Pierre-Louis Toutain, Ecole Nationale Vétérinaire National veterinary School of Toulouse, France Wuhan 12/10/2015
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1 Antimicrobial susceptibility testing for amoxicillin in pigs: the setting of the PK/PD cutoff value using population kinetic and Monte Carlo Simulation Pierre-Louis Toutain, Ecole Nationale Vétérinaire National veterinary School of Toulouse, France Wuhan 12/10/2015 1
2 Rremind: Glossary Breakpoint (BP) (clinical) A numerical value for S or I or R A decision (risk management) taking into account CO values & other considerations (harmonization ) Cutoffs (CO) Numerical values to decide of the BP Epidemiological or microbiological CO (CO WT ) PK/PD CO (CO PD ) Clinical CO (CO CL ) Co are computed (risk assessment) 2
3 Development of a (clinical) Breakpoint (BP) for amoxicillin Clinical BP Diameter CO WT ECOFFs CO PK/PD CO CL 3
4 The case of Amoxicillin in pigs, a time dependent AMD 4
5 PK/PD cutoff Much more simple when AUC/MIC is the appropriate index Single value for a given dose More complicate when T>MIC is the selected index Several Co pkpd values for a given dose depending of the modalities of drug administration 5
6 Co pkpk for time dependent antibiotic Relevance of the rate of absorption The 3 AUC are equal T>MIC can be very different MIC1 MIC2
7 Difficulties for amoxicillin to establish a CO pkpd Different modalities of administration Routes of administration Po, IM (formulation LA) Modalities of administration In feed (matrix effect.), pump Time dependent AMD Time>MIC depends of routes of administration, formulations. However a single BP should be decided! 7
8 Remind Actually, for all long-acting drug/formulations, AUC/MIC is the appropriate universal index 8
9 A proposal of clinical breakpoint for amoxicillin in pigs (CLSI) 9
10 Schwarz et al Vet. Microbiol. 2008: Based on pharmacological, clinical and microbiological parameters, we suggest the following clinical breakpoints for amoxicillin to be used for the classification of bacterial pathogens involved in porcine respiratory tract infections: 0.5 µg/ml for susceptible, 1.0 µg/ml for intermediate, and 2 µg/ml for resistant. This was a qualitative expert statement, not the result of any sort of computation 10
11 The limits of the CLSI determination : no PKPD Cutoff 11
12 The setting of a PK/PD cutoff 12
13 The setting of a PK/PD CO Step1 Selection of a PK/PD index predictive of clinical efficacy and/or prevention of resistance Step 2 Determination of the critical value (size) of the selected PK/PD index Step 3 Computation, for a given animal species and for all possible (not probable) MICs of the percentage (proportion) of animals able to achieve the critical value of the selected PK/PD index (computation of so-called Target Attainment Rates (or TAR) 13
14 PK/PD Index Step 1:Selection of a PK/PD index fauc 24h /MIC fcmax/mic ft>mic Rem: it was shown that for all drugs/formulations having a long half-live that AUC/MIC is the appropriate index (AU/MIC: universal index?) 14
15 Step 2: Determination of the critical value (size) of the selected PK/PD index Size of the PK/PD index Default value Experimental value Preclinical Clinical In vitro/in vivo In vivo Static/dynamic Rodents Target species 15
16 The setting of a PK/PD CO Step1 Selection of a PK/PD index predictive of clinical efficacy and/or prevention of resistance Step 2 Determination of the critical value (size) of the selected PK/PD index Step 3 Computation, for a given animal species and for all possible (not probable) MICs of the percentage (proportion) of animals able to achieve the critical value of the selected PK/PD index (computation of so-called Target Attainment Rates (or TAR) 16
17 Step 3: Computation of the TAR (%) for the critical value of the selected index for the different possible MICs (TAR are stratified by MIC) PK raw data Population modeling Monte Carlo Simulation (n=5000 animals) TAR(%) 17
18 How to get PK data for amoxicillin We need raw data not parameters from publications Raw data can be obtained: Prospectively New AMD Retrospectively For old AMD, only historical data Old and often of poor quality but for bioequivalence trials Data kindly provided by 3 drug French companies plus an academic lab. 18
19 Step 3: Computation of the TAR (%) for the critical value of the selected index for the different possible MICs (TAR are stratified by MIC) PK raw data Population modeling Monte Carlo Simulation (n=5000 animals) TAR(%) 19
20 Step 1:Population PK meta-analysis of amoxicillin in pigs 20
21 Data: N=191 individual curves (rich data) from 4 lab corresponding to 8 formulations Routes Sources IV oral IM Total
22 The IV data Allowed to bridge data from different sources To ensure a lack of analytical bias To determine the model of disposition 22
23 Amoxicillin: raw data N=80 N=40 IM; company 2; 15mg/kg;LOQ=25ng/ml; Oral (premix); company 3 20mg/kg;LOQ=25ng/mL; 23
24 Plasma concentration of amoxicillin in pigs (oral route; the 4 companies) For visual inspection, Concentrations scaled to a nominal dose of 20mg/kg 24
25 Data analyzed and simulations performed with Monolix software 25
26 PK models: oral route K0 (zero order) Parametrisation in terms of clearance and volumes Log normal distribution Residual: proportional Only the site as covariate (β) 26
27 PK models: oral route (Goodness of the fit) Censored model (take into account LOQ) Visual Predictive Check (VPC ) Pop 90% prediction interval 27
28 Observations PK models: oral route (Overall Goodness of the fit) The observations are plotted vs. the population and individual prediction respectively Data point evenly around the line of identity Left plot: Scatter is influenced by how we model interanimal variability(η (0, ω)) Pop pred Ind pred f (, ) f, ˆ ) t ij ( t ij i 28
29 PK models: oral route (parameters estimates) Parametrisation in terms of clearance and volumes K0 (zero order) Cl=3.08 Cl formulation2=3.08xexp(-0.671) CV% 29
30 PK models: IM route Ka No flip-flop Ka1 Ka2 Flip-flop 30
31 PK models: IM route (Goodness of the fit) VPC Arithmetic vs. log plot 31
32 Step 2:Monte Carlo Simulations (oral route) Computation of the time for which free plasma concentration are above MIC from MIC ranging from to 4µg/mL for different dosage regimen 32
33 Monte Carlo Simulations: oral route Pop parameters + Binding:17%; 1000 pigs per run Total dose (mg/kg) Number of administrations Infusion Intervals Over 15h 33
34 Monte Carlo Simulations: oral route 10 mg/kg & single dose Exemple: only 36.8% of pigs above plasma free concentration of µg/mL for a single 10 mg/kg dose of amoxicillin 34
35 Monte Carlo Simulations: oral route 6.7 mg/kg, 3 times at 5.5h interval 35
36 Step 3: Computation of the TAR (%) for the critical value of the selected index for the different possible MICs (TAR are stratified by MIC) PK raw data Population modeling Monte Carlo Simulation (n=5000 animals) TAR(%) 36
37 Step 2:Monte Carlo Simulations (oral route) Computation of the time for which free plasma concentration are above MIC from to 4µg/mL for different dosage regimen 37
38 Monte Carlo Simulations: oral route Influence of the total dose (10 to 40 mg/kg per 24h) and its splitting (1 to 4 administration vs infusion over 15h) on the TAR (90% of pigs above a MIC over 40% of the dosage interval e.g: for a total dose of 20mg/kg (4x5mg/kg at 3h interval), 89.94% of pigs are able to achieve the PK/PD breakpoint Mic values (µg/ml) Splitting
39 Monte Carlo Simulations: oral route Conclusion With the current recommended oral dosage regimen (20 mg/kg) and for an optimal modality of administration (splitting the dose over 12h), the critical MIC is of 0.25µg/mL for the oral route of administration 39
40 Amoxicilline Conclusion from MCS The investigated PK/PD breakpoint are: For oral route (20 mg/kg, : 0.25µg/mL For IM route (30mg/kg) : µg/ml 40
41 Discussion and issues raised by the present results 41
42 Some questions raised by this MCS 1-Why the current BP seems to satisfy clinicians? Our PK/PD concepts need to be challenged The PK/PD concept are sound but BP value betalactams (Time >MIC of 40% for 90% of pigs ) is not appropriate for our clinical conditions (prophylaxis, metaphylaxis (control)? Because susceptibility testing are useless to help clinicians to take a decision 42
43 Some questions raised by this MCS 3-Do we have to revise the current dosage regimen of amoxicillin in pigs (i.e to increase the dose)? If yes, what would be the consequence in terms of food safety, impact on gut flora etc 43
44 Development of a (clinical) Breakpoint (BP) for amoxicillin Clinical BP Diameter CO WT ECOFFs CO PK/PD CO CL 44
45 Disk diffusion zone diameter Disk diffusion zone diameter correlates were estimated using the error ratebounded method described by CLSI and implemented in the dbets online software ( 45
46 Determining zone diameter breakpoints 46
47 Regression line between diameters and MIC MIC (µg/ml) Ampicillin 10 µg Lorian, p Zone diameters (mm) Large scatter around the line due to lack of precision of diameters 47
48 Rules of decision to classify inhibitory diameter zona (error rate-bounded method) MIC µg/ml >25 Major error Not accepted Susceptible resistant False resistant Minor error accepted false susceptible True susceptible <0.05 R S I diametre (mm 48
49 Clinical validation of BP as a test 49
50 Clinical success & value of susceptibility test 50
51 51
52 Conclusions Methods to establish PK/PD cutoff now well established The critical point in veterinary mediine is to select the PK/PD index The future could be to work with AUC/MIC as an universal index 52
In the context of the emergence of AMR, the rational
Use of Monte Carlo simulation to determine pharmacodynamic cutoffs of amoxicillin to establish a breakpoint for antimicrobial susceptibility testing in pigs Julien F. Rey, DVM; Céline M. Laffont, PhD;
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