Population PK/PD and the rational design of an antimicrobial ...

Population PK/PD and the rational design of an antimicrobial ...

NATIONAL VETERINARY SCHOOL UMR 181 Physiopathologie & Toxicologie Exprimentales TOULOUSE Population PK/PD and the rational design of an antimicrobial dosage regimen in veterinary medicine Pierre-Louis Toutain AAVM Congress - Ottawa June 2004 02/24/20 Ottawa Juin 2004 - 1 Co-workers Academia Horse study

A. Bousquet-Mlou M. Doucet D. Concordet M. Peyrou Pig study J. del Castillo V. Laroute D. Concordet

P. Sanders M. Laurentie H. Morvan Industry Horse study Vetoquinol (France) M. Schneider Pig study SOGEVAL (France) C. Zemirline P. Pomie

VIRBAC (France) E. Bousquet INTERVET (germany) E Thomas Ottawa Juin 2004 - 2 "The design of appropriate dosage regimens may be the single most important contribution of clinical pharmacology to the resistance problem" Schentag et al. Annals of Pharmacotherapy, 30: 1029-1031 Ottawa Juin 2004 - 3 Dosage regimen and prevention of resistance Many factors can contribute to the development of bacteria resistance the most important risk factor is repeated exposure to suboptimal antibiotic concentrations

dosage regimen should minimize the likelihood of exposing pathogens to sublethal drug levels Ottawa Juin 2004 - 4 Ranking (Low, Medium, High) of extent of antibiotic drug use in animal based on duration and method of administration Duration Short <6 days Medium 6-21 d Long >21 days Individual animal Groups or pens of animal Flocks, herds

of animals L L M M M H H H H Ottawa Juin 2004 - 5 What is the contribution of the kineticist to the prudent use of antibiotics To assist the clinicians designing an optimal dosage regimen To ensure that the selected antibiotic reach the

site of infection at an appropriate effective concentration, for an adequate duration and for all (or most) animals under treatment to guarantee a cure (clinical, bacteriological) and without favoring antibioresistance Ottawa Juin 2004 - 6 The application of population pharmacokinetic modelling to optimize antibiotic therapy Ottawa Juin 2004 - 7 How to ensure that a dosage regimen minimizes the likelihood of exposing pathogens to sub-clinical drug levels Individual animals groups or pens vs flocks/herds population approach Ottawa Juin 2004 - 8

Reminder Traditional vs populational PK/PD approaches What is PK/PD for antibiotics and how to determine a dosage regimen using PK/PD predictors see P. Lees presentation Ottawa Juin 2004 - 9 Traditional veterinary PK Study performed in experimental setting elaborate design limited number of animals rich data Data analysis: two stages 1- modelling individuals samples of individual estimates Cl, Vss, F%, t1/2 2- statistical analysis

mean - SD search for difference between subgroups (ANOVA), for associations (regression) Ottawa Juin 2004 - 10 Limits of traditional PK Experimental conditions may be not representative of the real world consider variability as a nuisance Data analysis variance and covariance often badly estimated and explained Solution: the population approach Ottawa Juin 2004 - 11 How to determine a dosage regimen using PK/PD predictors

Ottawa Juin 2004 - 12 Dose titration Dose Response Black box PK/PD PK PD Response Dose Plasma concentration Ottawa Juin 2004 - 13

The main goal of a PK/PD trial in veterinary pharmacology To be an alternative to dose-titration studies to discover an optimal dosage regimen (will be presented by P. Lees) Ottawa Juin 2004 - 14 Contributions of the PK/PD approach to the population determination of a dosage regimen The separation of PK and PD variabilities Ottawa Juin 2004 - 15 PK/PD PK/PD variabilities

variabilities for for antibiotics antibiotics Consequence for dosage determination PK Dose BODY PD Plasma concentration Physiological/constitutional variables Breed, sex, age Kidney function Liver function... Pathogens

Effect Clinical covariables pathogens susceptibility (MIC) disease severity or duration PK/PD population approach Ottawa Juin 2004 - 16 PK/PD predictors of efficacy T>MIC : penicillins, cephalosporins, macrolides, oxazolidinones Cmax/MIC : aminoglycosides AUIC (or 24h AUC/MIC) : quinolones, tetracyclines, ketolides, azithromycins, streptogramins Cmax Concentrations Cmax/MIC AUC

AUIC = MIC Units = Time (h) MIC T>CMI 24h Time Ottawa Juin 2004 - 17 AUIC: an attempt to combine PK and PD properties of antibiotics Capacity to eliminate the drug PK AUC

AUIC # MIC PD Dose / Clearance = = MIC90 or MIC50 critical breakpoint value Fixed endpoint related to Emax and EC50 Application : fluoroquinolones Ottawa Juin 2004 - 18 Computation of dose using a PK/PD predictor

PD Breakpoint to be achieved Dose = AUIC 24h x MIC fu x F% x Clearance (24h) bioavailability Free fraction PK

Ottawa Juin 2004 - 19 Computation of dose using a PK/PD predictor PD Breakpoint to be achieved Dose = average (pop) AUIC 24h x MIC50 : average MIC90

MIC F% PK (average) x Clearance PK (average) Ottawa Juin 2004 - 20 Dispersion of variance around the mean may be the most relevant parameter to predict a population dosage regimen for antibiotics Ottawa Juin 2004 - 21 Variability and the likelihood of resistance Ingested dose

Selection of resistance Experimental setting MIC gut flora Field conditions oral Dose gut flora 1-F% Resistance: zoonotic, commensal F% Target biophase

Resistance: pathogens of interest Side effects Therapeutic window Undesirable concentration MIC90 Suboptimal exposure resistance Ottawa Juin 2004 - 22 Variability and the likelihood of resistance Ingested dose Selection of resistance

Field conditions oral MIC gut flora 1-F% Experimental setting Dose gut flora Resistance: zoonotic, commensal F% Target biophase Resistance: pathogens of interest

Side effects Therapeutic window Undesirable concentration MIC90 Suboptimal exposure resistance Ottawa Juin 2004 - 23 Examples of population approaches for antibiotics in veterinary medicine Identification and explanation of PK variability marbofloxacin in horse Determining drug PK characteristics in tissues using sparse sampling

marbofoxacin in ocular fluid in dog Dosage regimen determining doxycyclin in pig Ottawa Juin 2004 - 24 Marbofloxacin in horses A. Bousquet-Mlou et al. Ottawa Juin 2004 - 25 Marbofloxacin in horses: PK A fluoroquinolone No marketing authorization in horses Conventional PK study data analysis using the two-stage approach clearance = 4.15 0.75 mL/kg/min CV = 18% Vss = 1.48 0.3 L/kg t1/2 = 7.56 1.99 h Ottawa Juin 2004 - 26

Marbofloxacin in horses: PK/PD integration (oral route) Value of efficacy index (AUIC24h) and Cmax/MIC calculated from PK parameters obtained after the administration of 2 mg/kg BW in 6 horses MIC90 = 0.027 g/mL (enterobacteriaceae) average PK/PD index AUIC24h = 155 21 Cmax/MIC = 31 4.5 Ottawa Juin 2004 - 27 Population PK approach for marbofloxacin in horses: objective To measure the interindividual variability of systemic exposure to marbofloxacin in horses To identify covariates explaining a part of this variability Body clearance The only determinant of AUC

Ottawa Juin 2004 - 28 Materials and Methods (1) Animals patients from the Equine Clinic of the Veterinary School healthy horses from the Riding School Covariates record demographic, physiological, disease not all covariates presented IV administration of marbofloxacin (2 mg.kg-1) Nonlinear mixed-effects modelling Kinepop software (D. Concordet) Ottawa Juin 2004 - 29 Materials and Methods (2) Sampling design selection Number of samples per animal and selection of sampling times D - optimal design to maximize the precision of AUC [0-24h]

previous informations : AUC[0-24h] Mean and Standard Deviation Bousquet-Melou et al., Equine Vet J, 34, 2002 AUC imprecision 4 samples Sampling windows: 30min windows centred around 1.5, 3, 5, 7 and 19.5 h post-administration 5 samples Sampling design Ottawa Juin 2004 - 30 Materials and Methods (3) PK model : - biexponential equation - parameterisation in volumes of distribution and clearances

Statistical model : - lognormal distribution of PK parameters Model 1 : no covariate N 0, N 0, N 0, Log VC,i Vc Vc,i VC N 0, 2 Vc Log Vp,i Vp Vp,i Vp Log Cl i Cl Cl,i Cl

Log Cl d,i Cl d Cl d ,i Cl d 2 2 Vp Cl 2 Cl d

Model 2 : with covariates for body clearance Log Cl i Cl 1 Agei 2 Weight i Sex i Diseasei Cl,i Ottawa Juin 2004 - 31 Results: conventional vs pop kinetics Marbofloxacin (g/mL) 52 horses, 253 blood samples 10 1 0.1 0.01 0.001 0 4 8 12 16

Time (h) 20 24 Bousquet-Melou et al., Equine Vet J, 34, 2002 Ottawa Juin 2004 - 32 Variability: model without covariable 2.5 population mean = 3.88 mL/kg/min 2 (g/mL) predicted concentrations Clearance (pop)

Inter-individual variability CV(%) = 50 % 1.5 1 0.5 0 0 0.5 1 1.5 2 2.5 observed concentrations

(g/mL) Ottawa Juin 2004 - 33 Without covariable 2.5 (g/mL) predicted concentrations Variability: model with covariables 2.5 2 2 1.5 1.5

1 1 0.5 0.5 0 0 0 0.5 1 1.5 2

2.5 With covariables 0 0.5 1 1.5 2 2.5 observed concentrations (g/mL) Ottawa Juin 2004 - 34

Variability: explicative covariable Covariables for body clearance expressed in L.kg-1.h-1 Age NS Disease NS Sex NS Weight P=0.001 R2 = 0.33 The body weight explains about 33% of marbofloxacin clearance variability

Note: dose was 2 mg/kg BW i.e. already scaled to BW Ottawa Juin 2004 - 35 Marbofloxacin: the body weight is a covariable Body weight (kg) 200 400 600 0 -1 -2 -3 Clearance (L/kg/h)

Ln (Clearance) 0 0.6 0.4 0.2 0 0 Allometric relationship with an allometric exponent >1 200 400 600 Body weight (kg) Ottawa Juin 2004 - 36

Discussion Marbofloxacin clearance in horses Population trial Mean (L.kg-1.h-1) CV (%) Classical trials * 0.233 0.19 - 0.246 50 18 - 21 * Carretero et al., Equine Vet J, 34, 2002 Bousquet-Melou et al., Equine Vet J, 34, 2002 Influence of body weight

In the range of observed weights : about 3-fold variation in body clearance expressed per kilogram Ottawa Juin 2004 - 37 Conclusion High interindividual variability of marbofloxacin body clearance in horses Underestimated in classical PK trials Influence of body weight Consequences on systemic exposure Clinical relevance for efficacy and resistance ? Current trial Multicentric experiment (Montreal, Toulouse, Utrecht, Vienna) Increased number of covariates Further trials Assessment of variability of PD origin

Ottawa Juin 2004 - 38 Population PK/PD determination of a dosage regimen for an antiobiotic Ottawa Juin 2004 - 39 Objectives Document, with population PK/PD approach, the dosage regimen for antibiotics in pig Ultimate goal : make recommendations to determine a dosage regimen to establish MIC breakpoints to establish PK/PD predictor breakpoints Ottawa Juin 2004 - 40 Population trial (INRA/SOGEVAL/CTPA)

J. del Castillo et al. Antibiotic: doxycyclin Britain (2 settings) 215 pigs (30 to 110 kg BW) oral (soup) pens of 12-15 pigs (unit of treatment) Ottawa Juin 2004 - 41 Population trial Decision of treatment : metaphylaxis prevalence of disease>10% (tachypnee, body temperature > 40C) Treatments : Doxycyclin (5 mg/kg) or Doxycyclin + paracetamol (15 mg/kg)

2 meals apart from 24h Measure of covariables (rectal temperature /clinical signs etc.) Blood samplings (4 or 5 after the 2nd dose) Dosage HPLC (doxy, paracetamol+metabolite) Ottawa Juin 2004 - 42 PK Variability 1.6 Doxycycline Concentrations mg/mL 1.4 n = 215 1.2 1

0.8 0.6 0.4 0.2 0 -5 0 5 10 15 20 25 30

Time (h) Ottawa Juin 2004 - 43 PK doxycyclin variability analysis Ottawa Juin 2004 - 44 Doxycycline : sex effect Doxycycline Sexe 0 Sexe 1 Time (h) Ottawa Juin 2004 - 45 Doxycycline Doxycycline : body temperature effect

Rectal temperature Ottawa Juin 2004 - 46 Concentrations (g/mL) Doxycycline : disease effect healthy diseased Time (h) Ottawa Juin 2004 - 47 Variability analysis: AUC vs. body weight Distribution of AUC [0, 24 h] with weight AUC (mg h mL-1) 20

15 10 5 0 20 40 60 80 100 120 BW (kg) Ottawa Juin 2004 - 48

How to make use of PK/PD population knowledge to predict how well will doxycyclin perform clinically? Ottawa Juin 2004 - 49 The use of MonteCarlo simulation Dose selection at the population level Determination of breakpoints: PK/PD MIC Ottawa Juin 2004 - 50 Material and Method PK/PD analysis was performed using Monte Carlo simulations The method accounts for the variability in PK as well as MIC data to determine the

probability of reaching a target AUC0-24/MIC ratio Ottawa Juin 2004 - 51 Data analysis PK : non linear mixed effect model seek to explain the variability by covariables Computation of AUC and statistical establishment of distribution PK/PD: MonteCarlo approach to assess the distribution of the PK/PD endpoint Ottawa Juin 2004 - 52 Dosage regimen: application of PK/PD concepts The 2 sources of variability : PK and PD PK: exposure PD: MIC AUC [0, 24 h] Distribution

MIC Distribution (simulation) 16 30 25 12 % de germes Frquences (%) 14 10 8 6 4

20 15 10 5 2 0 0 3 4 5 6 7 8

9 10 11 12 13 14 15 16 17 18 19 20 AUC (g.h.mL-1) 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Distribution of PK/PD surrogates (AUC/MIC) Monte-Carlo approach 1 1.1 1.2 1.3 CMI (g/mL) Ottawa Juin 2004 - 53 AUC distribution AUC [0, 24 h] Distribution 16 Frequences (%)

14 12 10 8 6 4 2 0 3 4 5 6 7 8

Under-exposure ? 9 10 11 12 13 14 15 16 17 18 19 20 AUC (mg.h.mL-1) Ottawa Juin 2004 - 54 Microbiological data Intervet, Virbac, AFSSA Streptococcus suis (n=180) Actinobacillus pleuropneumoniae (n=110) Pasteurella multocida (n=206) Haemophilus (n=25) Ottawa Juin 2004 - 55

MIC distribution: Actinobacillus pleuropneumoniae (n=106) 35 30 INTERMEDIATE Pathogens % 40 25 20 15 10 5 SUSCEPTIBLE RESISTANT

0 0.25 0.5 1 2 4 8 MIC (g/mL) Ottawa Juin 2004 - 56 Pathogens % MIC distribution

Pasteurella multocida (n=205) 40 35 30 25 20 15 10 5 0 SUSCEPTIBLE 0.0625 0.125 0.25 0.5 1 2

4 MIC ( g/mL) Ottawa Juin 2004 - 57 MIC distribution Streptococcus suis (n=180) Bimodal distribution 30 INTERMEDIATE Pathogens % 35 25 20 SUSCEPTIBLE

15 RESIST. 10 5 0 0.0313 0.0625 0.125 0.5 1 2 CMI ( g/mL) 4 8

16 32 Ottawa Juin 2004 - 58 Statistical distribution of PK/PD predictors Question: what is the percentage of a pig population to achieve a given value of the PK/PD predictor for a given dose of doxycyclin for a: Empirical (initial) antibiotherapy (pathogen known, MIC unknown but distribution known) Targeted antibiotherapy (MIC known) Ottawa Juin 2004 - 59 Doctor or Regulator In clinical therapy, we would like to give optimal dose to each individual patient for the particular disease

individualized therapy (targeted antibiotherapy) In new drug assessment / development, we would like to know the overall probability for a population of an appropriate response to a given drug and proposed regimen population-based recommendations (empirical antibiotherapy) H. Sun, ISAP-FDA workshop 1999 Ottawa Juin 2004 - 60 Population PK/PD: applications Individualisation doctor Recommandation regulator Ottawa Juin 2004 - 61

% of pigs above the breakpoint Doxycycline (5 mg/kg) : empirical vs targeted antibiotherapy for Pasteurella multocida Empirical antibiotherapy Targeted antibiotherapy (MIC = 0.25 g/mL) 100% 80% 60% 40% 20% 0% 0 24 48 72 bacteriostatic 96 120 144 168 192

Breakpoint to be achieved (AUC/MIC) (h) Ottawa Juin 2004 - 62 % of pigs above the breakpoints Doxycycline (5 mg/kg): empirical vs targeted antibiotherapy for Actinobacillus pleuropneumoniae 100% Empirical (MIC unknown) 80% Targeted (MIC = 0.5 g/mL) 60% 40% 20%

Breakpoint to be achieved (AUC/MIC) (h) 0% 0 24 48 72 Bacteriostatic Ottawa Juin 2004 - 63 % of pigs above the breakpoint Doxycycline (5 mg/kg) : empirical vs targeted antibiotherapy for Streptococcus suis 100%

80% Empirical antibiotherapy Targeted antibiotherapy (MIC = 16 g/mL) 60% 40% 20% 0% 0 24 48 bacteriostatic 72 96

120 144 168 192 Breakpoint to be achieved (AUC/MIC) (h) Ottawa Juin 2004 - 64 Population dose determination Question: what is the doxycycline dose to be administered to achieve a given AUC/MIC ratio for a given percentage of the pig population ? (e.g. 90%) Ottawa Juin 2004 - 65

% of pigs above a given AUC/MIC ratio Doxycycline : selection of an empirical (initial) dose for Pasteurella multocida Doses 100% 90% 80% 5 mg/kg 60% 20 mg/kg 10 mg/kg 40% 20% 0% 0

24 48 bacteriostatic 72 96 120 144 168 AUC/MIC ratio (h) Ottawa Juin 2004 - 66 % of pigs above a given AUC/MIC ratio

Doxycycline : selection of an empirical (initial) dose for Actinobacillus pleuropneumoniae Doses 100% 5mg/kg 10 mg/kg 80% 20 mg/kg 60% 40% 20% 0% 0 24

bacteriostatic 48 72 AUC/CMI ratio (h) Ottawa Juin 2004 - 67 % of pigs above a given AUC/MIC ratio Doxycycline : selection of an empirical (initial) dose for Streptococcus suis Doses 100% 5 mg/kg 80% 10 mg/kg

60% 20 mg/kg 40% 20% 0% 0 24 48 72 96 120 144

168 AUC/MIC ratio (h) Ottawa Juin 2004 - 68 Determination of MIC breakpoints by standard developing organizations using population approach Ottawa Juin 2004 - 69 Determination of MIC breakpoints Current situation PK information is badly taken into account population approach Ottawa Juin 2004 - 70

Determination (or revision) of the clinical MIC breakpoint for a given drug against a given pathogen Dose fixed (marketing authorization) breakpoint to achieve determined: T>MIC >80% of the dosage interval or AUC/MIC = 100h computation of the critical MIC value for which T>MIC (or other PK/PD indices) are in excess of 90% (or other %) of subjects. Ottawa Juin 2004 - 71 % of pigs above the breakpoint Doxycycline (5 mg/kg) : MIC breakpoint for Actinobacillus pleuropneumoniae to achieve a given AUC/MIC ratio for 90% of pig MIC = 0.0625 g/mL

100% 90% 80% MIC = 0.125 g/mL MIC = 0.25 g/mL 60% 40% 20% 0% 0 24 48 bacteriostatic 72

96 120 144 168 192 216 240 Breakpoint AUC/MIC (h) Ottawa Juin 2004 - 72 % of pigs above a given AUC/MIC ratio Doxycycline (5 mg/kg): MIC breakpoint for Streptococcus suis to achieve a given AUC/ MIC ratio 100% 90% 80% MIC = 0.5g/mL MIC = 0.125 g/mL MIC = 0.0625 g/mL 60% 40%

20% 0% 0 24 48 Bacteriostatic 72 96 120 144 168 192

Breakpoint AUC/CMI (h) Ottawa Juin 2004 - 73 Doxycycline(5 mg/kg) : MIC breakpoints for Pasteurella multocida to achieve a given AUC/MIC ratio MIC = 0.0625 g/mL % de pc avec une AUC/CMI> seuil MIC = 0.125 g/mL MIC = 0.25 g/mL 100% 90% 80% 60% 40% 20% 0% 0

24 48 Bacteriostatic 72 96 120 144 168 192 AUC/MIC ratio (h) Ottawa Juin 2004 - 74

Determination of PK/PD predictor breakpoints For drug dosage prediction, not only PK/PD index that determine the effect but also its magnitude must be determined Prospective or retrospective approach using clinical data Ottawa Juin 2004 - 75 Conclusion For practitioners to adjust the dosage regimen for a given animal (or a given breed) flexible dosage regimen For drug companies and authorities a general framework to propose an empirical (initial) dosage regimen For standards-developing organizations MIC breakpoints

Ottawa Juin 2004 - 76 Experimental vs population studies Ottawa Juin 2004 - 77 Experimental Population Ottawa Juin 2004 - 78 Experimental vs. population approach Two questions regarding experimental approach What is its validity (clinical relevance) What about variability

Ottawa Juin 2004 - 79 Drug administration, social behavior and the dose Experimental Field Individually controlled by the investigator (restricted, tubing) related to individual feeding behavior (fever, anorexia) group effect (hierarchy, dominance) or other behavior The nominal dose is guaranteed to all individuals

Dose actually ingested can be much higher or much lower than the nominal dose Ottawa Juin 2004 - 80 The pathology Experimental Standardised experimental infectious model Field Spontaneous disease Ottawa Juin 2004 - 81 Animal selection Experimental Population

Highly selected (as homogeneous as possible) body weight, sex, age... Representative of the target population different breed, age, pathological conditions Ottawa Juin 2004 - 82 Study design Experimental Population Difference experimental, restrictive

Observational Power, inference space artificial (temperature, light) natural (e.g. field) interaction with environment behavior Ottawa Juin 2004 - 83 Experimental vs population approach: the status of variability Experimental

Population viewed as a nuisance that has to be overcome recognized as an important feature that should be identified, measured and explained (covariables) Ottawa Juin 2004 - 84 Experimental vs population approach Accuracy and variability In current experimental practices, major determinant of drug disposition (PK) or of drug effect (PD) can be modified, altered or suppressed ! GLP is not synonymous to good science

Ottawa Juin 2004 - 85 Advantage of field population kinetics over classical experimental setting Experimental environment healthy animals selected for homogeneity interindividual variability is viewed as a nuisance conditions rigidly standardized artificial conditions Real world / clinical setting patients representative of target population variability (inter & intraindividual, inter-occasion) is an important feature that should be identified and measured seek for explaining variability by identifying factors of

demographic pathophysiology Ottawa Juin 2004 - 86 Doxycycline concentration variability: population vs experimental trial DOXYCYCLINE (g/mL) 1.5 1.0 Number of data points Trial Population n=215 Experimental n=15 to 19 0.5 0.0 0

4 6 12 24 Time (h) Ottawa Juin 2004 - 87 Doxycycline concentration variability: population vs experimental trial for time 6h post-administration DOXYCYCLINE (g/mL) 1.5 Number of data points 1: Population n=215 2: Experimental n=16

3: Experimental n=64 1.0 0.5 0.0 0 1 2 3 Ottawa Juin 2004 - 88

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