICs of both strains were determined in
duplicates on three different days.
49
A bacterial dispersion, containing approximately 1.5 x 108 CFU/mL, was prepared
by dispensing overnight S. aureus colonies into sterile saline. It was then adjusted to a
0.5 McFarland standard using the turbidimeter.
Next, a 24-well plate was labeled according to Figure 4-1. 920 µL broth and 80
µL retapamulin secondary stock solution were pipetted into well C1 and mixed.
Subsequently, 500 µL of broth were added to wells C2 to C8 and retapamulin
concentrations were prepared by serial two-fold dilutions, ranging from 0.016 µg/mL to 2
µg/mL (Table 4-2). After serial dilution, 500 µL of C8 were discarded and wells C1 to C8
filled again with 490 µL of broth. Then, 10 µL of bacterial dispersion were added to each
well to yield an approximate starting inoculum of 106 CFU/mL. Negative control (NC,
containing no bacteria and no drug) and growth control (GC, containing no drug but
bacteria) were also included. For the growth control, 990 µL of broth and 10 µL bacterial
dispersion were added to well GC. The negative control contained 1,000 µL of broth.
The well plates were wrapped in parafilm immediately, to prevent evaporation,
and placed in an incubator at 37˚C for 20h. Following the incubation under constant
shaking, plates were removed from the incubator and the least concentration with no
visible growth indicated the MIC. Growth control and negative control were also
checked to ensure viability of the bacterial isolate and sterility of the broth.
Retapamulin Adsorption on 24 Well Plate
During the development of the bioanalytical assay we encountered loss of signal
of the calibration standards and nonlinear calibration curves when serial dilutions of
retapamulin were employed. As MICs were determined with serial two-fold dilution, we
wanted to investigate if the same behavior was seen throughout the MIC experiments.
50
To examine linearity of the MICs, broth was added to eight wells of a 24 well
plate and diluted as described in Table 4-2. However, the 10 µL of bacterial dispersion
were replaced with broth. Broth with drug concentrations ranging from 0.016-2 µg/mL
were incubated at 37˚C and constantly shaken for 20h. Thereafter, 20 µL were removed
from each well, pipetted into 0.5 mL microcentrifuge vials, mixed with 180 µL of ACN
and centrifuged at 12,000 rpm for 10 minutes. 20 µL of the supernatant were transferred
into autosampler vials and spiked with 10 µL of IS. Analysis was done using the LC-
MS/MS method described in Chapter 2.
Static Time-kill Curve
The modified droplet method51 was used and time-kill curve experiments were
performed in triplicates for each strain. The flasks were filled with 19.9 mL of MHBII and
0.1 mL of bacterial suspension, yielding a starting inoculum of approximately 106
CFU/mL. Prior to adding any drug the culture flasks were incubated at 37˚C, under
constant shaking, for 2h. This was done to ensure that bacteria were in their exponential
growth phase. Retapamulin was then added and concentrations for the clinical MSSA
isolate were 0.25-16xMIC and for the MRSA ATCC 43300 strain 0.125-16xMIC,
respectively. Dilution schemes for retapamulin are shown in Table 4-3. A growth control,
without antimicrobial agent, and a negative control, with broth only, were also included.
The flasks were incubated for 24 h at 37˚C. Sampling times were 0, 2, 4, 6, 8, 10,
12, 16 and 24 h and 20 µL aliquots were taken from each flask. Appropriate serial ten-
fold dilutions, ranging from 1:10 to 1:108, were performed with sterile saline in 96-well
plates (Tables 4-4 and 4-5). Five 10 µL aliquots from the diluted samples were plated in
duplicates on sheep-blood agar plates (Figure 4-2). After incubation for 16-20 h at 37˚C,
51
colonies were counted in all readable plates (≤200 colonies). Bacterial count was
transformed into CFU/mL by the following equation:
𝐶𝐹𝑈
𝑚𝐿= (𝐶𝐹𝑈𝑐𝑜𝑢𝑛𝑡𝑒𝑑 ∗ 10𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛) ∗
10
𝑚𝐿 (4-1)
Retapamulin Stability in Mueller-Hinton Broth
Drug stability was evaluated at three different concentrations over 24 h. Sampling
times for stability tests were 0, 8, 16 and 24 h at concentrations 0.25x, 1x and 4xMIC.
100 µL of broth was removed from the respective flasks. Then, 200 µL of ACN was
added, the mix centrifuged at 3,000 g for 15 minutes and the supernatant stored at -80
˚C until analysis. Samples were vortexed, thawed and 20 µL pipetted into autosampler
vials and spiked with 10 µL internal standard. The samples were analyzed with the
developed LC-MS/MS method and concentrations at times 8, 16 and 24 h were
compared with the initial concentrations
Results
MIC Determination
The MIC values of retapamulin for both strains were 0.125-0.25 µg/mL. The
higher MIC was detected in 66.7% of the observations for the MSSA strain, while it was
found in 50% of the experiments for the MRSA ATCC 43300 strain. The results are
summarized in Table 4-6 and shown in Figure 4-3.
Retapamulin Adsorption on 24 Well Plate
Retapamulin displayed linearity for the tested concentrations and the coefficient
of correlation was r2=0.996. Hence, adsorption on the 24-well plate was not observed
and did not interfere with MIC determination.
52
Retapamulin Stability in Mueller-Hinton Broth
Retapamulin was stable in MHBII at 37˚C for 24 h (Figure 4-4) and no
degradation was detected (ANCOVA p=0.533). Concentrations after 24 h were 92.3%
(0.25xMIC), 99.4% (1xMIC) and 99.0% (4xMIC) of the initial concentrations. Results are
summarized in Table 4-7.
Static Time-kill Curves
An MIC of 0.25 µg/mL was assumed for the experiments. The higher MIC was
selected because of its frequency and the fact that MICs may be anywhere between the
last dilution inhibiting growth and the first dilution not inhibiting growth52. Time-kill curve
results are presented in Figure 4-5. Both curves looked similar. Initially, the drug effect
was delayed during the first 2 h, followed by a rapid killing and a slower rate of
elimination after 6 h. The bacterial effect was dose dependent until 1xMIC (0.25 µg/mL)
was reached. Concentrations greater than 1xMIC did not increase the antimicrobial
effect. For concentrations ≥1xMIC, a 2-log10 reduction (99% bacteria killed) from the
initial inoculum was observed after 24 h, indicating a bacteriostatic effect of
retapamulin53. The time-kill curves also showed biphasic behavior suggesting the
existence of susceptible and persistent bacterial cells48,54,55
Data Analysis
Data was entered in Microsoft Excel 2013, statistical analysis was done in R
version 3.1.2 and RStudio version 0.98.1087, and plots were generated using the
ggplot2 package.
Summary
Retapamulin was shown to be active against the tested MSSA and MRSA
isolates. MICs for both strains were 0.125 µg/mL and 0.25 µg/mL and well within the
53
range of literature reports26,27. Time-kill curves were also similar which supports
previous findings that retapamulin has in vitro activity against certain MRSA
strains27,56,57. The drug showed a delayed onset of action and a bacteriostatic,
concentration-dependent effect. This was consistent with literature reports of
concentration-dependent inhibition of ribosomal subunit assembly in S. aureus cells58.
However, drug concentrations ≥0.25 µg/mL did not further increase the bacterial kill. A
biphasic kill was observed for retapamulin suggesting growing susceptible and dormant,
non-susceptible bacterial cells48.
54
Table 4-1. Pipetting scheme for retapamulin MIC determination C1 C2 C3 C4 C5 C6 C7 C8
Concentration (µg/mL)
2 1 0.5 0.25 0.125 0.063 0.031 0.016
Volume solution (µL) 80 2nd stock
500 of C1
500 of C2
500 of C3
500 of C4
500 of C5
500 of C6
500 of C7
Broth (µL) 920 500 500 500 500 500 500 500 Broth to add (µL) 490 490 490 490 490 490 490 490 Bacterial dispersion (µL)
10 10 10 10 10 10 10 10
Final volume (µL) 1,000 1,000 1,000 1,000 1,000 1,000 1,000 1,000
Table 4-2. Dilution scheme for retapamulin static time-kill curve experiments against a clinical MSSA isolate
MIC 0.25 0.5 1 2 4 16
Concentration (µg/mL)
0.063 0.125 0.25 0.5 1 4
Volume 2nd stock (µL)
25 50 100 202 408 1,740
Table 4-3. Dilution scheme for retapamulin static time-kill curve experiments against MRSA ATCC 43300
MIC 0.125 0.25 0.5 1 2 4 16
Concentration (µg/mL)
0.031 0.063 0.125 0.25 0.5 1 4
Volume 2nd stock (µL)
12.5 25 50 100 202 408 1,740
Table 4-4. Dilution factors for plating the clinical MSSA isolate Time (h) Growth
control 0.25xMIC 0.5xMIC 1xMIC 2xMIC 4xMIC 16xMIC
0 3-4 3-4 3-4 3-4 3-4 3-4 3-4 2 4-5 3-4 3-4 3-4 3-4 3-4 3-4 4 5-6 4-5 3-4 2-3 2-3 2-3 2-3 6 6-7 4-5 3-4 2-3 2-3 2-3 2-3 8 6-7 4-5 3-4 2-3 2-3 2-3 2-3 10 6-7 4-5 3-4 2-3 1-2 1-2 2-3 12 6-7 5-6 3-4 2-3 1-2 1-2 1-2 16 7-8 5-6 3-4 2-3 1-2 1-2 1-2 24 7-8 5-6 4-5 1-2 1-2 1-2 1-2
55
Table 4-5. Dilution factors for plating the MRSA ATCC 43300 strain Time (h)
Growth control
0.125xMIC 0.25xMIC 0.5xMIC 1xMIC 2xMIC 4xMIC 16xMIC
0 3-4 3-4 3-4 3-4 3-4 3-4 3-4 3-4 2 4-5 4-5 4-5 3-4 3-4 3-4 3-4 3-4 4 5-6 4-5 3-4 3-4 2-3 2-3 2-3 2-3 6 6-7 4-5 3-4 3-4 2-3 2-3 2-3 2-3 8 6-7 4-5 3-4 2-3 2-3 2-3 2-3 2-3 10 6-7 5-6 4-5 2-3 2-3 2-3 2-3 2-3 12 6-7 5-6 4-5 2-3 1-2 1-2 1-2 1-2 16 6-7 5-6 4-5 2-3 1-2 1-2 1-2 1-2 24 7-8 5-6 4-5 2-4 1-2 1-2 1-2 1-2
Table 4-6. Contingency table of MICs for retapamulin against a clinical MSSA isolate and MRSA ATCC 4330
MSSA MRSA
MIC 0.125 µg/mL 2 3 MIC 0.25 µg/mL 4 3
Table 4-7. Stability test of retapamulin in Mueller-Hinton broth II at 37˚C. Results are
shown as percentage of starting concentration 0 h 8 h 16 h 24 h
0.25xMIC (0.063 µg/mL) 100 % 104.3 % 94.9 % 92.3 % 1xMIC (0.25 µg/mL) 100 % 100.3 % 100.3 % 99.4 % 4xMIC (1 µg/mL) 100 % 99.2 % 111.8 % 99.0 %
56
Figure 4-1. Labeling-scheme for the 24-well plate used for retapamulin MIC-determination.
Figure 4-2. Spot inoculation on sheep-blood agar plates for colony enumeration after serial dilution. Five 10 µL spots in duplicates were plated for each dilution (n and (n+1)).
C1 C2 C3 C4 C5 C6
C7 C8 C1 C2 C3 C4
C5 C6 C7 C8 NC GC
10-n
10-n 10-(1+n)
10-(1+n)
57
Figure 4-3. MIC frequency distribution of retapamulin against the tested MSSA and
MRSA strains.
Figure 4-4. Stability of retapamulin in Mueller-Hinton broth II at 37˚C.
33.3
50
66.7
0.125 0.25
MIC (µg/mL)
Fre
qu
en
cy (
%)
Strain
MRSA
MSSA
0
20
40
60
80
100
0 8 16 24
Time (h)
Dru
g R
em
ain
ing
(%
)
MIC
0.25
1
4
58
Figure 4-5. Retapamulin time-kill curves against the tested MSSA and MRSA strains.
59
CHAPTER 5 RETAPAMULIN FEASIBILITY STUDY
Objective
Microdialysis allows to measure drug concentrations in skin after topical
application. The rationale of the feasibility study was to assess the in vivo recovery and
washout time following perfusion of retapamulin in healthy volunteers. Secondary
objectives were to investigate the safety and tolerability of the microdialysis technique.
Material and Methods
Retapamulin Solution
Sterile, 50 ng/mL retapamulin solution in normal saline was provided by DaVita
Clinical Research (Minneapolis, MN).
Materials
1% Lidocaine solution
8.4% Sodium bicarbonate solution
10.5 mL ChloraPrep applicator
Normal saline
Ultrasound gel
Equipment and Disposables
Sterile drapes
BD 27g needles
BD 19g needles
BD 20g spinal needles
Latex biogel gloves
Luer lock injection ports
Surgical clamps
Eppendorf Research Pipettes, volume: 2-20 µL, 10-100 µL, 20-200 µL, 100-1000 µL
60
Eppendorf Research Plus Pipette, volume: 0.1-10 µL
Fisherbrand Pipet Tips
Fisherbrand microcentrifuge tubes, 0.5 mL amber vials
10 mL BD Syringe, sterile
5 mL BD Luer-Lok syringe, non-sterile
BD Microtainer PST tubes with Li-Heparin
3M Surgical Clipper Kit
Surgical marker
Sun Sri Autosampler Vial 12x32 mm, 300 µL, conical
Sun Sri 11 mm aluminum seals
Fisher Scientific Mini Vortexer
Harvard Apparatus Model 22 Multiple Syringe Pump
µdialysis 66 Linear Catheter
Perkin Elmer Series 200 Pump
Perkin Elmer Series 200 Autosampler
AB Sciex QTrap 5500 LC/MS/MS
Waters Atlantis T3 2.1x150 mm HPLC column (S/N013333145140)
Waters Atlantis T3 2.1x10 mm Guard Cartridge
Pyrex volumetric flasks, volume: 10 mL, 200 mL
Pyrex Media-lab bottles, 500 mL
Perkin Elmer Series 200 Pump
Clinical Feasibility Study
The study protocol and informed consent form (ICF) was approved by the
institutional review board (IRB) in accordance with the International Conference on
61
Harmonisation of Technical Requirements for Registration of Pharmaceuticals for
Human Use (ICH), Good Clinical Practice (GCP) and United States (US) 21 Code of
Federal Regulations (CFR) 312.3(b) for constitution of independent ethics committees.
The study was conducted in accordance with ICH GCP and the ethical principles of the
Declaration of Helsinki.
This study was a single session, open-label, single-center study and consisted of
a screening phase (up to 30 days prior to Study day), treatment phase (study day) and
a follow-up phone call (within 72 h after discharge). After screening and obtaining
written consent, eligible subjects were admitted to the clinical research center.
On the day of dosing, the thigh of the subjects was locally anesthetized with
lidocaine solution and three microdialysis probes were placed into the skin. Probe depth
was measured using ultrasound. After a 30 min equilibration period with normal saline,
the retapamulin solution was perfused through each probe at a flow rate of 1.5 µL/min
for 90 minutes. Samples for recovery determination were collected for the last 30
minutes of the retapamulin perfusion. Then, saline was perfused for four hours and
dialysate samples were collected every 30 minutes to determine the washout period.
Subjects were discharged from the research center following completion of the study
procedures and a follow-up phone call occurred 1-3 days after the last dose of study
medication.
All samples were stored at -80˚C and analyzed using the validated LC-MS/MS
method. The sample analysis, however, was performed on an AB Sciex QTrap 5500
system, which was more sensitive with an LLOQ of 0.25 ng/mL. Samples were thawed,
vortexed and transferred into autosampler vials. Samples containing less than 10 µL of
62
dialysate were not able to be analyzed. Calibration curve standards along with quality
controls (QCs) at three different concentration levels (duplicates) were prepared.
Analytical runs were accepted if at least two-thirds of the QCs were within ±15% of their
nominal range and not more than one QC at each level outside the ±15% concentration
interval.
Adverse events (AEs) were collected from the start of the study treatment until
the follow-up phone call. Clinical laboratory tests and vital signs were measured at
screening and on the study day. Electrocardiograms and physical examinations were
performed during screening only.
Results
Patient Demographics and Baseline Characteristics
Two male and one female subject were enrolled into the study. Their age ranged
from 24 to 55 years (mean±SD 34.7±17.6 years). Their average±SD weight was
79.8±16.1 kg with a mean±SD BMI of 26.7±3.8 kg/m2. All baseline characteristics are
summarized in Table 5-1.
In Vivo Recovery
All subjects received 50 ng/mL of retapamulin solution through the implanted
microdialysis probes. Three catheters were inserted into the thigh of subjects 1 and 2,
while subject 3 only had two probes inserted. Recovery percentage was calculated
using equation 3-2.
In vivo recovery ranged from 77.49% to 94.36%, with an overall recovery of
88.22%. The lowest recovery was observed in the only female of the study (subject 1).
Variability was also higher if compared to the two male study participants. Results are
summarized in Table 5-2 and Figure 5-1.
63
Washout Period
Washout sample concentrations (mean±SD) for each subject are displayed in
Figure 5-2. Because dialysate samples were collected over a period of 30 minutes, the
corresponding time point of a concentration was the mean of this time interval.
The first washout time point (2 to 2.5 h) for subject 2 yielded an insufficient
volume, hence no concentrations were determined. The next time point (2.5 to 3 h) had
only one measurable sample, therefore SD estimation was not applicable. All mean
concentrations and SD for subject 3 were estimated based on two dialysate samples at
each time point.
Retapamulin dialysate concentrations were rapidly decreasing during the first
hour of the washout (2 to 3 h). Drug clearance then slowed down and appeared to be
steady at a concentration close to the limit of quantification for subjects 2 (0.39 ng/mL)
and 3 (0.27 ng/mL). Subject 1, however, had higher dialysate concentrations in
comparison to subjects 2 and 3 and a slower rate of elimination of the drug. After four
hours of washout, the tissue dialysate concentrations were 0.99 ng/mL.
Safety Assessment
Two subjects each reported one mild adverse event after being discharged from
the clinical research center. One experienced a headache which resolved on the same
day, while the other reported AE was a mild pain in the extremity that resolved four days
after follow-up. All reported AEs were non serious and might be related to study
treatment.
Summary
Three healthy subjects completed the microdialysis feasibility study. Retapamulin
is dialyzable in vivo and exhibited good probe recovery, with a mean recovery rate of
64
88.22±11.59% at a flow rate of 1.5 µL/min. The results were in agreement with recovery
rates determined by in vitro experiments. Skin concentrations after four hours of
retapamulin washout were ranging from 0.27 to 0.99 ng/mL. Although retapamulin
concentrations were detectable, a four hour washout period may be sufficient
considering that concentrations in the skin will likely be higher after topical application.
In order to have an antimicrobial effect, skin concentrations should be in the magnitude
of the MIC of retapamulin (e.g. 0.03-0.25 µg/mL for S. aureus). Thus, remaining
retapamulin in the skin should be negligible.
Occurred adverse events were of mild intensity and not serious. Overall, the
microdialysis method was tolerable and safe.
65
Table 5-1. Demographic and Baseline Characteristics Demographics
Age in Years [Mean (SD)] 34.7 (17.6) Sex [n (%)] Female 1 (33.3) Male 2 (66.7) BMI (kg/m2) [Mean (SD)] 26.7 (3.8) Height (cm) [Mean (SD)] 172.7 (12.5) Weight (kg) [Mean (SD)] 79.8 (16.1) Ethnicity [n (%)] Hispanic or Latino 1 (33.3) Not Hispanic or Latino 2 (66.7) Race [n (%)] Asian – Central/South Asian Heritage 1 (33.3) White – White/Caucasian/European Heritage 2 (66.7)
Table 5-2. Mean in vivo recovery percentages, sample size (N), standard deviation (SD)
and coefficient of variation (CV) for retapamulin after retrodialysis Subject Mean recovery (%) N SD (%) CV (%)
1 77.49 3 14.71 18.98
2 92.81 3 3.48 3.75
3 94.36 2 2.00 2.65
Overall 88.22 8 11.59 13.14
66
Figure 5-1. In vivo recovery of retapamulin determined by retrodialysis (mean±SD).
Figure 5-2. Skin concentrations (mean±SD) of retapamulin during the washout period.
The concentration at 1.75 h corresponds to the retrodialysis sample.
0
20
40
60
80
100
1 2 3Subject
%R
ecovery
0
1
2
3
4
5
6
7
8
9
1.75 2.25 2.75 3.25 3.75 4.25 4.75 5.25 5.75
Time (hours)
Co
nce
ntr
atio
n (
ng
/mL
)
Subject
000001
000002
000003
67
CHAPTER 6 IN VIVO PHARMACOKINETICS OF RETAPAMULIN
Objective
Since retapamulin is applied topically, systemic exposure is low and availability of
pharmacokinetic data is limited. Pharmacokinetic parameters for retapamulin have not
been established yet25; in vitro protein binding is 75-94%1. No information on unbound
concentrations at the target site or tissue distribution of retapamulin was available prior
to the start of the study.
The objective was to investigate the pharmacokinetics of retapamulin in plasma
and in skin in healthy Wistar rats.
Material and Methods
Antimicrobial Agents
Micronized Retapamulin (lot #WG0223980-140411001) was purchased from Ark
Pharm, Inc. Altabax™ (1% retapamulin ointment 15 g) was obtained from a local
pharmacy. The drug powder and the ointment were stored at room temperature and
protected from light.
Materials
Formic Acid (FA), Fisher #A119P-1
Acetic Acid, Fisher #A35-500
Acetonitrile (ACN), Fisher #A998-4
Ethanol USP (EtOH), Aaper #05A25GA
Methanol (MeOH), Fisher #A456-1
Isoflurane, Piramal Healthcare
Triple distilled water (TDW), in house, Pharmaceutics Department
Normal saline (0.9%), Ricca #2502970
Isopropanol (70%)
Chlorhexidine (2%)
Virkon disinfectant (1%)
Heparin 210 U/mg, Affymetrix #4229340
68
Equipment and Disposables
Eppendorf Research Pipettes, volume: 2-20 µL, 10-100 µL, 20-200 µL, 100-1000 µL
Eppendorf Research Plus Pipette, volume: 0.1-10 µL
Fisherbrand Pipet Tips
Mettler Toledo AB104 balance
Millipore nylon membrane filter type 0.2 µm
Fisherbrand microcentrifuge tubes, 0.5 mL amber vials
Fisherbrand microcentrifuge tubes, 1.5 mL amber vials
Corning 15 mL centrifuge tubes
1 mL BD Syringe, sterile
5 mL BD Luer-Lok syringe, non-sterile
BD 21g needle
BD 27g needle
BD Microtainer PST tubes with Li-Heparin
3M Surgical Clipper Kit
Delfin VapoMeter
Surgical marker
Millipore Centrifree
Sun Sri Autosampler Vial 12x32 mm, 300 µL, conical
Sun Sri 11 mm aluminum seals
Fisher Scientific Mini Vortexer
Harvard Apparatus Model 22 Multiple Syringe Pump
µdialysis 66 Linear Catheter
Millipore nylon membrane filter type 0.2 µm
69
Perkin Elmer Series 200 Pump
Perkin Elmer Series 200 Autosampler
AB Sciex API 4000 LC/MS/MS
Waters Atlantis T3 2.1x150 mm HPLC column (S/N013333145140)
Waters Atlantis T3 2.1x10 mm Guard Cartridge
Pyrex volumetric flasks, volume: 10 mL, 200 mL
Pyrex Media-lab bottles, 500 mL
Perkin Elmer Series 200 Pump
In Vivo Pharmacokinetic Study
A total of 15 male, pathogen-free Wistar rats, weighing between 280-310 g, were
randomly assigned to three treatment groups. Two groups received 1% retapamulin
ointment after topical administration on either intact or tape-stripped skin. The
administered dose was 0.1 mg/cm2 (approximately 0.525 mg retapamulin). The third
group received 5 mg/kg retapamulin after an IV bolus. The study was approved by the
IACUC and the protocol adhered to the “Guide for the Care and Use of Laboratory
Animals”1. A flow chart of study procedures is shown in Figure 5-5.
Anesthetization
On the day of the experiment, rats were anesthetized with an isoflurane
vaporizer. Isoflurane inhalation was performed as follows: the rat was placed in an
induction chamber under the chemical fume hood, which was supplied with an air-
isoflurane (4%) mixture at a flow rate of 2,000 mL/min. Loss of consciousness took 2-3
minutes, and surgical stage of anesthesia, with loss of reflexes and muscular relaxation,
was examined by pinching the tail and ears. Once under anesthesia, a mask was
placed onto the nose of the animal and the isoflurane concentration was decreased to
70
approximately 1.5%. Then, the animal was placed on a temperature-controlled heating
pad in a dorsal position, with the tail toward the investigator. Body temperature was
maintained at 37°C.
Microdialysis probe implantation
Two µdialysis 66 Linear Microdialysis Catheters were used and the inlet tube of
the probes were connected to a Harvard Apparatus 22 microinjection.
The probe insertion site (abdominal region of the rat) was clipped and disinfected
by swiping the area with 2% chlorhexidine and 70% isopropanol. For the tape-stripping
group, adhesive tapes were applied and pressed onto the skin, to remove the stratum
corneum before probe insertion. This procedure was repeated 20 times59,60. Probe
insertion site and drug absorption window (approximately 35x15 mm) was marked with
a surgical marker. An introducer needle was carefully inserted intradermally and the
outlet of the microdialysis probe was pushed through the needle end. Then, the probe
was held in place and the introducer needle was withdrawn carefully. The probe was
positioned in such a way that the membrane was within the marked area and probe
position was secured with tape.
Microdialysis probe stabilization
Two 5 mL syringes with 0.9% normal saline were connected with the probe’s
inlets. The pump was started, flow rate set to 5 µL/min, and the outlet tubing was
observed to see if perfusate was flowing. Flushing of the probes continued for another
five minutes in order to remove air bubbles from the system.
Flow rate was then lowered to 1.5 µL/min and the probes were perfused for 30
minutes, to equilibrate the system and allow the skin to recover from the insertion
trauma.
71
Retrodialysis
A 50 ng/mL retapamulin solution for in vivo microdialysis calibration using
retrodialysis61–64 was prepared on the study day. Briefly, 10µL of a 1 mg/mL primary
retapamulin stock solution were diluted with 990 µL of ethanol to yield a 10 µg/mL
secondary stock solution. Subsequently, 25 µL of the secondary stock solution were
mixed with 4,975 µL of sterile normal. The retrodialysis solution was dispensed in two 5
mL syringes. Drug samples were taken and the syringes were connected with the inlets
of the probes. Again, the pump was started at a flow rate set to 5 µL/min for five minutes
and then lowered to 1.5 µL/min. An equilibration period of 30 minutes was allowed,
followed by a 30 minutes sampling period of the dialysate to calculate microdialysis in
vivo recovery. Probes were disconnected and drug was sampled from each syringe
again.
Baseline sample collection
Syringes were changed and replaced with syringes containing normal saline.
After flushing for five minutes at a flow rate of 5 µL/min, the flow rate was changed back
to 1.5 µL/min and a 30 minutes washout sample was collected from both catheters. The
syringes and the flow rate were not changed for the remainder of the study.
Topical administration of ointment
After 30 minutes washout period and baseline sample collection, transepidermal
water loss (TEWL) was measured in triplicates and 1% retapamulin ointment was
applied on the abdominal skin at a dose of 0.1 mg/cm2 (approximately 0.525 mg
retapamulin). In the tape-stripped skin group ointment was wiped off 3 h after
application to capture the distribution and elimination phase.
72
IV bolus administration
Solution for IV bolus was fresh prepared on the study day. 10 mg of micronized
retapamulin were dissolved in 2 mL of 0.1% acetic acid in normal saline (approximate
pH=3.2) and filtered through a 0.22 µm Millipore filter. An IV bolus of 5 mg/kg was
injected via the lateral tail vein.
Microdialysis and blood sample collection
Microdialysis samples were collected every 30 minutes for 6 h and stored at -
80˚C until analysis.
Arterial blood (200 µL) was collected at pre-dose, 0.5, 1, 2, 3, 4, 5 and 6 h when
drug was administered topically and at pre-dose, 5, 15 and 30 minutes and 1, 2, 3, 4, 5
and 6 h for IV bolus administration. Lithium-Heparin tubes were used for blood
collection and the samples were centrifuged at 10,000 rpm for 12 minutes. The plasma
was transferred into microcentrifuge vials and stored at -80˚C.
Protein binding and Centrifree recovery
Plasma protein binding (PPB) in Wistar rats and humans was examined by the
ultrafiltration technique65. It is reported that plasma protein binding of retapamulin is not
concentration dependent1,25. A mass balance approach was used to calculate PPB and
recovery from the Centrifree devices66. A 10 µg/mL retapamulin solution was prepared
by mixing 10 µL primary stock with 990 µL saline. 30 µL of this solution was added to
1,170 µL of pooled plasma, vortexed and three 50 µL aliquots were immediately taken
out for measurement of initial concentrations (C1). The plasma-drug mix (250 ng/mL)
was incubated for 30 minutes at 37˚C. Top and bottom of the Centrifree device were
weighed before addition of plasma-drug mix and after ultrafiltration (10 min at 1,000 g)
to obtain the volume of retinate (V2) and ultrafiltrate (V3). Aliquots of 50 µL were
73
removed from the top (C2) and bottom (C3) of the Centrifree device. Experiments were
conducted in triplicates.
Protein precipitation of all samples was done prior to analysis with 100 µL of a
1:1 ACN:IS mixture and centrifugation. Analyte/IS response area after LC-MS/MS
analysis was used for PPB and recovery calculations. The percentage of protein binding
was calculated by:
𝑃𝑃𝐵% =(𝐶2−𝐶3)∗𝑉2
(𝐶2∗𝑉2+𝐶3∗𝑉3)∗ 100% (6-1)
Recovery in percent was calculated by:
𝑅% =(𝐶2∗𝑉2+𝐶3∗𝑉3)
(𝐶1∗𝑉1)∗ 100% (6-2)
Sample preparation and analysis
Samples were thawed at room temperature. Plasma proteins were removed
using Centrifree ultrafiltration devices to obtain free unbound drug67–69. Briefly, plasma
samples were incubated for 30 minutes at 37˚C in a water bath, then Centrifree devices
were loaded with 100 µL plasma and centrifuged at 1,000 g for 10 minutes. Free plasma
concentrations were corrected for ultrafiltration recovery.
For analysis with LC-MS/MS, 20 µL of dialysate and ultrafiltrate was spiked with
10 µL of IS. LC-MS/MS conditions were the same as specified in chapter 2. Calibration
standards, double blank, blank and QCs (5% of the number of samples analyzed or a
total of six, whichever was greater) were prepared on the day of analysis. Analytical
runs were accepted if more than 75% of the calibration standards were within ±15%
(±20% for LLOQ) and if more than 67% of the QCs, with at least 50% at each level,
were within ±15% of their nominal concentrations. In vivo microdialysis recovery R% for
each animal was calculated using equation 3-2, measured retapamulin skin
74
concentrations were divided by R% (see equation 3-3) and the mean free
concentrations of both probes used. Since samples were collected over a period of 30
minutes, the corresponding time point of a concentration was the mean of this time
interval (e.g. time point was 2.25 h for a collection interval from 2 to 2.5 h).
Data collection, analysis and plotting was performed using in Microsoft Excel
2013, R version 3.1.2, RStudio version 0.98.1087 and the ggplot2 package.
Results
Plasma Protein Binding and Recovery
Plasma Protein binding was higher in humans if compared to Wistar rats (90.8%
vs. 81.0%) and in accordance with literature reports1.Recovery form the Centrifree
devices were 88.6±4.5% (mean±SD) from human plasma and 93.9±7.5% (mean±SD)
from rat plasma.
Retapamulin Concentrations in Plasma and Skin
IV bolus
Five animals received an IV bolus of retapamulin via the tail vein. Dosing was 5
mg/kg, however, one animal (ID1) received 1 mg/kg due to dilution error and another
animal (ID4) received only approximately 32% of the total dose, because the needle
slipped out of the tail vein. Total administered retapamulin dose was ranging from 0.30-
1.64 mg. Distribution of retapamulin from plasma into peripheral compartments was
rapid and appeared to follow a three-compartmental disposition model (Figure 6-2).
Free plasma and free skin concentrations were in equilibrium after 3 hours.
Microdialysis probe recovery was 92.2±2.8% (mean±SD).
75
Topical application after tape-stripping
Five animals received Altabax™ topically after tape-stripping of the skin. Total
applied retapamulin dose was 0.60±0.04 mg (mean±SD). TEWL after tape-stripping
varied from 26.5-187 g*m-2*s-1 with a mean of 110.1±72.5 g*m-2*s-1.
Drug absorption into the skin seemed to be faster during the first 1.25 h and
slowed down afterwards (Figure 6-2). After ointment removal (3 h), drug concentrations
declined. Contrary to the observations from the IV bolus group, distribution and
elimination from the skin was slower and biphasic.
Free plasma concentrations were much lower after topical application if
compared to IV bolus. Probe recovery was 91.3±5.4% (mean±SD).
Topical application on intact skin
A total of four animals received Altabax™ topically on intact skin. Total
retapamulin dose was 0.56±0.06 mg (mean±SD) and was 6.8±0.8 g*m-2*s-1 (mean±SD).
Compared to the tape-stripped group, drug absorption into the skin was very slow and
delayed (Figure 6-3). Only three out of 32 analyzed plasma samples had quantifiable
drug concentrations (>0.5 ng/mL). Since the ointment was not removed from the skin,
no distribution and absorption phase was captured.
Summary
Retapamulin concentrations were determined in plasma and skin ISF of Wistar
rats. In vivo microdialysis recovery from animal skin was high and comparable to the
results from the in vitro and the clinical feasibility study. After IV administration,
retapamulin showed fast elimination and rapid distribution from plasma into peripheral
tissues. High variability in retapamulin skin concentrations was observed following
topical application of ointment on tape-stripped skin. Percutaneous drug absorption was
76
slightly delayed and maximum skin concentrations were achieved before the removal of
the ointment. Average maximum skin concentrations were also above the MIC (0.125-
0.25 µg/mL). Free plasma concentrations were quantifiable but low. When retapamulin
was applied on intact skin, percutaneous absorption was very slow and maximum
concentrations were observed at the end of the study. However, maximum skin
concentrations were very low and would most likely not elicit an antibacterial effect.
Additionally, systemic exposure was low too and only a few plasma samples were
quantifiable.
77
Figure 6-1. Plasma protein binding (mean±SD) in humans and rats.
0
10
20
30
40
50
60
70
80
90
100
Human Rat
Species
Me
an
PP
B (
%)
78
Figure 6-2. Unbound plasma and skin ISF concentration profiles of retapamulin after intravenous administration. In the upper panel concentrations are shown on a normal scale, while on the lower panel concentrations are displayed on a log-normal scale
79
Figure 6-3. Unbound plasma and skin ISF concentration profiles of retapamulin after
tape-stripping and topical application. The upper panel displays concentrations on normal scale, whereas the lower panel shows concentrations on a log-normal scale
80
Figure 6-4. Unbound skin ISF concentration profiles of retapamulin after topical
application on intact skin. Concentrations in the upper panel and lower panel are plotted on a normal scale and log-normal scale, respectively. Plasma concentrations were below the LOQ and therefore not shown.
81
Time (h) 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8
Saline
Retapamulin
Blood X X X X X X X X
RD Sample X
MD Sample X X X X X X X X X X X X X
Dosing X
Figure 6-5. Flowchart with time and events of the in vivo PK study.
82
CHAPTER 7 PHARMACOKINETIC AND PHARMACODYNAMIC ANALYSIS
Objective
The aim was to quantitatively describe the disposition and elimination of
retapamulin in plasma and skin using a non-compartmental and population
pharmacokinetic approach. Additionally, a semi-mechanistic pharmacodynamic model
was developed for the tested S. aureus strains and integrated with the PK model, to
guide development and help optimizing the pharmacotherapy of retapamulin. Lastly,
allometric scaling was used to predict the human exposure-response relationship.
Material and Methods
Non-compartmental Analysis
Non-compartmental analysis (NCA) was performed with Phoenix WinNonlin
version 6.4. Free plasma concentrations were adjusted based on the plasma protein
binding to obtain total plasma concentrations. The area-under-the-concentration curve
(AUC0-t) was calculated using the trapezoidal rule. AUC0-∞ was the sum of AUC0-t and
the extrapolated AUCt-∞, calculated by Clast/ke. Elimination rate constant ke was
estimated based on the best fit of concentration-time points in the terminal phase. In
addition, extrapolated concentration at time zero (C0), total clearance (CL), observed
maximal concentration (Cmax), terminal half-life (t1/2), mean residence time (MRT), time
at Cmax (Tmax), volume of distribution in steady-state (Vss) and volume of distribution in
the terminal phase (Vz) were calculated. AUCt-∞ and Cmax were also normalized for
dose. For topical application, apparent clearance (CL/F) and apparent volume of
distribution in the terminal phase (Vz/F) were estimated. The distribution between skin
and plasma was calculated by the ratio of free plasma AUC0-∞ (fAUCplasma) and skin ISF
83
AUC0-∞ (AUCISF) from each animal. Difference between plasma and skin PK parameters
was evaluated by one-way analysis of variance (ANOVA) at a significance level of
α=5%.
Population Pharmacokinetic Analysis
Population PK (PopPK) analysis was performed with the non-linear mixed effects
modeling software NONMEM version 7.3 and the integrated modeling and simulation
workbench Pirana version 2.9, PSN version 4.2.0 and Xpose version 4.570. Plots were
generated with R version 3.1.2, RStudio version 0.98.1087 and Xpose. Different
disposition models were tested, consisting of two and three compartment mammillary
models, with plasma as central compartment. Percutaneous absorption, with or without
lag-time, was investigated by testing zero-order absorption, single/parallel first-order
absorption, sequential/parallel/linked mixed zero-order and first-order absorption, transit
compartment and Weibull absorption models71–77. Interindividual variability was
assumed to be log-normal distributed, with a mean θ and variance ω2. Residual
unexplained variability was examined (additive, proportional and combined error
models). All models were parameterized as a set of ordinary differential equations
(ODE) using the ADVAN13 subroutine. PK parameters were estimated with the Monte-
Carlo importance sampling (IMP) method and optimized estimation options78,79. Model
selection was based on the Akaike information criterion (AIC)80, parameter estimation
precision, goodness-of-fit plots, ill conditioning81 and prediction corrected visual
predictive checks (pcVPC)82.
Semi-mechanistic Pharmacodynamic Model
PD model development was also performed in NONMEM 7.3. The ADVAN13
subroutine with natural log transformed data was used and PD parameter estimates
84
were obtained with the iterative two stage (ITS) method. A model with two bacterial
subpopulations, including susceptible and persistent cells, was evaluated48,54,83. Drug
effect was modeled as sigmoidal Emax model and delay in growth and/or delay of drug
onset were also investigated51,84. Model selection was based on AIC, goodness-of-fit
plots and VPCs.
Allometric Scaling
To predict human concentration time-profiles in plasma and skin, the animal
profiles were normalized. Time was normalized with the MRT and concentrations with
dose/Vss85. Micro rate constants obtained from the PopPK model were converted into
hybrid rate constants. Estimation of human clearance was based on scaling from one
species86 and human Vss was predicted the Øie-Tozer equation87. Human equivalent
dose was calculated based on body surface area88. Predicted human hybrid constants
were then back transformed into micro rate constants and retapamulin concentration
profiles in human skin were simulated using a typical subject. The simulated
concentration profiles were then linked with the PD models of the MSSA and MRSA
strains to predict the time-effect course of retapamulin in human skin.
Results
Non-compartmental Analysis
The parameter estimates from the non-compartmental analysis after IV bolus and
topical application are summarized in Table 7-1, Table 7-2 and Table 7-3, respectively.
Half-life of retapamulin after IV bolus administration was comparable in plasma
and skin (2.2 vs 2.0 h, p>0.05). Dose normalized fAUC0-∞ was larger in plasma than in
skin ISF (126.0 vs 69.4 ng/mL*h, p<0.05) and the free plasma fraction distributing into
the skin ISF was 57%. The dose-normalized maximum skin concentration was
85
approximately 25% of the free observed plasma concentration. MRT in the skin was
longer but did not differ if compared to plasma (2.8 vs 1.9 h, p>0.05). Clearance of
retapamulin from the plasma was fast and exceeded total hepatic blood flow (55
mL/min/kg)89–91, suggesting extrahepatic clearance mechanisms. Terminal volume of
distribution of retapamulin (Vz 15,470 mL/kg) was greater than the total body water of a
rat (670 mL/kg)90 indicating extensive distribution into peripheral tissues.
After topical application of Altabax™ ointment on tape-stripped skin, retapamulin
exposure was significantly greater in skin ISF compared to plasma (AUC0-∞ 1,049 vs
20.5 ng/mL*h, p<0.05) and distribution from skin into plasma was 3.9%. Maximum
unbound drug concentrations in skin ISF were 303.5 ng/mL observed at 2.5 h and in
plasma 4.2 ng/mL observed at 2.2 h, respectively. Half-life in plasma was longer than in
skin (2.7 vs 1.3 h) but not different if compared to t1/2 after IV bolus administration (2.7
vs 2.2 h, p>0.05). MRT resembled the mean residence time after intravenous
administration and duration of ointment application.
For topical application on intact skin, only Cmax, AUC0-t and Tmax were
determined. Maximum concentrations in skin ISF were achieved at 5.6 h and were 8.9
ng/mL. AUC0-t was 15.9 ng/mL*h and only 1.7% of the tape-stripped skin exposure.
Population Pharmacokinetic Analysis
Plasma concentrations were adjusted for protein binding and compiled with
microdialysis data. IV and topical route of administration (tape-stripped group only) was
modeled simultaneously. The final model comprised a two-compartment body model,
with elimination from the central compartment and zero-order percutaneous absorption
with lag time for topical application (Figure 7-1). Residual variability was explained by a
combined error model. A distribution factor DF was added to account for the difference
86
between free plasma and free skin ISF concentrations. The residual unexplained
variability was
The ordinary differential equations describing the change of drug amounts over
time (t) in the plasma [A(1)] and skin [A(2)] compartments after IV administration were
described as follows:
𝑑𝐴(1)
𝑑𝑡= −(𝑘𝑒 + 𝑘12) ∗ 𝐴(1) + 𝑘21 ∗ 𝐴(2) (7-1)
𝑑𝐴(2)
𝑑𝑡= 𝑘12 ∗ 𝐴(1) − 𝑘21 ∗ 𝐴(2) (7-2)
where ke is the elimination rate constant and k12 and k21 are the transfer rate
constants.
Concentrations in plasma and skin were obtained by scaling drug amounts with
volumes. Volume of distribution in the central compartment Vc was estimated and
volume of distribution in the skin compartment Vs was parameterized as k12/k21*Vc, since
k12*Vc = k21* Vs at steady state. Because concentrations were measured in ng/mL and
dose was given in mg, a conversion factor of 1000 was included. Hence, concentrations
in plasma and skin were:
𝐶𝑝𝑙𝑎𝑠𝑚𝑎 =𝐴(1)
𝑉𝑐∗1000 (7-3)
𝐶𝑠𝑘𝑖𝑛 =𝐴(2)∗𝑘21∗𝐷𝐹
𝑘12∗𝑉𝑐∗1000 (7-4)
The best model fit for topical application was obtained using a zero-order
absorption process with lag time. k0 was the zero-order drug input constant, duration
was fixed to three hours and the change of amount over time in skin was described as:
𝑑𝐴(2)
𝑑𝑡= 𝑘0 + 𝑘12 ∗ 𝐴(1) − 𝑘21 ∗ 𝐴(2) (7-5)
87
Concentrations in plasma after topical application were modeled as described in
equation 7-3. For skin concentrations, a scaling factor S was included for the skin
volume of distribution (equation 7-6). The skin volume where the microdialysis probes
were placed, and ISF concentrations measured, only reflected a fraction of the total
skin, therefore the skin volume of distribution differs from that of the intravenous route of
administration.
𝐶𝑠𝑘𝑖𝑛 =𝐴(2)∗𝑘21∗𝐷𝐹
𝑘12∗𝑆∗𝑉𝑐∗1000 (7-6)
Individual and population predictions described the observed plasma data
adequately (Figure 7-2). IDs 6 to 10 received retapamulin ointment and deviation from
the individual predictions were greater. However, it should be noted that the
measurements were at the lower end of the linearity range of the assay and that they
also mirror the greater variability observed in the skin.
Compared to IV bolus, variability of skin concentrations after topical application
was large (Figure 7-3) with greater than ten-fold difference in maximum concentrations.
TEWL was tested as covariate to account for variability, but was not significant.
Prediction-corrected VPCs are displayed in Figure 7-4 (IV bolus), Figure 7-5
(topical application) and basic goodness-of-fit plots are depicted in Figure 7-6,
respectively. Although, variability was inflated by the skin observations from the group
treated with ointment, the overall fit was adequate and the model predicted the
observed data reasonably.
The population PK parameter estimates are summarized in Table 7-4. All
estimates had reasonable precision. Higher inter-individual variability was observed for
the scaling factor S and bioavailability F. Clearance calculated as CL = ke*Vc was
88
greater than the CL obtained from NCA (1.96 vs 1.57 L/h), while Vss, calculated as Vc +
Vp, was virtually identical (2.7 vs 2.7 L). The transfer rate constants indicated a fast
distribution from the central to the skin compartment. The distribution factor DF was
0.68 and slightly larger if compared with NCA (0.57). Bioavailability after topical
application was 23.4%.
Semi-mechanistic Pharmacodynamic Model
The PD final model included a susceptible and persistent bacterial
subpopulation. The susceptible subpopulation S included a first-order rate constant for
bacterial multiplication kg and a first-order rate for natural death kd. The susceptible
subpopulation was also able to switch into a resting state R. While in the resting state,
bacteria was not able to replicate itself, but also was not susceptible to the antimicrobial
effect of retapamulin. Figure 7-7 illustrates the semi-mechanistic model. Since growth
and death rate constants could not be estimated separately, knet, a composite of growth
and death rate constant, was used (knet = kg – kd)47. Bacterial growth was modeled by
applying a logistic growth function92–94. Delay in bacterial growth and onset of drug was
also included. The differential equations for the change in the number of susceptible
and resting bacteria over time was described as follows:
𝑑𝑆
𝑑𝑡= [𝑘𝑛𝑒𝑡 ∗ (1 − 𝑒−𝑑𝑔𝑠∗𝑡) ∗ (1 −
𝑆+𝑅
𝑁𝑚𝑎𝑥) − 𝐸𝑓𝑓 ∗ (1 − 𝑒−𝑑𝑘𝑠∗𝑡)] ∗ 𝑆
−𝑘𝑆𝑅 ∗ 𝑆 + 𝑘𝑅𝑆 ∗ 𝑅 (7-7)
𝑑𝑅
𝑑𝑡= 𝑘𝑆𝑅 ∗ 𝑆 − 𝑘𝑅𝑆 ∗ 𝑅 (7-8)
Where ksr and krs are the transfer rate constants, Nmax is the maximum carrying
capacity, Eff is the drug effect and dgs and dks are delay constants for growth and drug
onset. The antimicrobial effect was incorporated as sigmoidal Emax model, with
89
maximum drug effect Emax, retapamulin concentration C, drug concentration EC50 where
the half-maximum antimicrobial effect is achieved and the Hill factor h, which describes
the steepness of the concentration-response curve.
𝐸𝑓𝑓 =𝐸𝑚𝑎𝑥∗𝐶ℎ
𝐸𝐶50+𝐶ℎ (7-9)
A log-additive error model was used for both MSSA and MRSA PD models.
Parameter estimates were reasonable and are summarized in Table 7-5. Goodness-of-
fit plots and VPCs, stratified for MICs, are displayed in Figure 7-8 and Figure 7-9 for
MSSA and in Figure 7-10 and Figure 7-11 for MRSA. Both models described the
bacterial counts quite well. Retapamulin appeared to have a higher maximum effect
against the MRSA ATCC4330 strain when compared to the clinical MSSA isolate (4.8
vs 2.43 h-1). The EC50 was also slightly lower for the MRSA strain (0.147 vs 0.19 mg/L),
yet the concentration-response relationship was steeper against the MSSA isolate (1.35
vs 0.678).
Allometric Scaling
Micro rate constants were converted into hybrid constants A, B, α and β. The
equations were:
𝛼 + 𝛽 = 𝑘𝑒 + 𝑘12 + 𝑘21 (7-10)
𝛼 ∗ 𝛽 = 𝑘𝑒 ∗ 𝑘12 (7-11)
𝛼, 𝛽 =(𝛼+𝛽)±√𝑏(𝛼+𝛽)2−4𝛼∗𝛽
2 (7-12)
𝐴 =𝐷𝑜𝑠𝑒∗(𝛼−𝑘21)
𝑉𝑐∗(𝛼−𝛽) (7-13)
𝐵 =𝐷𝑜𝑠𝑒∗(𝑘21−𝛽)
𝑉𝑐∗(𝛼−𝛽) (7-14)
90
The converted hybrid constants were A=151, B=52.3, α=7.307 and β=0.6026.
Concentration profiles from the animal was normalized according to the equation:
𝐶′ =𝐴
𝐶𝑠𝑠∗ 𝑒(−𝛼∗𝑀𝑅𝑇∗𝑡) +
𝐵
𝐶𝑠𝑠∗ 𝑒(−𝛽∗𝑀𝑅𝑇∗𝑡) (7-15)
To obtain human hybrid constants following equations were used:
𝐴𝑚𝑎𝑛 =𝐶𝑠𝑠,𝑚𝑎𝑛
𝐶𝑠𝑠,𝑎𝑛𝑖𝑚𝑎𝑙∗ 𝐴𝑎𝑛𝑖𝑚𝑎𝑙 (7-16)
𝐵𝑚𝑎𝑛 =𝐶𝑠𝑠,𝑚𝑎𝑛
𝐶𝑠𝑠,𝑎𝑛𝑖𝑚𝑎𝑙∗ 𝐵𝑎𝑛𝑖𝑚𝑎𝑙 (7-17)
𝛼𝑚𝑎𝑛 =𝑀𝑅𝑇𝑎𝑛𝑖𝑚𝑎𝑙
𝑀𝑅𝑇𝑚𝑎𝑛∗ 𝛼𝑎𝑛𝑖𝑚𝑎𝑙 (7-18)
𝛽𝑚𝑎𝑛 =𝑀𝑅𝑇𝑎𝑛𝑖𝑚𝑎𝑙
𝑀𝑅𝑇𝑚𝑎𝑛∗ 𝛽𝑎𝑛𝑖𝑚𝑎𝑙 (7-19)
Human CL and Vss were calculated using scaling form one species and the Øie-
Tozer equation:
𝐶𝐿𝑚𝑎𝑛/𝑘𝑔 = 0.152 ∗ 𝐶𝐿𝑎𝑛𝑖𝑚𝑎𝑙/𝑘𝑔 (7-20)
𝑉𝑠𝑠 = 𝑉𝑝 + (𝑓𝑢𝑝 + 𝑉𝑒) + [(1 − 𝑓𝑢𝑝) ∗ 𝑅𝐸
𝐼
∗ 𝑉𝑃] + 𝑉𝑟 ∗ 𝑓𝑢𝑝/𝑓𝑢𝑡,𝑚𝑎𝑛 (7-21)
where fup is the fraction unbound in plasma, fut is the fraction unbound in tissues,
and RE/I is the extravascular/intravascular ratio of binding proteins and Vp, Ve, and Vr are
the volumes of plasma, extracellular fluid, and remainder fluid.
Equation 7-21 was rearranged to express fut in terms of Vss and fup95:
𝑓𝑢𝑡 =𝑉𝑟∗𝑓𝑢𝑝
[𝑉𝑠𝑠−𝑉𝑝−(𝑓𝑢𝑝∗𝑉𝑒)]−[(1−𝑓𝑢𝑝)∗𝑅𝐸𝐼
∗𝑉𝑝]
(7-22)
Then, fut was estimated using 9.267 L/kg, 0.364 L/kg, 0.0313 L/kg and 0.265
L/kg for animal Vss, Vr, Vp and Ve87,95,96, respectively. Ratio of binding proteins RE/I was
1.495 and fraction unbound fu in plasma was 0.19. Estimated fut was 0.0076. Human Vss
was predicted (5.14 L/kg) with Vr, Vp and Ve at 0.38 L/kg, 0.0436 L/kg and 0.151 L/kg.
91
RE/I and fut were assumed to be equal to the animal values and fu in plasma was 0.1.
The human clearance estimate was 0.99 L/kg. Human Css and MRT were then
calculated using the equations:
𝐶𝑠𝑠,𝑚𝑎𝑛 = 𝐷𝑜𝑠𝑒/𝑉𝑠𝑠 (7-23)
𝑀𝑅𝑇𝑚𝑎𝑛 = 𝑉𝑠𝑠/𝐶𝐿 (7-24)
Human equivalent dose (HED) was based on body surface area and was
calculated from the following formula88:
𝐻𝐸𝐷(𝑚𝑔 𝑘𝑔⁄ ) = 𝑎𝑛𝑖𝑚𝑎𝑙 𝑑𝑜𝑠𝑒(𝑚𝑔 𝑘𝑔⁄ ) ∗𝑘𝑚𝑎𝑛𝑖𝑚𝑎𝑙
𝑘𝑚𝑚𝑎𝑛 (7-25)
where the conversion factors (km) from mg/kg to mg/m2 for rat and human were
6 and 37, respectively. HED, Css and MRT for a typical person weighing 70 kg were 7.9
mg, 22.23 ng/mL and 5.15 h. Hybrid constants for human, estimated with equations 7-
16-19, were A=43, B=14.9, α=1.95 and β=0.16. Back conversion into micro rate
constants and volume of distribution was performed with equations:
𝑘21 =𝐴∗𝛽+𝐵∗𝛼
𝐴+𝐵 (7-26)
𝑘10 =𝛽∗𝛼
𝑘21 (7-27)
𝑘12 = 𝛼 + 𝛽 − 𝑘21 − 𝑘10 (7-28)
𝑉𝑐 =𝐷𝑜𝑠𝑒
𝐴+𝐵 (7-29)
And ke, k21, k12 and Vc were 0.503 h-1, 0.621 h-1, 0.987 h-1 and 137.9 L. Those
constants were used to simulate skin ISF concentrations in humans after topical
application of 10 mg of retapamulin ointment on 100 cm2 (0.1 mg/cm2), twice a day.
Absorption rate constant k0, distribution factor DF and bioavailability were assumed to
be equal to the estimates obtained from rats. The skin volume proportionality factor S
92
was approximated with regards to ointment application area, body surface area (BSA)
and animal scaling factor S. A BSA of 1.73m2 for humans was assumed and animal
BSA was calculated with Meeh’s formula97:
𝐵𝑆𝐴 = 𝑘 ∗ 𝑊2/3 (7-30)
where Meeh’s constant k was 9.8398 and the weight W was 300 g.
Four different scenarios, where ointment stayed on the skin for 3, 4, 6 and 12 h
were simulated. The skin PK profiles were then used to simulate the time course of the
drug against MSSA and MRSA. PK and PD profiles are shown in Figure 7-12. The
antimicrobial effect seemed to be time-dependent with only slight differences between
MSSA and MRSA. Increasing the duration from 3 to 4 hours inhibited bacterial growth
and reduced the bacterial burden. Longer ointment exposure led to further antimicrobial
clearance. In spite of achieving higher steady-state concentrations, the difference of
antibacterial efficacy after 12 h exposure was marginal compared to 6 h exposure.
Summary
Non-compartmental analysis of retapamulin revealed fast plasma clearance and
extensive tissue distribution. The fraction of unbound retapamulin distributing from
plasma into the skin was approximately 57%. A simultaneous population
pharmacokinetic model for IV and topical administration was developed. The change
over time of retapamulin plasma and skin concentrations were best described by a two
compartment body model. Percutaneous absorption followed zero-order kinetics with
lag time. The bacterial system consisted of a susceptible and persistent bacterial
subpopulation with delayed growth. The antimicrobial drug effect was included as a
sigmoidal Emax model with a delayed onset. Concentration and time normalization of the
animal pharmacokinetic data was used to predict plasma and skin concentrations in
93
humans. Clearance was estimated using a one species approach and volume of
distribution calculations were based on physiological parameters from rats and humans.
Simulations of the antibacterial effect of retapamulin following topical application
displayed only minor differences between the tested MSSA and MRSA strains.
94
Table 7-1. Non-compartmental pharmacokinetic analysis for retapamulin after IV bolus administration
Parameters Total Plasma Free Plasma SkinISFa
Mean SD CV% Mean SD CV% Mean SD CV% AUC0-t (ng/mL*h) 635.8 359.9 56.6 120.8 68.4 56.6 65.4 44.7 68.3 AUC0-∞/D (ng/mL/mg*h)
663.1 141.2 21.3 126.0 26.8 21.3 69.4* 8.7 12.5
AUC0-∞ (ng/mL*h) 687.2 369.2 53.7 130.6 70.1 53.7 75.8 44.0 58.1 C0 (ng/mL) 970.2 586.0 60.4 184.3 111.3 60.4 ND ND ND CL (mL/h) 1,569 365.0 23.2 ND ND ND ND ND ND Cmax (ng/mL) 740.6 440.6 59.5 140.7 83.7 59.5 39.3* 30.2 76.9 Cmax/D (ng/mL/mg)
677.5 104.0 15.3 128.7 19.8 15.3 31.5* 12.2 38.6
t1/2 (h) 2.2 1.2 53.4 ND ND ND 2.0 1.0 48.3 MRT (h) 1.9 1.1 57.3 ND ND ND 2.8 1.0 36.5 Tmax (h) 0.1 0.0 0.0 ND ND ND 0.4‡ 0.2 63.9 Vss (mL) 2,780 1,099 39.5 ND ND ND ND ND ND Vz (mL) 4,641 1,675 36.1 ND ND ND ND ND ND AUCISF/fAUCplasma ND ND ND ND ND ND 0.57 0.13 22.2
ND not determined, SD standard deviation, CV coefficient of variation; a statistical difference determined by one-way ANOVA, * p<0.05 compared to free plasma, ‡ p<0.05 compared to total plasma
Table 7-2. Non-compartmental pharmacokinetic analysis for retapamulin after topical
application on tape-stripped skin Parameters Total Plasma Free Plasma SkinISF
a
Mean SD CV% Mean SD CV% Mean SD CV% AUC0-t (ng/mL*h) 77.9 32.4 41.5 14.8 6.2 41.5 944.3* 616.1 65.3
AUC0-∞/D (ng/mL/mg*h) 182.8 97.8 53.5 34.7 18.6 53.5 1,793* 1,202 67.1
AUC0-∞ (ng/mL*h) 108.0 53.3 49.4 20.5 10.1 49.4 1,049* 682.5 65.0
CL/F (mL/h) 7,255 4,836 66.7 ND ND ND ND ND ND
Cmax (ng/mL) 21.9 8.9 40.8 4.2 1.7 40.8 303.5* 208.3 68.6
Cmax/D (ng/mL/mg) 37.1 16.9 45.5 7.1 3.2 45.5 514.0* 350.9 68.3
t1/2 (h) 2.7 0.9 33.1 ND ND ND 1.3‡ 0.4 33.5
MRT (h) 4.8 1.0 20.3 ND ND ND 3.3‡ 0.4 11.5
Tmax (h) 2.2 0.8 38.0 ND ND ND 2.5 0.8 31.0
Vz (mL) 25,392 13,591 53.5 ND ND ND ND ND ND
fAUCplasma/AUCISF ND ND ND 0.039 0.043 109.5 ND ND ND
ND not determined, SD standard deviation, CV coefficient of variation; a statistical difference determined by one-way ANOVA, * p<0.05 compared to free plasma, ‡ p<0.05 compared to total plasma
95
Table 7-3. Non-compartmental pharmacokinetic analysis for retapamulin after topical application on intact skin
Parameters SkinISF
Mean SD CV% AUC0-t (ng/mL*h) 15.9 5.8 36.7 AUC0-∞/D (ng/mL/mg*h) ND ND ND AUC0-∞ (ng/mL*h) ND ND ND CL/F (mL/h) ND ND ND Cmax (ng/mL) 8.9 6.1 68.4 Cmax/D (ng/mL/mg) 16.5 12.0 72.5 t1/2 (h) ND ND ND MRT (h) ND ND ND Tmax (h) 5.6 0.3 4.4 Vz (mL) ND ND ND fAUCplasma/AUCISF ND ND ND
ND not determined, SD standard deviation, CV coefficient of variation
Table 7-4. Population pharmacokinetic parameter estimates
Parameter Estimate RSE% Inter-individual Variability RSE%
Ke (h-1) 1.89 16 16.3 32 Vc (L) 1.04 15 NA NA K12 (h-1) 3.69 28 15.1 47 K21 (h-1) 2.33 15 19.8 43 DF 0.675 11 22 37 S 0.018 48 100.5 32 F 0.234 32 73.3 35 tlag (h) 0.183 6 NA NA Prop. Error (%) 19.5 8 NA NA Add. Error (ng/mL) 0.514 15 NA NA
NA not applicable, RSE residual standard error
96
Table 7-5. Parameter estimates for the MSSA and MRSA PD model
MSSA MRSA
Parameter Mean RSE Mean RSE knet (h-1) 1.85 31.9% 3.09 37.5% Nmax (CFU/mL) 2.0x109 0% 1.1x109 0% Emax (h-1) 2.43 32.3% 4.8 40.4% EC50 (mg/L) 0.19 24.5% 0.147 25% h 1.35 33.7% 0.678 22.7% ksr (h-1) 0.04 49.8% 0.034 22.5% krs (h-1) 0.189 18.5% 0.157 9.1% dgs (h-1) 0.432 44.9% 0.289 53.6% dks (h-1) 0.33 29.8% 0.231 45.5% Interexperimental variability h (%) 12 70.5% 17 68.8% Residual Variability Prop. error (%) 43.6 11.3% 48.8 4.6%
Figure 7-1. Scheme of the final population pharmacokinetic model. Central
compartment refers to plasma. ke is the elimination rate constant and k12 and k21 denote the transfer rate constants from plasma to skin and vice versa. k0 is the zero-order percutaneous absorption rate constant with lag time Tlag.
97
Figure 7-2. Individual unbound concentration profiles in plasma. The upper panel refers
to concentration profiles after IV bolus, whereas the lower panel denotes concentration profiles after ointment application. Grey circles display observed data, red solid lines are individual predictions and blue dotted lines represent population predictions.
98
Figure 7-3. Individual unbound concentration profiles in skin. Upper panel presents IV
bolus concentration profiles after IV bolus and lower panel refers to concentration profiles after topical application. Grey circles are observed data, red solid lines display individual predictions and blue dotted lines show population predictions.
99
Figure 7-4. Prediction-corrected VPCs for IV bolus administration. The open circles
present observed data. The grey shaded area displays the 90% model prediction interval with the solid black line as median.
Figure 7-5. Prediction-corrected VPCs for topical route of administration. Open circles
display observed data, while the grey shaded area presents the 90% model prediction interval.
100
Figure 7-6. Basic goodness-of-fit plots. On the upper panels, the black line denotes the
line of unity, while on the lower residual plots, the black line displays the mean zero and the dashed lines ±1.96 standard deviations. Red lines indicate trend lines.
Figure 7-7. Semi-mechanistic PD model for retapamulin against S. aureus.
101
Figure 7-8. Basic goodness-of-fit plots from the MSSA PD model. Observed and
predicted concentrations are displayed on natural log scales.
102
Figure 7-9. VPCs for the MSSA PD model stratified for MICs. Open circles are
observations and grey shaded area the 90% prediction interval.
103
Figure 7-10. Basic goodness-of-fit plots from the MRSA PD model. Observed and
predicted concentrations are displayed on natural log scales.
104
Figure 7-11. VPCs for the MRSA PD model stratified for MICs. Open circles are
observations and grey shaded area the 90% prediction interval.
105
Figure 7-12. Simulated human PK and PD profiles for retapamulin.
106
CHAPTER 8 DISCUSSION AND CONCLUSION
Retapamulin is the first drug from the pleuromutilin class which is approved for
clinical use. It is indicated to treat impetigo and uncomplicated superficial skin infections
caused by S. aureus and S. pyogenes. Even though superficial skin infections heal
spontaneously, treatment can help prevent disease spread and reduce the risk of
developing serious complications99–101. Its unique mechanism of action makes
retapamulin a valuable treatment option against pathogens which developed resistance
against mupirocin and fusidic acid31.
Usually, plasma concentrations are used as a surrogate for concentrations of
antimicrobials at the target site. The PK/PD index, derived from these plasma
concentrations, is then used to guide dosing recommendations and evaluate the
antimicrobial activity. For topical antibiotic drugs, however, systemic exposure is low
and the target site is the skin. Therefore, it is pivotal to measure drug concentrations at
the site of infection. Tissue samples can be harvested and concentrations can be
determined by homogenizing or lysing the tissue102. As a result, total tissue
concentrations are measured rather than active unbound concentrations at the site of
infection103–105. Therefore, microdialysis was used to determine the unbound
pharmacologically active retapamulin concentrations. Since there is a constant flow of
perfusate, a true equilibrium between the microdialysis probe and the surrounding
tissue cannot be achieved. The recovery has to be determined, which is dependent on
flow rate, membrane surface area, temperature, physicochemical characteristics of the
investigated drug, perfusion medium and probe membrane and tubing material. These
influencing factors were investigated in vitro and helped to determine the recovery and
107
optimize the microdialysis set up. As in vivo recovery was measured by retrodialysis
(drug loss) but tissue concentrations were measured by extraction efficiency (drug
gain), it was crucial to investigate if there were any differences between the two
methods. Non-specific binding of highly lipophilic drugs on the tubing or membrane
makes quantification difficult and could lead to underestimation of concentrations.
Furthermore, it was important to examine whether there was a concentration-dependent
recovery relationship or not. Overall, the in vitro recovery of retapamulin in saline, at a
flow rate of 1.5 µL/min, was high for both extraction efficiency (90.1%) and retrodialysis
(96.0%) method with no significant differences between the methods no concentration-
dependent recovery.
The clinical feasibility study also confirmed that retapamulin freely crosses the
microdialysis membrane. Overall in vivo drug recovery was 88.22±11.59% and the male
subjects had higher recoveries than the female subject. Retapamulin tissue
concentrations at the end of the 4 hour washout period were 0.39 and 0.27 ng/mL for
the male subjects and 0.99 ng/mL for the female subject. Although the sample size was
too small to draw an inference, the differences in recovery and washout could be due to
differences in body fat composition and blood flow. Retapamulin may retain longer in
adipose tissue due to its lipophilic properties and its extensive tissue distribution.
Increased blood flow can also enhance systemic distribution and elimination from the
skin35,106. Clough et al.107 also reported that changes in blood flow altered analyte
recovery but left drug loss unaffected. In summary, retapamulin is dialyzable in human
skin and a 4 hour washout period may be sufficient.
108
In vivo recovery of retapamulin in Wistar rats was comparable to that in humans.
Following IV administration, retapamulin was rapidly eliminated and distributed into the
ISF of the skin, with a distribution factor of 0.57 (AUCISF/fAUCplasma). Plasma half-life,
determined by NCA, was 2.2 h and higher than the reported half-life of 1 h in rats and
monkeys1. Total plasma clearance of retapamulin exceeded the hepatic blood flow of
rats (55 mL/min/kg), hence extrahepatic clearance may play a role in drug elimination.
Retapamulin PK after topical application was examined on intact and tape-stripped skin.
After application of retapamulin on intact skin, percutaneous absorption was very slow.
The outermost skin layer, the stratum corneum (SC), acts as a barrier and provides the
rate-limiting step of drug penetration into the skin. It is composed of corneocytes, fatty
acids, cholesterol and ceramides108. In order to permeate through skin, drugs need to
partition into the lipophilic SC and subsequently, as they permeate further, partition into
the hydrophilic epidermis and dermis109. Due to its lipophilic properties (logP 5)110
retapamulin should partition well into the SC. As a result, retapamulin may form a depot
in the SC, leading to sustained release kinetics and very low dermal concentrations. It is
important to mention that the measured skin Cmax after application on intact skin was
more than 16-fold below the lowest observed MIC. On the other hand, maximum
retapamulin concentrations after application on tape-stripped skin were above the MIC.
Skin infections could impair or even disrupt the skin barrier and lead to an increased
TEWL111,112. Simulating perturbed skin is commonly done by the tape-stripping
method113–116. TEWL increased more than 15-fold after SC removal and variability was
high. Likewise, dermal drug concentrations varied but the average retapamulin
exposure was 59-fold greater compared to intact skin. Although correlation between
109
TEWL and percutaneous absorption has been shown,117,118,119, we did not find such a
relationship. Probe depth could also influence skin concentration measurements120,121,
but not all studies show a correlation122–124. We did not measure probe depth with
ultrasound and thus could not investigate a probe depth-skin concentration relationship.
Plasma concentrations were quantifiable for the tape-stripped group and variability was
not as pronounced as the corresponding skin concentrations. This may support the
hypothesis that probe depth matters in dermal microdialysis. If we suppose that
percutaneous absorption was significantly different between the tested animals, than it
should be also reflected in the systemic exposure.
The simultaneous two-compartment PK model was the most stable model. It
should be mentioned that when IV data was modeled alone, without the topical route of
administration, a three-compartment PK model had a lower AIC and described the data
better. However, for the simultaneous approach, a three-compartment model was over-
parameterized and was also not supported by the data following topical application. Our
main goal was to describe and evaluate the time-course of retapamulin in skin after
ointment application. Following model parsimony, we wanted to explain drug disposition
and elimination with as few variables as possible. Because drug was absorbed from the
ointment at a constant rate, and the skin was under sink conditions, a zero-order
absorption process was selected. Zero-order percutaneous absorption has also been
described in other publications125–127. The remaining amount of drug in the ointment,
however, was not determined and therefore only the apparent zero-order rate constant
k0 was obtained.
110
The PD model consisted of a susceptible and persistent bacterial subpopulation
and a logistic growth function. Another way to model self-limiting bacterial growth is to
use a nonlinear function128. A growth delay was also included into the PD model using
an empirical first-order growth delay constant. Different approaches could also describe
the growth delay. For instance, a prebacterial lag compartment, where bacteria
transfers into proliferating, susceptible stage could have been used129,130. Similarly to
the delay in growth, the onset of antimicrobial effect was implemented, but delay of
effect by introducing an effect compartment or by depletion of cell wall constituents have
also been described129,131. Transfer rate constants were used to model the transition
between susceptible and persistent bacterial population. Although this approach was
described in other papers83,132,133, Nielsen et al.48 assumed that the transfer back from
persistent to susceptible stage was negligible.
The MICs indicated activity of retapamulin against both clinical MSSA isolate and
MRSA ATCC43300 strain. The shortcomings of the MIC, i.e. limited information on drug
activity kinetics, two-fold variability and inability to show presence of persistent/resistant
bacteria, warranted the conduct of time-kill curve experiments. Static time-kill curves,
however, do not mimic the in vivo situation where drug concentrations constantly
change over time. As a consequence, dynamic time-kill curves could provide more
meaningful information. Nevertheless, the performed static time-kill curve experiments
confirmed the MIC findings and activity of retapamulin against the tested MRSA strain
was akin to MSSA. In vitro MRSA activity has also been shown in other studies134,135.
Methicillin-resistance of S. aureus is mediated by the acquisition of the
extrachromosomal gene mecA, which encodes penicillin-binding protein 2a
111
(PBP2a)136,137. Beta-lactam antibiotics, such as methicillin, have lower affinity to PBP2a
and as a result, cannot inhibit the transpeptidation reaction and bacterial cell wall
synthesis. Because retapamulin binds to the 50S ribosomal subunit and inhibits protein
synthesis it may not be surprising that it exhibits MRSA activity.
The prediction of human skin ISF concentrations was done by the Css-mean
residence method. Other approaches are the species-invariant time method138 or
physiologically-based pharmacokinetic modeling. The Css-MRT method normalizes
plasma concentration profiles between species and back-transform them using Css and
MRT, which are estimated from Vss and CL, to predict human plasma profiles. The
original method uses rat and dog data to estimate human Vss and CL. Since we only
had data from one species, different Vss87 and CL86 estimation methods were used and
results may deviate from the original method. Usually, simple allometry is used to
predict clearance and volume of distribution. It assumes similar relationships of anatomy
and physiological functions between species. It is simple, widely used and applicable for
compounds with high hepatic clearance, but requires data from multiple species139. CL
prediction performance for biliarily excreted drugs, however, was poor140,141. Prediction
of clearance from one species is applicable for hepatically metabolized compounds and
requires less data, but neglects interspecies differences in metabolism and protein
binding139. Regarding the prediction of volume of distribution, the Øie-Tozer equation
was more accurate compared to simple allometry142, but may be inappropriate for drugs
with nonlinear or complex PK143. The equation also assumes distribution which is driven
by nonspecific binding, rapid equilibrium between blood and tissue, no active transport
and nonsaturating distributional processes144. Drugs with a Vss < 0.6L/kg and logP less
112
than 0 did not obey the Øie-Tozer equation144. Because of retapamulin’s lipophilicity and
high volume of distribution, it was thought to be not a substrate of efflux transporters
and thus, Vss predictions may be reasonable.
Prediction of percutaneous absorption was assumed to be similar between rats
and humans. Relative to human skin, rat skin is observed to be two to five time more
permeable145. An in vitro study146 found no difference in rat and human skin permeation
of salicylic acid. Conversely, Benfeldt et al.117,123,147 reported a 53-fold increase of
salicylic acid penetration in rat skin. Anatomically, rat skin differs from human skin; it
contains less layers of corneocytes and is thinner126. According to Fick’s second law,
diffusion is inversely proportional to the thickness of the diffusion layer. As a
consequence, the rate of permeation may be lower in human skin. Lastly, the difference
in thickness may also change the volume of distribution in the skin. For topical
application, the volume of distribution was modeled as a fraction of the IV volume of
distribution. It was approximately the ratio of application area and total body surface
area of the rat. Similarly, the fraction of skin volume of distribution was adjusted in
humans. Still, this was only a gross approximation and might over-/underestimate the
volume.
In conclusion, showed in vitro activity against the tested MSSA and MRSA
strains. Relative to intact skin, retapamulin permeation was higher in perturbed skin and
concentration levels suggest that the drug may be suited to not only treat superficial
skin diseases. The antibacterial activity of retapamulin seemed to be time-dependent.
Nonetheless, clinical studies are necessary to evaluate our predictions, establish human
PK parameters, refine the model and assess the efficacy against other indications.
113
LIST OF REFERENCES
1. Australian Government Department of Health Therapeutic Goods Administration. Australian Public Assessment Report for Retapamulin. Aust. Public Assess. Rep. (2013).
2. May, A. K., Stafford R.E., Bulger E.M., Heffernan D., Guillamondegui O., Bochicchio G. & Eachempati S.R. Treatment of complicated skin and soft tissue infections. Surg. Infect. (Larchmt). 10, 467–99 (2009).
3. Ki, V. & Rotstein, C. Bacterial skin and soft tissue infections in adults: A review of their epidemiology, pathogenesis, diagnosis, treatment and site of care. Can. J. Infect. Dis. Med. Microbiol. 19, 173–84 (2008).
4. Cornia, P. B., Davidson, H. L. & Lipsky, B. A. The evaluation and treatment of complicated skin and skin structure infections. Expert Opin. Pharmacother. 9, 717–30 (2008).
5. Curcio, D. Resistant pathogen-associated skin and skin-structure infections: antibiotic options. Expert Rev. Anti. Infect. Ther. 8, 1019–36 (2010).
6. US Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER). Guidance for Industry: Uncomplicated and Complicated Skin and Skin Structure Infections—Developing Antimicrobial Drugs for Treatment (1998) at <http://www.fda.gov/ohrms/dockets/98fr/2566dft.pdf>
7. Rosen, T. Update on treating uncomplicated skin and skin structure infections. J. Drugs Dermatol. 4, s9–14 (2012).
8. Rajan, S. Skin and soft-tissue infections: classifying and treating a spectrum. Cleve. Clin. J. Med. 79, 57–66 (2012).
9. Napolitano, L. M. Severe soft tissue infections. Infect. Dis. Clin. North Am. 23, 571–91 (2009).
114
10. Diekema, D. J., Pfaller M.A., Schmitz F.J., Smayevsky J., Bell J., Jones R.N. & Beach M. Survey of Infections Due to Staphylococcus Species: Frequency of Occurrence and Antimicrobial Susceptibility of Isolates Collected in the United States, Canada, Latin America, Europe, and the Western Pacific Region for the SENTRY Antimicrobial Surveillanc. Clin. Infect. Dis. 32, S114–S132 (2001).
11. Moet, G. J., Jones, R. N., Biedenbach, D. J., Stilwell, M. G. & Fritsche, T. R. Contemporary causes of skin and soft tissue infections in North America, Latin America, and Europe: report from the SENTRY Antimicrobial Surveillance Program (1998-2004). Diagn. Microbiol. Infect. Dis. 57, 7–13 (2007).
12. Ray, G. T., Suaya, J. A. & Baxter, R. Incidence, microbiology, and patient characteristics of skin and soft-tissue infections in a U.S. population: a retrospective population-based study. BMC Infect. Dis. 13, 252 (2013).
13. Vinh, D. C. & Embil, J. M. Rapidly progressive soft tissue infections. Lancet. Infect. Dis. 5, 501–13 (2005).
14. DiNubile, M. J. & Lipsky, B. A. Complicated infections of skin and skin structures: when the infection is more than skin deep. J. Antimicrob. Chemother. 53 Suppl 2, ii37–50 (2004).
15. Dong, S. L., Kelly, K. D., Oland, R. C., Holroyd, B. R. & Rowe, B. H. ED management of cellulitis: a review of five urban centers. Am. J. Emerg. Med. 19, 535–40 (2001).
16. Edelsberg, J., Taneja C., Zervos M., Haque N., Moore C., Reyes K., Spalding J., Jiang J. & Oster G. Trends in US hospital admissions for skin and soft tissue infections. Emerg. Infect. Dis. 15, 1516–8 (2009).
17. Suaya, J. A., Mera R.M., Cassidy A., O'Hara P., Amrine-Madsen H., Burstin S. & Miller L.G. Incidence and cost of hospitalizations associated with Staphylococcus aureus skin and soft tissue infections in the United States from 2001 through 2009. BMC Infect. Dis. 14, 296 (2014).
18. McCaig, L. F., McDonald, L. C., Mandal, S. & Jernigan, D. B. Staphylococcus aureus-associated skin and soft tissue infections in ambulatory care. Emerg. Infect. Dis. 12, 1715–23 (2006).
115
19. May, L., Mullins, P. & Pines, J. Demographic and treatment patterns for infections in ambulatory settings in the United States, 2006-2010. Acad. Emerg. Med. 21, 17–24 (2014).
20. Hersh, A. L., Chambers, H. F., Maselli, J. H. & Gonzales, R. National trends in ambulatory visits and antibiotic prescribing for skin and soft-tissue infections. Arch. Intern. Med. 168, 1585–91 (2008).
21. Yang, L. P. H. & Keam, S. J. Spotlight on retapamulin in impetigo and other uncomplicated superficial skin infections. Am. J. Clin. Dermatol. 9, 411–3 (2008).
22. Yang, L. P. H. & Keam, S. J. Retapamulin: a review of its use in the management of impetigo and other uncomplicated superficial skin infections. Drugs 68, 855–73 (2008).
23. Laustsen, G. Altabax approved to treat impetigo. Nurse Pract. 32, 13 (2007).
24. Yan, K., Madden L., Choudhry A.E., Voigt C.S., Copeland R.A. & Gontarek R.R. Biochemical characterization of the interactions of the novel pleuromutilin derivative retapamulin with bacterial ribosomes. Antimicrob. Agents Chemother. 50, 3875–81 (2006).
25. ALTABAX Prescribing Information. at <http://www.accessdata.fda.gov/drugsatfda_docs/label/2012/022055s002lbl.pdf>
26. Pankuch, G. A., Lin G., Hoellman D.B., Good C.E., Jacobs M.R. & Appelbaum P.C. Activity of retapamulin against Streptococcus pyogenes and Staphylococcus aureus evaluated by agar dilution, microdilution, E-test, and disk diffusion methodologies. Antimicrob. Agents Chemother. 50, 1727–30 (2006).
27. Woodford, N., Afzal-Shah, M., Warner, M. & Livermore, D. M. In vitro activity of retapamulin against Staphylococcus aureus isolates resistant to fusidic acid and mupirocin. J. Antimicrob. Chemother. 62, 766–8 (2008).
28. Kosowska-Shick, K. , Clark C., Credito K., McGhee P., Dewasse B., Bogdanovich T. & Appelbaum PC. Single- and multistep resistance selection studies on the activity of retapamulin compared to other agents against Staphylococcus aureus and Streptococcus pyogenes. Antimicrob. Agents Chemother. 50, 765–9 (2006).
116
29. Free, A., Roth E., Dalessandro M., Hiram J., Scangarella N., Shawar R. & White S. Retapamulin ointment twice daily for 5 days vs oral cephalexin twice daily for 10 days for empiric treatment of secondarily infected traumatic lesions of the skin. Skinmed 5, 224–32
30. Koning, S. , van der Wouden J.C., Chosidow O., Twynholm M., Singh K.P., Scangarella N. & Oranje A.P. Efficacy and safety of retapamulin ointment as treatment of impetigo: randomized double-blind multicentre placebo-controlled trial. Br. J. Dermatol. 158, 1077–82 (2008).
31. Oranje, A. P., Chosidow O., Sacchidanand S., Todd G., Singh K., Scangarella N., Shawar R. & Twynholm M. Topical retapamulin ointment, 1%, versus sodium fusidate ointment, 2%, for impetigo: a randomized, observer-blinded, noninferiority study. Dermatology 215, 331–40 (2007).
32. Altargo Summary of Product Characteristics. at <http://www.ema.europa.eu/docs/en_GB/document_library/EPAR_-_Product_Information/human/000757/WC500024409.pdf>
33. Chaurasia, C. S., Müller M., Bashaw E.D., Benfeldt E., Bolinder J., Bullock R., Bungay P.M., DeLange E.C., Derendorf H., Elmquist W.F., Hammarlund-Udenaes M., Joukhadar C., Kellogg D.L. Jr, Lunte C.E., Nordstrom C.H., Rollema H., Sawchuk R.J., Cheung B.W., Shah V.P., Stahle L., Ungerstedt U., Welty D.F. & Yeo H. AAPS-FDA workshop white paper: microdialysis principles, application and regulatory perspectives. Pharm. Res. 24, 1014–25 (2007).
34. Ungerstedt, U. Microdialysis--principles and applications for studies in animals and man. J. Intern. Med. 230, 365–73 (1991).
35. Microdialysis in Drug Development. 4, (Springer New York, 2013).
36. Bouw, M. R. & Hammarlund-Udenaes, M. Methodological aspects of the use of a calibrator in in vivo microdialysis-further development of the retrodialysis method. Pharm. Res. 15, 1673–9 (1998).
37. Lönnroth, P., Jansson, P. A. & Smith, U. A microdialysis method allowing characterization of intercellular water space in humans. Am. J. Physiol. 253, E228–31 (1987).
117
38. Olson, R. J. & Justice, J. B. Quantitative microdialysis under transient conditions. Anal. Chem. 65, 1017–22 (1993).
39. Schmidt, S., Banks, R., Kumar, V., Rand, K. H. & Derendorf, H. Clinical microdialysis in skin and soft tissues: an update. J. Clin. Pharmacol. 48, 351–64 (2008).
40. Narkar, Y. Bioequivalence for topical products--an update. Pharm. Res. 27, 2590–601 (2010).
41. Holmgaard, R., Nielsen, J. B. & Benfeldt, E. Microdialysis sampling for investigations of bioavailability and bioequivalence of topically administered drugs: current state and future perspectives. Skin Pharmacol. Physiol. 23, 225–43 (2010).
42. Mouton, J. W., Dudley, M. N., Cars, O., Derendorf, H. & Drusano, G. L. Standardization of pharmacokinetic/pharmacodynamic (PK/PD) terminology for anti-infective drugs: an update. J. Antimicrob. Chemother. 55, 601–7 (2005).
43. Andes, D. & Craig, W. A. Animal model pharmacokinetics and pharmacodynamics: a critical review. Int. J. Antimicrob. Agents 19, 261–8 (2002).
44. Craig, W. A. Pharmacokinetic/pharmacodynamic parameters: rationale for antibacterial dosing of mice and men. Clin. Infect. Dis. 26, 1–10; quiz 11–2 (1998).
45. Mueller, M., de la Pena, A. & Derendorf, H. Issues in Pharmacokinetics and Pharmacodynamics of Anti-Infective Agents: Kill Curves versus MIC. Antimicrob. Agents Chemother. 48, 369–377 (2004).
46. Nielsen, E. I., Cars, O. & Friberg, L. E. Predicting in vitro antibacterial efficacy across experimental designs with a semimechanistic pharmacokinetic-pharmacodynamic model. Antimicrob. Agents Chemother. 55, 1571–9 (2011).
47. Nielsen, E. I. & Friberg, L. E. Pharmacokinetic-pharmacodynamic modeling of antibacterial drugs. Pharmacol. Rev. 65, 1053–90 (2013).
118
48. Nielsen, E. I., Viberg A., Löwdin E., Cars O., Karlsson M.O. & Sandström M. Semimechanistic pharmacokinetic/pharmacodynamic model for assessment of activity of antibacterial agents from time-kill curve experiments. Antimicrob. Agents Chemother. 51, 128–36 (2007).
49. Points To Consider On Pharmacokinetics and Pharmacodynamics in the development of antibacterial medicinal products. at <http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500003420.pdf>
50. Innovation or Stagnation: Challenge and Opportunity on the Critical Path to New
Medical Products - March 2004. at <http://www.fda.gov/ScienceResearch/SpecialTopics/CriticalPathInitiative/CriticalPathOpportunitiesReports/ucm077262.htm>
51. Treyaprasert, W., Schmidt, S., Rand, K. H., Suvanakoot, U. & Derendorf, H. Pharmacokinetic/pharmacodynamic modeling of in vitro activity of azithromycin against four different bacterial strains. Int. J. Antimicrob. Agents 29, 263–70 (2007).
52. van de Kassteele, J., van Santen-Verheuvel M.G., Koedijk F.D., van Dam A.P., van der Sande M.A. & de Neeling A.J. New Statistical Technique for Analyzing MIC-Based Susceptibility Data. Antimicrob. Agents Chemother. 56, 1557–1563 (2012).
53. Pankey, G. A. & Sabath, L. D. Clinical relevance of bacteriostatic versus bactericidal mechanisms of action in the treatment of Gram-positive bacterial infections. Clin. Infect. Dis. 38, 864–70 (2004).
54. Yano, Y., Oguma, T., Nagata, H. & Sasaki, S. Application of logistic growth model to pharmacodynamic analysis of in vitro bactericidal kinetics. J. Pharm. Sci. 87, 1177–83 (1998).
55. Zhi, J., Nightingale, C. H. & Quintiliani, R. A pharmacodynamic model for the activity of antibiotics against microorganisms under nonsaturable conditions. J. Pharm. Sci. 75, 1063–1067 (1986).
56. Candel, F. J., Morales, G. & Picazo, J. J. In vitro activity of retapamulin against linezolid and methicillin-resistant Staphylococcus aureus isolates. Rev. Esp. Quimioter. 24, 127–30 (2011).
119
57. Kircik, L. H. Efficacy and tolerability of retapamulin 1% ointment for the treatment of infected atopic dermatitis: a pilot study. J. Drugs Dermatol. 11, 858–60 (2012).
58. Champney, W. S. & Rodgers, W. K. Retapamulin Inhibition of Translation and 50S Ribosomal Subunit Formation in Staphylococcus aureus Cells. Antimicrob. Agents Chemother. 51, 3385–3387 (2007).
59. Murakami, T., Yoshioka M., Okamoto I., Yumoto R., Higashi Y., Okahara K. & Yata N. Effect of ointment bases on topical and transdermal delivery of salicylic acid in rats: evaluation by skin microdialysis. J. Pharm. Pharmacol. 50, 55–61 (1998).
60. Osamura, H., Jimbo, Y. & Ishihara, M. Skin penetration of nicotinic acid, methyl nicotinate, and butyl nicotinate in the guinea pig--comparison of in vivo and excised skin, and the effects of four dermatologic conditions. J. Dermatol. 11, 471–81 (1984).
61. Sun, L., Stenken J.A., Brunner J.E., Michel K.B., Adelsberger J.K., Yang A.Y., Zhao J.J. & Musson D.G. An in vivo microdialysis coupled with liquid chromatography/tandem mass spectrometry study of cortisol metabolism in monkey adipose tissue. Anal. Biochem. 381, 214–23 (2008).
62. Bengtsson, J., Boström, E. & Hammarlund-Udenaes, M. The use of a deuterated calibrator for in vivo recovery estimations in microdialysis studies. J. Pharm. Sci. 97, 3433–41 (2008).
63. Wang, Y., Wong, S. L. & Sawchuk, R. J. Microdialysis calibration using retrodialysis and zero-net flux: application to a study of the distribution of zidovudine to rabbit cerebrospinal fluid and thalamus. Pharm. Res. 10, 1411–9 (1993).
64. Clément, R., Malinovsky J.M., Dollo G., Le Corre P., Chevanne F. & Le Verge R. In vitro and in vivo microdialysis calibration using retrodialysis for the study of the cerebrospinal distribution of bupivacaine. J. Pharm. Biomed. Anal. 17, 665–70 (1998).
65. Barré, J., Chamouard, J. M., Houin, G. & Tillement, J. P. Equilibrium dialysis, ultrafiltration, and ultracentrifugation compared for determining the plasma-protein-binding characteristics of valproic acid. Clin. Chem. 31, 60–4 (1985).
120
66. Wang, C. & Williams, N. S. A mass balance approach for calculation of recovery and binding enables the use of ultrafiltration as a rapid method for measurement of plasma protein binding for even highly lipophilic compounds. J. Pharm. Biomed. Anal. 75, 112–7 (2013).
67. Stove, V., Coene L., Carlier M., De Waele J.J., Fiers T. & Verstraete A.G. Measuring unbound versus total vancomycin concentrations in serum and plasma: methodological issues and relevance. Ther. Drug Monit. 37, 180–7 (2015).
68. Jarzabek, J. I. & Kampa, I. S. Adaptation of total phenytoin reagent pack for measuring free phenytoin levels with the Abbott AxSYM immunoassay analyzer. Ther. Drug Monit. 21, 134–6 (1999).
69. Jensen, B. P., Chin, P. K. L. & Begg, E. J. Quantification of total and free concentrations of R- and S-warfarin in human plasma by ultrafiltration and LC-MS/MS. Anal. Bioanal. Chem. 401, 2187–2193 (2011).
70. Keizer, R. J., Karlsson, M. O. & Hooker, A. Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose. CPT pharmacometrics Syst. Pharmacol. 2, e50 (2013).
71. Kim, T. H., Shin B.S., Kim K.B., Shin S.W., Seok S.H., Kim M.K., Kim E.J., Kim D., Kim M.G., Park E.S., Kim J.Y. & Yoo S.D. Percutaneous absorption, disposition, and exposure assessment of homosalate, a UV filtering agent, in rats. J. Toxicol. Environ. Health. A 77, 202–13 (2014).
72. McCarley, K. D. & Bunge, A. L. Pharmacokinetic models of dermal absorption. J. Pharm. Sci. 90, 1699–719 (2001).
73. Poet, T. S. Assessing Dermal Absorption. Toxicol. Sci. 58, 1–2 (2000).
74. Reddy, M. B., Looney, R. J., Utell, M. J., Plotzke, K. P. & Andersen, M. E. Modeling of human dermal absorption of octamethylcyclotetrasiloxane (D(4)) and decamethylcyclopentasiloxane (D(5)). Toxicol. Sci. 99, 422–31 (2007).
75. Zhou, H. Pharmacokinetic Strategies in Deciphering Atypical Drug Absorption Profiles. J. Clin. Pharmacol. 43, 211–227 (2003).
121
76. Holford, N. H., Ambros, R. J. & Stoeckel, K. Models for describing absorption rate and estimating extent of bioavailability: application to cefetamet pivoxil. J. Pharmacokinet. Biopharm. 20, 421–42 (1992).
77. Savic, R. M., Jonker, D. M., Kerbusch, T. & Karlsson, M. O. Implementation of a transit compartment model for describing drug absorption in pharmacokinetic studies. J. Pharmacokinet. Pharmacodyn. 34, 711–26 (2007).
78. Bauer, R. NONMEM users guide introduction to NONMEM 7.3.0. (2013).
79. Gibiansky, L., Gibiansky, E. & Bauer, R. Comparison of Nonmem 7.2 estimation methods and parallel processing efficiency on a target-mediated drug disposition model. J. Pharmacokinet. Pharmacodyn. 39, 17–35 (2012).
80. Akaike, H. A new look at the statistical model identification. IEEE Trans. Automat. Contr. 19:716–23 (1974). at <http://www.garfield.library.upenn.edu/classics1981/A1981MS54100001.pdf>
81. Montgomery, D. C. & Peck, E. A. Introduction to Linear Regression Analysis. Wiley 301–302 (1982)
82. Bergstrand, M., Hooker, A. C., Wallin, J. E. & Karlsson, M. O. Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models. AAPS J. 13, 143–51 (2011).
83. Schmidt, S., Sabarinath S.N., Barbour A., Abbanat D., Manitpisitkul P., Sha S. & Derendorf H. Pharmacokinetic-pharmacodynamic modeling of the in vitro activities of oxazolidinone antimicrobial agents against methicillin-resistant Staphylococcus aureus. Antimicrob. Agents Chemother. 53, 5039–45 (2009).
84. Nolting, A., Dalla Costa, T., Rand, K. H. & Derendorf, H. Pharmacokinetic-pharmacodynamic modeling of the antibiotic effect of piperacillin in vitro. Pharm. Res. 13, 91–6 (1996).
85. Wajima, T., Yano, Y., Fukumura, K. & Oguma, T. Prediction of human pharmacokinetic profile in animal scale up based on normalizing time course profiles. J. Pharm. Sci. 93, 1890–900 (2004).
122
86. Tang, H., Hussain, A., Leal, M., Mayersohn, M. & Fluhler, E. Interspecies prediction of human drug clearance based on scaling data from one or two animal species. Drug Metab. Dispos. 35, 1886–93 (2007).
87. Øie, S. & Tozer, T. N. Effect of altered plasma protein binding on apparent volume of distribution. J. Pharm. Sci. 68, 1203–1205 (1979).
88. FDA. Guidance for Industry: Estimating the Maximum Safe Starting Dose in Adult Healthy Volunteer. (2005). at <http://www.fda.gov/downloads/Drugs/.../Guidances/UCM078932.pdf>
89. Breimer, D. D. Pharmacokinetics in liver disease. Pharm. Weekbl. Sci. 9, 79–84 (1987).
90. Davies, B. & Morris, T. Physiological parameters in laboratory animals and humans. Pharm. Res. 10, 1093–5 (1993).
91. Tschida, S. J., Vance-Bryan, K. & Zaske, D. E. Anti-infective agents and hepatic disease. Med. Clin. North Am. 79, 895–917 (1995).
92. Tam, V. H., Schilling, A. N. & Nikolaou, M. Modelling time-kill studies to discern the pharmacodynamics of meropenem. J. Antimicrob. Chemother. 55, 699–706 (2005).
93. Mouton, J. W. & Vinks, A. A. Pharmacokinetic/pharmacodynamic modelling of antibacterials in vitro and in vivo using bacterial growth and kill kinetics: the minimum inhibitory concentration versus stationary concentration. Clin. Pharmacokinet. 44, 201–10 (2005).
94. Campion, J. J., Chung, P., McNamara, P. J., Titlow, W. B. & Evans, M. E. Pharmacodynamic modeling of the evolution of levofloxacin resistance in Staphylococcus aureus. Antimicrob. Agents Chemother. 49, 2189–99 (2005).
95. Obach, R. S., Baxter J.G., Liston T.E., Silber B.M., Jones B.C., MacIntyre F., Rance D.J. & Wastall P. The Prediction of Human Pharmacokinetic Parameters from Preclinical and In Vitro Metabolism Data. J. Pharmacol. Exp. Ther. 283, 46–58 (1997).
123
96. Brown, R. P., Delp, M. D., Lindstedt, S. L., Rhomberg, L. R. & Beliles, R. P. Physiological parameter values for physiologically based pharmacokinetic models. Toxicol. Ind. Health 13, 407–84
97. Diack, S. L. The determination of the surface area of the white rat. Journal of Nutrition 3:289–296 (1930).
98. Gouma, E., Simos Y., Verginadis I., Lykoudis E., Evangelou A. & Karkabounas S. A simple procedure for estimation of total body surface area and determination of a new value of Meeh’s constant in rats. Lab. Anim. 46, 40–5 (2012).
99. Cole, C. & Gazewood, J. Diagnosis and Treatment of Impetigo. Am. Fam. Physician. 75(6):859–864 (2007).
100. Laube, S. & Farrell, A. M. Bacterial skin infections in the elderly: diagnosis and treatment. Drugs Aging 19, 331–42 (2002).
101. Retapamulin: a guide to its use in impetigo and other uncomplicated superficial skin infections. Drugs Ther. Perspect. 24, 1–4 (2008).
102. Mouton, J. W., Theuretzbacher U., Craig W.A., Tulkens P.M., Derendorf H & Cars O. Tissue concentrations: do we ever learn? J. Antimicrob. Chemother. 61, 235–7 (2008).
103. Burkhardt, O., Brunner M., Schmidt S., Grant M., Tang Y. & Derendorf H. Penetration of ertapenem into skeletal muscle and subcutaneous adipose tissue in healthy volunteers measured by in vivo microdialysis. J. Antimicrob. Chemother. 58, 632–6 (2006).
104. Ryan, D. M. & Cars, O. Antibiotic assays in muscle: are conventional tissue levels misleading as indicator of the antibacterial activity? Scand. J. Infect. Dis. 12, 307–9 (1980).
105. Ryan, D. M. & Cars, O. A problem in the interpretation of β-lactam antibiotic levels in tissues. J. Antimicrob. Chemother. 12, 281–284 (1983).
106. Ault, J. M., Riley, C. M., Meltzer, N. M. & Lunte, C. E. Dermal microdialysis sampling in vivo. Pharm. Res. 11, 1631–9 (1994).
124
107. Clough, G. F., Boutsiouki, P., Church, M. K. & Michel, C. C. Effects of blood flow on the in vivo recovery of a small diffusible molecule by microdialysis in human skin. J. Pharmacol. Exp. Ther. 302, 681–6 (2002).
108. Bouwstra, J. A., Honeywell-Nguyen, P. L., Gooris, G. S. & Ponec, M. Structure of the skin barrier and its modulation by vesicular formulations. Prog. Lipid Res. 42, 1–36 (2003).
109. Tadicherla, S. & Berman, B. Percutaneous dermal drug delivery for local pain control. Ther. Clin. Risk Manag. 2, 99–113 (2006).
110. DrugBank: Retapamulin. at <http://www.drugbank.ca/drugs/DB01256>
111. Schlupp, P., Weber, M., Schmidts, T., Geiger, K. & Runkel, F. Development and validation of an alternative disturbed skin model by mechanical abrasion to study drug penetration. Results Pharma Sci. 4, 26–33 (2014).
112. Lee, W. J., Kim J.Y., Song C.H., Jung H.D., Lee S.H., Lee S.J. & Kim do W. Disruption of barrier function in dermatophytosis and pityriasis versicolor. J. Dermatol. 38, 1049–53 (2011).
113. Bronaugh, R. L. & Stewart, R. F. Methods for in vitro percutaneous absorption studies V: Permeation through damaged skin. J. Pharm. Sci. 74, 1062–6 (1985).
114. Feldmann, R. J. & Maibach, H. I. Penetration of 14C hydrocortisone through normal skin: the effect of stripping and occlusion. Arch. Dermatol. 91, 661–6 (1965).
115. Rubio, L., Alonso C., López O., Rodríguez G., Coderch L., Notario J., de la Maza A. & Parra J.L. Barrier function of intact and impaired skin: percutaneous penetration of caffeine and salicylic acid. Int. J. Dermatol. 50, 881–9 (2011).
116. Simonsen, L. & Fullerton, A. Development of an in vitro skin permeation model simulating atopic dermatitis skin for the evaluation of dermatological products. Skin Pharmacol. Physiol. 20, 230–6 (2007).
125
117. Benfeldt, E. In vivo microdialysis for the investigation of drug levels in the dermis and the effect of barrier perturbation on cutaneous drug penetration. Studies in hairless rats and human subjects. Acta Derm. Venereol. Suppl. (Stockh). 206, 1–59 (1999).
118. Aalto-Korte, K. & Turpeinen, M. Transepidermal water loss and absorption of hydrocortisone in widespread dermatitis. Br. J. Dermatol. 128, 633–635 (1993).
119. Aalto-Korte, K. Improvement of skin barrier function during treatment of atopic dermatitis. J. Am. Acad. Dermatol. 33, 969–972 (1995).
120. Holmgaard, R., Benfeldt E., Bangsgaard N., Sorensen J.A., Brosen K., Nielsen F. & Nielsen J.B. Probe depth matters in dermal microdialysis sampling of benzoic acid after topical application: an ex vivo study in human skin. Skin Pharmacol. Physiol. 25, 9–16 (2012).
121. Müller, M., Lunte C.E., Meltzer N.M. & Riley C.M. In vivo characterization of transdermal drug transport by microdialysis. J. Control. Release 37, 49–57 (1995).
122. Tettey-Amlalo, R. N. O., Kanfer, I., Skinner, M. F., Benfeldt, E. & Verbeeck, R. K. Application of dermal microdialysis for the evaluation of bioequivalence of a ketoprofen topical gel. Eur. J. Pharm. Sci. 36, 219–25 (2009).
123. Benfeldt, E., Hansen, S. H., Vølund, A., Menné, T. & Shah, V. P. Bioequivalence of topical formulations in humans: evaluation by dermal microdialysis sampling and the dermatopharmacokinetic method. J. Invest. Dermatol. 127, 170–8 (2007).
124. Ortiz, P. G., Hansen, S. H., Shah, V. P., Menné, T. & Benfeldt, E. The effect of irritant dermatitis on cutaneous bioavailability of a metronidazole formulation, investigated by microdialysis and dermatopharmacokinetic method. Contact Dermatitis 59, 23–30 (2008).
125. Kreilgaard, M. Dermal pharmacokinetics of microemulsion formulations determined by in vivo microdialysis. Pharm. Res. 18, 367–73 (2001).
126. Kreilgaard, M. Assessment of cutaneous drug delivery using microdialysis. Adv. Drug Deliv. Rev. 54, S99–S121 (2002).
126
127. Reddy, M. B., Looney, R. J., Utell, M. J., Plotzke, K. P. & Andersen, M. E. Modeling of human dermal absorption of octamethylcyclotetrasiloxane (D(4)) and decamethylcyclopentasiloxane (D(5)). Toxicol. Sci. 99, 422–31 (2007).
128. Meagher, A. K., Forrest, A., Dalhoff, A., Stass, H. & Schentag, J. J. Novel pharmacokinetic-pharmacodynamic model for prediction of outcomes with an extended-release formulation of ciprofloxacin. Antimicrob. Agents Chemother. 48, 2061–8 (2004).
129. Bulitta, J. B., Ly N.S., Yang J.C., Forrest A., Jusko W.J. & Tsuji B.T. Development and qualification of a pharmacodynamic model for the pronounced inoculum effect of ceftazidime against Pseudomonas aeruginosa. Antimicrob. Agents Chemother. 53, 46–56 (2009).
130. Harigaya, Y., Bulitta J.B., Forrest A., Sakoulas G., Lesse A.J., Mylotte J.M. & Tsuji BT. Pharmacodynamics of vancomycin at simulated epithelial lining fluid concentrations against methicillin-resistant Staphylococcus aureus (MRSA): implications for dosing in MRSA pneumonia. Antimicrob. Agents Chemother. 53, 3894–901 (2009).
131. Sheiner, L. B., Stanski, D. R., Vozeh, S., Miller, R. D. & Ham, J. Simultaneous modeling of pharmacokinetics and pharmacodynamics: application to d-tubocurarine. Clin. Pharmacol. Ther. 25, 358–71 (1979).
132. Barbour, A. M., Schmidt, S., Zhuang, L., Rand, K. & Derendorf, H. Application of pharmacokinetic/pharmacodynamic modelling and simulation for the prediction of target attainment of ceftobiprole against meticillin-resistant Staphylococcus aureus using minimum inhibitory concentration and time-kill curve based approaches. Int. J. Antimicrob. Agents 43, 60–7 (2014).
133. Katsube, T., Yamano, Y. & Yano, Y. Pharmacokinetic-pharmacodynamic modeling and simulation for in vivo bactericidal effect in murine infection model. J. Pharm. Sci. 97, 1606–14 (2008).
134. Park, S. H., Kim, J. K. & Park, K. In Vitro Antimicrobial Activities of Fusidic Acid and Retapamulin against Mupirocin- and Methicillin-Resistant Staphylococcus aureus. Ann. Dermatol. 27, 551–6 (2015).
135. Saravolatz, L. D., Pawlak, J., Saravolatz, S. N. & Johnson, L. B. In vitro Activity of Retapamulin against Staphylococcus aureus Resistant to Various Antimicrobial Agents. Antimicrob. Agents Chemother. 57, 4547–4550 (2013).
127
136. Lowy, F. D. Antimicrobial resistance: the example of Staphylococcus aureus. J. Clin. Invest. 111, 1265–73 (2003).
137. Chambers, H. F. Methicillin resistance in staphylococci: molecular and biochemical basis and clinical implications. Clin. Microbiol. Rev. 10, 781–91 (1997).
138. Dedrick, R., Bischoff, K. B. & Zaharko, D. S. Interspecies correlation of plasma concentration history of methotrexate (NSC-740). Cancer Chemother. Rep. 54, 95–101 (1970).
139. Zou, P., Yu Y., Zheng N., Yang Y., Paholak H.J., Yu L.X. & Sun D. Applications of human pharmacokinetic prediction in first-in-human dose estimation. AAPS J. 14, 262–81 (2012).
140. Mahmood, I. Interspecies scaling of biliary excreted drugs: a comparison of several methods. J. Pharm. Sci. 94, 883–92 (2005).
141. Fagerholm, U. Prediction of human pharmacokinetics-biliary and intestinal clearance and enterohepatic circulation. J. Pharm. Pharmacol. 60, 535–42 (2008).
142. Zou, P., Zheng, N., Yang, Y., Yu, L. X. & Sun, D. Prediction of volume of distribution at steady state in humans: comparison of different approaches. Expert Opin. Drug Metab. Toxicol. 8, 855–72 (2012).
143. Stepensky, D. The Øie–Tozer model of drug distribution and its suitability for drugs with different pharmacokinetic behavior. Expert Opin. Drug Metab. Toxicol. (2011).
144. Waters, N. J. & Lombardo, F. Use of the Øie-Tozer model in understanding mechanisms and determinants of drug distribution. Drug Metab. Dispos. 38, 1159–65 (2010).
145. Skin Barrier: Principles of Percutaneous Absorption. 1, (Karger Basel, 1996).
146. Harada, K., Murakami T., Kawasaki E., Higashi Y., Yamamoto S. & Yata N. In-vitro permeability to salicylic acid of human, rodent, and shed snake skin. J. Pharm. Pharmacol. 45, 414–8 (1993).
128
147. Benfeldt, E. & Serup, J. Effect of barrier perturbation on cutaneous penetration of salicylic acid in hairless rats: in vivo pharmacokinetics using microdialysis and non-invasive quantification of barrier function. Arch. Dermatol. Res. 291, 517–26 (1999).
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BIOGRAPHICAL SKETCH
Alexander Voelkner was born in Zwenkau, Germany. He studied pharmacy at the
Martin-Luther-University in Halle, Germany and earned his degree, B.S. in
pharmaceutical sciences, in November 2009. Upon completion of his practical
pharmaceutical training year he received his license to work as a pharmacist (R.Ph.) in
Germany in April 2011. In January 2012, he was accepted into the Ph.D. program at the
University of Florida, College of Pharmacy, Pharmaceutics Department. Under the
supervision of Dr. Hartmut Derendorf, he focused his research on the pharmacokinetics
and pharmacodynamics of anti-infectives. He has been an active member of the
American Association of Pharmaceutical Scientists (AAPS) and the American College of
Clinical Pharmacology (ACCP), where he also served on their leadership panels. He
received his Ph.D. in pharmaceutical sciences in December 2015.