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What is a MIC ? Relationship between a MIC and conventional pharmacodynamic parameters

Veterinary Committee on Antimicrobial Susceptibility Testing ( VetCAST). What is a MIC ? Relationship between a MIC and conventional pharmacodynamic parameters. P.L. Toutain VMAS symposium/workshop Uppsala 13 December 2017. MIC: definition (ISO 20776).

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What is a MIC ? Relationship between a MIC and conventional pharmacodynamic parameters

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  1. Veterinary Committee on Antimicrobial Susceptibility Testing (VetCAST) What is a MIC?Relationship between a MIC and conventional pharmacodynamic parameters P.L. Toutain VMAS symposium/workshop Uppsala 13 December 2017

  2. MIC: definition (ISO 20776) • It is the lowest concentration (in mg/L) of an antimicrobial agent (AMD) that, under defined in vitro conditions, prevents the appearance of visible growth of a microorganism within a defined period of time

  3. Minimum Inhibitory Concentration (MIC) is used for many purposes • For the susceptibility testing (AST) to guide clinician • MIC distributions to define wild type or non-wild type bacterial populations (ECOFF) • Resistance surveillance, • For PK/PD indices (fAUC/MIC, fT>MIC) • Comparative “potency” of new AMD during drug development • ……

  4. MIC should be obtained in strictly defined in vitro conditions • Any calculation or expression of the MIC should include a description of the method by which the MIC was determined or a reference to a published method (e.g. CLSI or EUCAST) should be given. • Many factors of variability may impact the MIC value

  5. PL Toutain Ecole Vétérinaire Toulouse Linezolid Oxacillin Ciprofloxacin Daptomycin Gentamicin Vancomycin MICs estimated with different inoculum densities, relative to that MIC at 2x105

  6. Zone diameters (mm) 40 x 30 x x x x 20 Chlortétracycline Streptomycine pH 6 7 8 influence of pH on AMD activity Lorian, p35

  7. The matrix effect • MHB is the standard matrix • What about MIC in a more relevant biological matrix as serum? • The case of macrolides

  8. PL Toutain; Ecole Vétérinaire de Toulouse The case of tulathromycin • CLSI CBP=16µg/mL MIC Tulathromycine

  9. MICs for M. haemolytica (calf isolates)in biological fluid (calf serum) versus broth (n=6)MICserum / MICbroth ratios • Serum MIC 29 times higher than broth MIC Serum MIC 50 times lower than broth Tulathromycin

  10. Clinical Infectious Diseases 2012 55 , 534 • “Macrolides show antimicrobial activity against P. aeruginosa in eukaryotic media through increased uptake and reduced efflux. These data may help explain the clinical efficacy of macrolides against pseudomonal Infections”.

  11. MIC of azithromycin (mg/L):CA-MBH vs. RPMI1640 medium Macrolides are considered intrinsically inactive against P. aeruginosa, with high (⩾256 mg·L−1) minimal inhibitory concentrations (MICs) measured in the recommended conventional broth but not in RPMI1640 Buyck et al 2012 CID 55, 534

  12. Macrolides increase outer Membrane Permeability in RPMI, not CA-MHB by down regulating oprM efflux pump • Macrolides have low MICs against P. aeruginosawhen tested in the presence of serum, bronchoalveolar lavage fluid or culture media used for eukaryotic cell cultures. • Enhanced macrolide activity in these media results from an increased permeability of the bacterial outer membrane by downregulation of oprM by macrolides in RPMI 1640 medium Buyck et al 2012 CID 55, 534

  13. Impairment of oprM Expression by Azithromycin in RPMI 1640 Medium The addition of a subinhibitory concentration of azithromycin (1 mg/L) caused a marked decrease of oprMexpression in bacteria grown in RPMI 1640 medium but no change in those grown in CA-MHB.

  14. Clinical consequences of (1) ignoring the true potency of macrolides against bacteria and (2) seeking to explain macrolide efficacy by an anti-inflammatory activity The risk of selecting macrolide-resistant P. aeruginosa

  15. What is exactly a MIC?An hybrid variable obtained in standardized conditions

  16. MIC is an activity • MIC provides a quantitative measure of an phenotypic activity over a certain period of time (most often 18-24h) • It is the end result of growth and kill/death of bacteria by the AMD • This activity reflects more fundamental pharmacodynamic (PD) parameters An antimicrobials can be fully describe by its fundamental PD parameters (as for any others drugs) and a MIC can be also viewed as an hybrid variable

  17. Main PD parameters that can be estimated from killing curves • MIC:Minimum inhibitory concentration • is not a “parameter” but an hybrid variable • Dimension: concentration • Efficacy (Emax or Kmax) • Measured in vitro as a Maximum killing rate constant (Kmax)) • Dimension : per hour (1/h) • Potency • Measured as an EC50 • Dimension : concentration • Sensitivity • Measured as a slope of the concentration -effect relationship • Dimension: scalar (without unit)

  18. The 3 PD parameters of a concentration -effect relationship Emax (Kmax) EC50 Slope Time-dep 1 1 Emax 1 2 2 Emax 2 shallow Conc-dep Emax/2 stiff EC501 EC502 AMD Concentration • Sensitivity • Allow to classify AMD as time-vs conc-dependent Efficacy (pharmacological) Potency

  19. Potency vs. efficacy • Not to be confused when doing pharmacology • MIC reflect both thus MIC is hybrid • Efficacy in a clinical context encompass all PD parameters • Advantages and disadvantages of a high potency • Advantage : Low dose to administrate when very potent • Limits: potency often positively correlated to lipophilicity

  20. Potency of FluoroquinolonesHydrophobicity vs MIC for S aureus MIC (µg/mL) Hydrophobicity (Clog-P) Takenouchi et al AAC 1996

  21. How to model efficacy, potency and sensitivity from killing curves: the Emax model % of Maximal Effect Maximal effect Efficacy [Concentration] EC50 Potency

  22. Sigmoid Emax PD Model:the “n” of Hill Effect (%) n = 5 n = 2 n = 1 n = 0.5 n = 0.1 EC50 EC50 [Drug]

  23. The Emax/Hill modelparameters vs. variables Efficacy (parameter) Sensitivity (parameter) Dependent variable Killing rate Independent variable (µg/mL or µMolar or MIC multiple) Potency (parameter)

  24. Interpretation of the slope (Gamma or Hill coefficient)

  25. MIC can be related to its more fundamental PD parameters by the modeling of killing curves

  26. A semimechanistic model to analyse KC (see presentation by Lena and Anders)

  27. The drug Killing rate is a function of basic PD parameters

  28. The three PD parameters of florfenicol for M.haemolytica

  29. What are the relationship between the MIC and the three PD parameters?

  30. Relationship between the MIC and the 3 PD parameters MIC is define as for ISO/EUCAST/CLSI With time=18h, N(0)=5x105 and N(18h)=108

  31. What is the most influencing factors on the value of the MIC? How to document this issue? Monte Carlo simulation and sensitivity analysis

  32. What is a MIC?Hand-on exercise using Monte Carlo simulations

  33. Q1: compute the MIC of florfenicol for M. haemolytica from its PD parameters and test tube conditions Click here to access the Excel sheet

  34. Q1: Results It is generally accepted that broth MIC tests are reproducible to within one doubling dilution of the real end point (i.e. ± one well or tube in a doubling dilution series).

  35. Q2: what is the computed MIC for florfenicol if the initial inoculum is 2x107, not 5x105

  36. Q3: What is the Minimum bactericidal concentration (MBC)? • It is the concentration (mg/L) with no (or few) surviving bacteria in the MIC test • Concentration resulting in at least 99.9% killing compared to initial inoculum • Operational definition final INO=5x102 CFU/mL • (see Mouton et al ClinPharmacokinet 2005 44 767-768):

  37. Q3: What is the Minimum Bactericidal concentration (MBC)?

  38. An infinity of what if questions • To systematically explore influence of the different PD parameters and test tube conditions, the only viable option is Monte Carlo Simulations • For a general presentation of MCS, see presentation by Ludovic Pelligand

  39. An add-in design to help Excel spreadsheet modelers perform Monte Carlo simulations • Others features • Search optimal solution (e.g. dose) by finding the best combination of decision variables for the best possible results

  40. MIC: Monte Carlo Simulations Replace point estimates by distribution to solve the equation

  41. Crystal Ball

  42. Open your Excel sheet with Crystal Ball and define assumptions

  43. Assumptions for Emax: log-normal distribution; GSD=10% Also minimum

  44. Assumption for Duration of the test : Time

  45. Assumption for Final INO

  46. Define forecast and start simulations (n=5000)

  47. Forecast distribution for MIC

  48. Q4: What is the certainty to have a MIC between 0.40 and 0.60mg/L Right Certainty Grabber Left Certainty Grabber

  49. Sensitivity Charts • Sensitivity charts show the influence of each assumption on MIC. • The overall sensitivity of a forecast to an assumption is a combination of two factors: • The model sensitivity of the forecast to the assumption (structural features of the model) • The assumption’s uncertainty (here 10% for all factors)

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