PK/PD APPROACH AND ANTIMICROBIAL RESISTANCE

1. PK/PD APPROACH AND ANTIMICROBIAL RESISTANCE Pierre-Louis Toutain, Ecole Nationale Vétérinaire INRA & National veterinary School of Toulouse, France 7th International Conference on antimicrobial agents in veterinary medicine Berlin September 16-19,2014

2. Introduction • PK/PD concepts are now well established to determine the dosing regimen for antimicrobials (AM) in veterinary medicine. • the previous presentation by Stefan • The main goal is to optimize clinical efficacy, but the risk of resistance development has been generally ignored in these dose optimizations

3. But of what resistance are we speaking?

4. Target pathogens Zoonotics Commensal Efficacy in animals Efficacy in man Global ecological problem Human Individual issue Public health issue Prevent emergence of resistance: but of what resistance? Environment Food chain Animal health issue

5. Bacterial load exposed to antibiotics during a treatment Digestive tract Infected Lungs Test tube Manure waste 1µg Several tons 1 mg Several Kg Food chain Soil, plant….

6. Duration of exposure of bacteria exposed to antibiotics Digestive tract Manure Sludge waste Infected Lungs Test tube Few days Several weeks/months 24h Food chain Soil, plant….

7. The priorities of a sustainable veterinary antimicrobial therapy is related to public health issues, not to animal health issuesAtrade-off between these two objectives is difficult or even impossible to achieve due to the non selectivity of most veterinary antibiotics.

8. Outline of the presentation • The classical integrated PK/P indices and the question of resistance: the MSW • The limits of the MSW • The mechanism-based models • Options to mitigate emergence and selection of resistance • Early/low dose treatment • Duration of treatment • Dug combinations

9. The mutant Selective Window(MSW) Currently the MSW is the only PK/PD index that is use to mitigate the emergence of resistance

10. Traditional hypothesis on emergence of AMR Concentration MIC Selective pressure for antibiotic concentration lower than the MIC Time

11. Current view for the emergence and selection of resistance : situation II No antibiotics & low inoculum size Mutation rate10-8 105 CFU No Mutant pop Wild pop With antibiotics eradication résistant susceptible

12. Current view for the emergence and selection of resistance : situation II Mutation rate10-8 No antibiotics & high inoculum 108 CFU Mutant pop 5-10xMIC=MPC Wild pop With antibiotics Mutation rate10-8 eradication Mutants population susceptible

13. The selection window hypothesis Mutant prevention concentration (MPC) (to inhibit growth of the least susceptible, single step mutant) MIC Selective concentration (SC) to block wild-type bacteria Mutant Selection window Plasma concentrations All bacteria inhibited Growth of only the most resistant subpopulation Growth of all bacteria

14. MIC & MPC for the main veterinary quinolones for E. coli & S. aureus

15. The MSW • The concept PK/PD of MSW was shown to be useful for quinolones for which resistance develops by mutational alterations of the drug target, but the concept is less clear for others mechanisms of resistance (e.g. plasmid mediated resistance) and for other classes of antibiotics even if the MIC/MPC ratio has been proposed for a variety of veterinary antibiotics (macrolides, cephalosporines, florfenicol)

16. Comparative MIC and MPC values for 285 M. haemolytica strains collected from cattle Vet Microbiol 2012 Blondeau JM

17. MSW: target pathogen vs. commensal flora

18. In the present study, we used fecal samples collected from these volunteers during and after ciprofloxacin treatment to analyze the dynamics of the emergence of resistance in E. coli over time in each volunteer.

19. Effect of ciprofloxacine on E coli • During antibiotic exposure (on days 8 and 14), no E. coli could be detected in most volunteers. • This was explained by the high fecal concentrations of ciprofloxacin, which was several thousand times greater than both the MIC and the mutant-prevention concentration against the dominant flora . • Selection of resistance was unlikely during treatment. • The appearance of QREC strains 4 weeks after the end of ciprofloxacin therapy was observed • explained by the pharmacokinetics of ciprofloxacin in stool, because ciprofloxacin concentrations slowly decreased from day 14 to day 42, when they were undetectable, with ciprofloxacin concentrations passing through the mutant selection window between days 14 and 42, when emergence of resistance was eventually detected in the fecal microbiota.

20. MSW: biophase vs Feces QREC From environment Stools 100 Target pathogen 10 MPC 1 MIC Time MSW MSW

21. Treated I have nowmy MSW What is the better option :Collective vs. selective treatment

22. The limit MSW and of PK/PD indices and of their breakpoint values regarding the resistance issues

23. The limit of MSW • simulations with more advanced semi-mechanistic PK/PD models showed that the classical PK/PD indices, including the MSW, have several major limitations and there is a need to go beyond these summary PK/PD variables to efficiently combat resistance by designing appropriate dosage regimens.

24. The three mains limits of classical PK/PD and MSW indices • They ignore information on the time-course of the PK and PD. • The U shaped curve of the MSW • They rely on the MIC that is not a PD parameter but a hybrid variable. • They are established on 24 hours, a too short period to study the adaptation of the bacteria to antibiotic drug exposure and selection of resistant bacterial subpopulations

25. T>MIC for 40-50% of the dosing interval:Daily dosing vs. long-acting drug Daily formulation Long-acting drug/formulation MIC Both treatments ensure plasma concentrations above MIC for 50% of the dosing interval (1 or 14 days) but they are not equivalent

26. Linezolid Oxacillin Ciprofloxacin Daptomycin Gentamicin Vancomycin MICs estimated with different inoculmum densities, relative to that MIC at 2x105

27. What is a MIC? • An hybrid variable • Its reflects: • The drug potency • The drug efficacy • the bacterial growth rate, • the bacterial death rate • and many other factors associated to its in vitro measurement (inoculum size, selected milieu, etc.).

28. Whatis a MIC?An hybrid variable From a mechanistic model point of view AM Potency AM efficacy Rate of death Defense mechanisms Rate of growth (supply shortage)

29. Effect of resistance on Kkill • The observed killing rate is a function of the natural death rate(0) times a scalar given by the Emax function Target site alteration Reduced Emax=Kkillmax/Kdeath Drug efflux pumps and enzymatic drug deactivation increase EC50 Can be surmounted by a higher dose

30. What is a MIC • The MIC value is only a snaphot measure of the net effect of the antibiotic under well standardized conditions (18-24h, constant AM concentration).

31. Clinical Pharmacokinetics 2005 44 201-210

32. Investigation of resistance require more than 24h

33. Impact on the total population of Staphylococcus aureus over time by two regimens of garenoxacin (in vitro model) The less intense regimen ceases to be effective after a delay of 5 days. the residual population to be eradicated by the immune system

34. Impact on the less-susceptible population of S. aureus over time by two regimens of garenoxacin. If therapy had been ended at day 4 or 5, little or no resistant mutant amplification would have occurred

35. Limits of the classical PK/PD indices to limit resistance • Therefore, the classical PK/PD indices are not well suited to understand and predict the emergence of resistance. • They are also unable to characterize the effect of drug combinations that are one of the best options to combat resistance

36. Mechanism-based model of antimicrobials

37. The value of mechanism-based models • These models aim to give a better understanding of the PK/PD relationship when modeling the full time-course of bacterial growth and killing.

38. A major review

39. The mechanism-based models:4 submodels • Models including equations to describe: • The microorganisms growth: microorganisms sub-model, • the changing drug concentration: PK model • The effect of AM drug: PD sub-model • to describe the interaction between the two preceding sub-models. • They can also include a sub-model for the host defenses.

40. Mechanism-based model of antimicrobials • Equation with: • no replication inhibition • Time-invariant susceptibility to drug • Constant replication rate

41. The microorganism sub-models • The microorganism sub-models can consider simultaneously different bacterial subpopulations with different levels of susceptibility and they can differentiate different mechanisms of resistance (alteration of the mutation rate, adaptative resistance, persisters)

42. PK/PD model for resistance and predicted bacterial time-kill curves B1, compartment with drug sensitive bacteria; B2, compartment with less drug-sensitive bacteria;

43. PKPD model for resistance (persisters) and predicted bacterial time-kill curves B1, compartment with drug sensitive bacteria; B3, compartment with non growing, drug-insensitive bacteria

45. The mechanism-based models • The mechanism-based model can be used for many purposes to test mechanistic hypotheses, to predict untested doses and complicated dosing regimens (PK mimicking in vivo situations, drug combinations, duration of treatment, etc).

46. Classical PK/PD indices vs. semi-mechanistic models

47. Classical PK/PD indices vs. semi-mechanistic models • These semi-mechanistic models are able to predict the classical PK/PD indices and their breakpoint values.

48. Classical PK/PD indices vs. semi-mechanistic models • However, they also predict that when the AM half-life is short, the best predictor is always T>MIC and when the half-life is long, the best predictor is always AUC/MIC whatever the antibiotic. • For long-acting formulations AUC/MIC is likely an universal PK/PD index • This would greatly facilitate many tasks such as finding an optimal dosage regimen and fixing sound clinical breakpoints for susceptibility testing.

49. How to mitigate emergence of resistance: practical aspects

50. How to combat resistance • Early initiation of AM therapy • Short duration • Combination therapy with 2 antibiotics