1. Predictive value of PK/PD drug modelling: application to analgesic drugs PL Toutain UMR 181 Physiopathologie et Toxicologie Expérimentales INRA, ENVT ECOLE NATIONALE VETERINAIRE T O U L O U S E Satellite symposium: Validity and Quality of Animal Models for Measurement of Pain

2. Objectives of the presentation 1.Overview on the concept of PK/PD 2.Predictive value of PK/PD modeling for analgesics

3. What is PK/PD modeling? PK-PD modeling is a scientific tool to quantify, in vivo, the key PD parameters (efficacy, potency and sensitivity) of a drug, which allows to predict the time course of drug effects under physiological and pathological conditions (intensity and duration)

4. What are the main practical applications of a PK/PD trial  Preclinical investigations: It is an alternative to dose-titration studies to discover a dosage regimen  Clinical setting:  It is a tool to optimize dosage regimen in a clinical setting (pop PK/PD)

5. 1-An overview on the concept of PK/PD

6. Dose titration DoseResponse Black box PK/PD Dose PKPD Plasma concentration Response

7. Why is plasma concentration profile a better explicative (independent) variable than dose for determining a dosage regimen ?

8. Dose vs. plasma concentration profile as independent variable Dose Mass (no biological information) Dose F% Clearance Time Concentration profile X (biological information)

9. Why to prefer a PK/PD approach to a classical dose-titration?

10. ED 50 = ED 50 - is a hybrid parameter (PK and PD) - is not a genuine PD drug parameter Clearance x target EC 50 Bioavailability PD PK The determination of an ED 50 or any ED %

11. The 3 structural PD parameters: Dose titration (DT) vs. PK/PD Emax ED 50 /EC 50 Slope Sensitivity shallow steep ED 50 2 Emax 1 Efficacy Potency Range of useful concentrations Selectivity Emax 2 1 2 1 2 ED 50 1 1 2 Emax/2 Dose Titration EmaxED 50 No PK/PD EmaxEC 50 yes

12. Why to prefer a PK/PD approach to a classical dose-titration? 2.The separation of PK and PD variability

13. PK/PD variability Consequence for dosage adjustment PKPD Dose Plasma concentration Effect BODY Receptor Kidney function Liver function... Clinical covariables Pain severity or duration PK/PD population approach

14. 2-Predictive value of PK/PD for analgesics

15. Predictive value of PK/PD modeling rely on: 1.The question: –Mechanistic question vs. Clinical drug development 2.Selection of a pain model & In life validation of the selected model 3.Appropriate study design & conduct 4.Appropriate PK & PD data 5.Appropriate PK/PD modeling 6.Population PK/PD (clinical setting)

16. The question: a mechanistic question Drug discovery

17. Questions for a veterinary rational drug development: find an optimal dosage regimen for a target species What is the typical Dosage regimen Time information and decision –Onset of drug action: fentanyl vs. morphine –Duration of drug action: time of remedication ( Dosage interval) Extrapolation –Between species assumption of the same PD parameters –Within the same species: between route of administration Assumption: different PK profile but same qualitative metabolic profile Dosage adjustment –Population investigations

18. 2-Selection of a pain model: experimental pain models vs. clinical pain for PK/PD investigations

19. Pain models For PK/PD investigation Preclinical Inflammatory Dose determination e.g. NSAIDs Non Inflammatory Dose determination Opioids Gabapentine Clinical pain≠nociception Surgical models Possibility to standardize Dose confirmation Spontaneous pain neuropathy Dose adjustment Pop PK/PD

20. Pain model selection for PK/PD investigation: value & validity Validity: –to be discussed by the pain’ specialist –refers to whether a study is able to scientifically answer the questions it is intended to answer –Regarding the ultimate objective: To investigate neurophysiologic mechanisms of pain or complicate drug mechanism of action Preclinical determination of a dosage regimen –Simple but reproducible antinociceptive model are often sufficient –Validityof a model =capacity to find a useful dose Value: –to be demonstrated by the PK/PD trialist

21. Pain model selection for PK/PD investigation: value & validity Validity Value –Ethical –Metrological performances Reliable Sensitive Robust & transferable –Convenience – Etc.

22. Models using pressure noxious stimulus or thermal noxious stimulus are considered as valuable in veterinary medicine to approximate a starting dose

23. Inflammatory pressure noxious stimulus. (here a kaolin inflammation model)

24. To measure the vertical forces, a corridor of walk is used with a force plate placed in its center. The cat walks on the force plate on leach. Video Measure of vertical forces exerted on force plate

25. The measure of vertical force and video control are recorded  Vertical forces (Kg) Video Measure of vertical forces exerted on force plate

26. Measure of pain with analgesiometer The time for the cat to withdraw its paw of the ray is measured.  withdrawal time of the paws (second)  Sensitive and specific model to activate C-fibers Video

27. Validation of the selected model

28. Validation of the model 1.A priori validation makes sure the method is suitable for its intended use –When developing a new method 2.In life validation (routine validation for any new trial) –Animal selection –Investigator skill –Reproducibility & repeatability of selected animals –etc

29. Validation of the model is tedious

30. Predictive value of PK/PD modeling rely on: 1.The question: 2.Selection of a pain model & In life validation of the selected model 3.Appropriate study design & conduct Crossover design and placebo period 4.Appropriate PK & PD data 5.Appropriate PK/PD modeling 6.Population PK/PD (clinical setting)

31. 4-Appropriate data for PK/PD modeling

32. Measuring drug response Measuring drug exposure Measuring variables in PK/PD trials Full concentration time curve –experimental setting Cmax, Cmin –Clinical setting Biomarkers Surrogate Clinical outcomes

33. Measuring exposure Generally straightforward. May be more complicate if: – presence of an active metabolite Tramadol –Racemates Profens

34. Tramadol plasma concentration (ng/mL) vs. time (min) after an IM administration of tramadol (circa 8 mg/kg);

35. pharmacokinetics of (±)-trans-T and M1 are stereoselective in vivo Trans-tramadol [(±)-trans-T] hydrochloride is a chiral compound (+)-, (-)-Trans-T take as the action mainly through inhibiting the reuptake of serotonin and norepinephrine, respectively The drug is metabolized in the liver to form five phase I metabolites, with the main pathways (in man and rats) being O-demethylation to O- demethyltramadol (M1) Among the metabolites, M1 is an only active metabolite, and (+)-M1 has a high affinity to the opioid receptor

36. SubstancesAction RR-TNo action SS-TMonoamine re-uptake RR-M1µ-opioid SS-M1Monoamine re-uptake

37. Pharmacodynamic parameters of tramadol in the rat Action IC 50 (ng/mL) RR-TNo actionNA SS-TMonoamine re-uptake 230 RR-M1µ-opioid20.2 SS-M1Monoamine re-uptake 869

38. Tramadol and tramadol metabolite M1 concentration (ng/mL) vs. time (min) in 8 dogs after an IM administration of tramadol (circa 8 mg/kg) ; Spaghetti plot; semilogarithmic scale No CYP2D6 in dogs but an ortholog i.e CYP2D15

39. Plasma concentrations of R- and S- ketoprofen after intramuscular administration of ketoprofen ( 6 mg/kg)

40. Time development of the plasma concentration of ketoprofen and the mechanical nociceptive thresholds before kaolin injection (negative control), after kaolin injection (positive control) and after ketoprofen administration EC 50 R-keto=2.0±05 µg/mL S-ket=38.8±10.8 T. K. FOSSE et al JVPT in press Kaolin R-keto S-Keto Nociception

41. Measuring drug response Measuring drug exposure Measuring variables in PK/PD trials Full concentration time curve AUC Cmax, Cmin Biomarkers Surrogate Clinical outcomes

42. Requires  90% PGE2 inhibition EC 50 response EC 50 response >> EC 50 effect EC 50 in vivo effect EC 50 action whole blood assay Which dependent variable for PK/PD modeling ? NSAID plasma concentration Inhibition of COX Inhibition of PGE2 production Suppression of lameness

43. 5-PK/PD modelling

44. Modeling options regarding presence or not of a delay between PK and PD time development PK and PD delay NO YES No PK modeling PK modeling PK origin PD origin Indirect response model Effect compartment model E = Emax x C(t) model EC 50 + C(t) model Emax x C observed EC 50 + C observedl E =

45. Thermal threshold Plasma Fentanyl No hysteresis for fentanyl Direct incorporation of plasma fentanyl concentration in an Emax model

46. IV Oral Buprenorphine concentration ΔT(ºC) hysteresis loop

47. Modeling strategies when there is a delay of PK origin

48. The “effect compartment model” Dose 1:PK model Parametric (Exponential) Non parametric (Spline) 2:Link model Ke0 3:PD model Parametric (Emax, Hill) Non parametric (spline) Ke0 K 10 Cp(t) Ce(t) Time Concentration effect Ce Effect Effect(t) Time Effect Estimation of EC 50 and Ke0

49. A mechanistic class of PK/PD models

50. An example of dose determination using a PK/PD modeling approach: Tramadol in dogs

51. Thermal stimulus: time course (h) of the paw withdrawal time expressed as a percentage of the control value Tramadol 8mg/kg Placebo

52. Data modeling using an indirect effect model Rate of change of the response (withdrawal time, WT) over time Kin is the (control) zero- order rate constant of the response formation Kout is the first-order rate constant of response disappearance Model of placebo effect

53. Observed and fitted response (WT in sec) vs. time (h) to tramadol after IM administration of tramadol to a dogs.

54. Dose effect relationship for tramadol as predicted by the PK/PD model. Placebo 5mg/kg 14mg/kg 1mg/kg time course of effect from 0 to 4h post administration for different IM doses of tramadol ranging from 1 to 14 µmg/kg

55. Dose effect relationship for tramadol. Doses are from 0 to 14 mg/kg and effects are expressed by the Area Under the Effect vs. time curves (%*h) from 0 to 4 or 0 to 6h post tramadol administration 0 to 4h Emax=362 (%*h) ED 50 =4.67mg/kg 0 to 6h Emax=581 (%*h) ED 50 =9.90mg/kg

56. Tramadol: dose-effect Relationship: 7mg/kg IM vs PO IM PO Placebo

57. Predictive value of PK/PD modeling rely on: 1.The question: –Mechanistic question vs. Clinical drug development 2.Selection of a pain model & In life validation of the selected model 3.Appropriate study design & conduct 4.Appropriate PK & PD data 5.Appropriate PK/PD modeling 6.Population PK/PD (clinical setting)

58. 6-Experimental vs. observational population approach Two questions regarding experimental approach What is its validity (clinical relevance) What about intersubject variability

59. Dog model “accuracy” Experimental Highly selected (as homogeneous as possible) body weight, sex, age... Observational Population Representative of the target population different breed, age, pathological conditions… e.g. Beagle dogs

60. Beagle dogs: strain (colony) effect Some strains are responsive to pain thermal stimulus while some others are totally unresponsive –(strain raised for toxicology and selected and trained to be as quiet as possible) Some strains are very resilient Some strains are very responsive Dog enrolled in a trial based on their individual reproducibility(<25% over 3 days)

61. Cat model “accuracy” Not selected for experimental purposes Are re-homed after trial completion

62. Experimental pain model “accuracy” Experimental nociception Clinical pains –Inflammatory pain – Visceral pain –Muscle and joint pain –Peripheral neuropathy –Central neuropathy –Cancer pain

63. Variability is a biological fact not a noise …

64. What is population PK/PD Goal: to determine the sources of PK and PD variability in the target animal population as well as the magnitude of that variability, in order to design dosage regimens that account for individual animal (or group) characteristics to adapt dosage regimen to different subjects of the population having a given characteristic (e.g. breed)

65. Pain subjective assessment (composite measurement of behavioral & physiological signs) Data analysis –Ordinal (Y/N) or interval scale? Scoring rating scale –Simple descriptive scale (SDS) –Numerical rating scale (NRS) –Visual analogue scale (VAS) Issues: –reliability Confounding factors (hospitalization, anesthetics, drugs given peri- operatively (including some antibiotics as aminoglycosides…); unresponsiveness of some species; reproducibility between observers –Validity: No assessment of the subjective part of pain as for self-reporting in man

66. Probability of pain alleviation (POA) Logistic regression may be used to link measures of drug exposure to the probability of a clinical success Dependent variable Placebo effect sensitivity Independent variable (analgesic exposure) 2 parameters: a (placebo effect) & b (slope of the exposure-effect curve)

67. Probability of pain relief: Slope is controlled by the the intersubject variability, For morphine in man, the slope factor is of 3.6 indicating there is approximately fourfold variability between subjects. In analgesic studies in man, the mean effective concentration (MEC), which is the concentration at time remedication is required, is usually obtained in this manner.

68. PK / PD modeling Conclusions 1.A powerful tool for dose determination and adjustment or mechanistic purposes –If a a clear understanding of theoretical background and computer software. –If appropriate design (placebo) and metrological validation of the different endpoints 2.In preclinical setting, the question of the validity of the selected experimental model holds 3.In clinical setting, there is no longer a “model “ but the main difficulty is the validity (reliability) of the pain assessment