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Introduction to PKPD Modelling – Applications Joe Standing June 2012 UCL Institute of Child Health & Great Ormond Street Hospital for Children, London.

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Presentation on theme: "Introduction to PKPD Modelling – Applications Joe Standing June 2012 UCL Institute of Child Health & Great Ormond Street Hospital for Children, London."— Presentation transcript:

1 Introduction to PKPD Modelling – Applications Joe Standing June 2012 UCL Institute of Child Health & Great Ormond Street Hospital for Children, London

2 Mycophenolate in Lupus Mycophenolic acid: selective noncompetitive inhibitor of ionosine 5’-monophosphate dehydrogenase (IMPDH) Blocking this depletes lymphocyte guanosine triphosphate

3 Mycophenolate in Lupus Simplistic statistical analysis What could model-based approach show?

4 Summary Scaling Pharmacokinetics Empirical PKPD models –Accepted PK target –In-vitro correlations –Models of disease score Effect site models Mechanistic PKPD Disease Models

5 Medicines in Children Unlicensed medicines –Prevalence: 36-67% (ICU 90%+) (Turner 1998) Notterman 1986:

6 Regulatory Perspective Legislation –FDA Modernisation Act 1997 –EU Paediatric Medicines Regulation 2006 All new medicines must be studied Old medicines can be licensed for children with appropriate studies

7 “Children are not small adults” Kearns 2003 VS. “Children are small adults” Tod 2008 and adults? 7

8 A typical plot: 8

9 “Children are small adults” CL often better correlated with BSA than wt (Cawford 1950) BMR correlated with wt 0.75 (Kleiber 1947) 9

10 “Children are small adults” 10

11 Scaling in PK: Tod et al 2008 MF = maturation function OF = organ function 11

12 Scaling in PK: Maturation Anderson 2010, Midazolam maturation 12

13 Scaling in PK: Size Warfarin (Takanashi 2006)

14 Scaling in PK: Size Size matters (Takanashi 2006) Dose/weight (mg/kg) 0.06 0.06 0.06

15 Summary Scaling Pharmacokinetics Empirical PKPD models –Accepted PK target –In-vitro correlations –Models of disease score Effect site models Mechanistic PKPD Disease Models

16 Aim for accepted target PK

17

18 Principles of antimicrobial PKPD 18

19 In vitro PKPD 19

20 20

21 Principles of antimicrobial PKPD 21

22 Clinical data: C max /MIC RATE OF CLINICAL RESPONSE VS. CMAX/MIC RATIO 22

23 Clinical data: AUC/MIC 23

24 Clinical data: AUC/MIC 24

25 Clinical data T>MIC 25 Clinical evidence lacking…

26 Be careful … 26

27 Methotrexate (MTX) PKPD PD marker – disease score Aims Characterise MTX PK in osteosarcoma patients Predict when concentration will fall below 0.2mcmol/L Investigate relationship between MTX PK and mucositis scores

28 Treatment Schedule (EURAMOS 1)

29 Raw PK Data 943 concentrations from 46 patients on up to 12 occasions

30 Mucositis Scoring WHO mucositis scale 01234 NoneSoreness ± erythema Erythema, ulcers, and patient can swallow solid food Ulcers with extensive erythema and patient cannot swallow solid food Mucositis to the extent that alimentation is not possible

31 PK VPC

32 PD VPC

33 PKPD Relationship

34 Summary Scaling Pharmacokinetics Empirical PKPD models –Accepted PK target –In-vitro correlations –Models of disease score Effect site models Mechanistic PKPD Disease Models

35 Remifentanil PKPD in infants Remifentanil used to decrease mean arterial pressure (MAP) during craniofacial surgery Aim: Describe PKPD relationship with remifentanil and MAP

36 Data 7 infants (0.3-1y; 6.6-9.6kg) 6 had rich (3 samples/min) PD data PD data during 1st half hour PK data during whole operation (before and 5min after changes in rate)

37 Remifentanil Raw Data PK Data: Remifentanyl concentration vs time (min) PD Data: MAP vs time (min)

38 PD Model

39 Remifentanil Results Final model - Sigmoidal Emax Target concentration for 30% MAP reduction = 14ng/mL

40 Individual PD Fits

41 Defined Concentration/Effect Relationship

42 Summary Scaling Pharmacokinetics Empirical PKPD models –Accepted PK target –In-vitro correlations –Models of disease score Effect site models Mechanistic PKPD Disease Models

43 Modelling hematological toxicity Relationship between drug exposure and myelosuppression Myelosuppression dose-limiting Typically: Logistic (E max ) model

44 Circulating Proliferative MTT Transit k tr Slope · Conc Feedback = Circulating Circ 0  Model of myelosuppression:

45 Estimated parameters - Leukocytes *=Unbound concentrations

46 Neutrophil model example CP-690,550 new oral DMARD Inhibitor of Janus kinase T and Bcell depression, causes neutropenia Phase 2a study, 264 subjects, placebo, 5, 15 and 30mg bd dosing

47 Gupta et al PD model Model simulation properties: Visual Predictive Check

48 Gupta et al PD model

49 Maintenance ALL treatment

50 Maintenance ALL Prevents recurrence in sanctuary sites 3 monthly intrathecals Monthly: vinc, dex Weekly: MTX Daily: 6-MP Target neuts: 0.75 – 1.5 *10 9 /L

51 Retrospective data 31 children, 2-13 y

52 Research question Does dose affect neutrophil counts? How should doses be adjusted?

53 Method Fitted Friberg model Drug effects as logistic decrease in proliferation Dexamethasone effect – increase Ktr Estimate baseline

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57 Summary Scaling Pharmacokinetics Empirical PKPD models –Accepted PK target –In-vitro correlations –Models of disease score Effect site models Mechanistic PKPD Disease Models

58 Diabetes Platform Models

59 Extension to diabetes model

60 Antiviral PKPD 60

61 HIV viral load/CD4

62

63 Summary Scaling Pharmacokinetics Empirical PKPD models Effect site models Mechanistic PKPD Disease Models


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