Best practice in dose finding studies. Rudolf Koehne-Volland Head of Biostatistics & CEO Metronomia Clinical Research GmbH

Transcription

1 Best practice in dose finding studies Rudolf Koehne-Volland Head of Biostatistics & CEO Metronomia Clinical Research GmbH

2 Best practice s in dose 13-Oct-2016 finding 2

3 Best practice in dose finding studies Agenda What is the problem? Dose finding requirements Dose finding approaches Challenges Conclusion 3

4 Success rates in drug development Trends over time Source: CMR International 2015 Global R&D Performance Metrics Programme 4

5 Attrition reasons 2013 & 2014 Reason Phase II Phase III & Reg review Efficacy 49% 53% Safety 31% 25% Strategy 19% 5% Source: Cortellis Competitive Intelligence & Thomson Reuters Integrity In many cases homework was not done in Phase II Not learning as much as necessary about a new treatment Not generating a good data basis or know-how for planning Phase III 5

6 Poor dose finding and failure around 16% of FDA NME filings failed to be approved first time due to uncertainties related to dose selection (Sacks et al., 2014) 21% of drugs filed in had post-approval dosage changes or were removed from sale (Cross et al., 2002) Source: Cortellis Competitive Intelligence & Thomson Reuters Integrity 6

7 What is the problem? Dose finding challenge Characterizing dose response for safety and efficacy is critical dose too high safety and tolerability problems are likely to result dose too low may lead to inadequate efficacy Therapeutic window: doses that are both efficacious and safe Optimal dose: a trade-off between efficacy and safety efficacy 1 safety Response clinically relevant effect Pr(dose tolerated) safety threshold dose d1 dose d2 7

8 Agenda What is the problem? Dose finding requirements Dose finding approaches Challenges Conclusion 8

9 Paracelsus ( ) All things are poison and nothing is without poison, only the dose permits something not to be poison. 9

10 ICH E4 Dose Response Information to Support Drug Registration 10

11 Selecting the right dose Paracelsus: ~ 500 years ago ICH E4: >20 years ago : ~ 16% of FDA NME filings failed due to uncertainties related to dose selection Are we doing ok? We are probably not doing ok! 11

12 Source: 12

13 EMA Report from Dose Finding Workshop 2014 Source: 13

14 EMA Report from Dose Finding Workshop 2014 Source: 14

15 EMA Report from Dose Finding Workshop 2014 Source: 15

16 Times are changing Better dose finding is required by Regulatory guidance Medical & scientific needs Drug development business Biotech business model potential pharma investors look more carefully into dose finding and even request certain study designs and methods 16

17 Agenda What is the problem? Dose finding requirements Dose finding approaches Challenges Conclusion 17

18 Dose finding approaches in Phase I Most common objective Identification of the maximum tolerated dose (MTD) Most frequently used study design 3+3 design (and its modifications) are used since decades Alternatives Accelerated titration design Adaptive dose finding designs incl. Bayesian model based methods (e.g. continual reassessment method) 18

19 Source: 19

20 Agenda What is the problem? Dose finding requirements Dose finding approaches In Phase I In Phase II Challenges Conclusion 20

21 Phase II dose finding studies Standard study design Multiple, parallel dose groups Placebo controlled, sometimes also with active controll Randomized 21

22 Phase II dose finding studies Objectives Establish evidence of a dose-response relationship (proof of concept) Is there a dose related effect at all? What is the maximum effect size? What is the nature of the dose response shape? Go / no go decision to Phase III If go : Selection of optimal dose for Phase III 22

23 Phase II dose finding studies Most frequently used statistical method Pairwise comparisons Pairwise comparisons of active doses against placebo (e.g. ANOVA-based hypothesis testing or hierarchical testing) Drawback: Available information across all active doses is not considered efficiently Questions What happens in-between the doses? What is the dose-response curve? Do you want to rely on point estimates? * * * Statistically significant better than placebo, but no difference between the two Dose 23

24 Phase II dose finding studies EMA Report from Dose Finding Workshop 2014 Source: 24

25 Phase II dose finding studies Issues with pairwise comparisons Statistical testing is normally done in Phase III and requires large sample sizes Testing in Phase II with much lower sample sizes is often not adequately powered Pairwise comparisons in dose finding trials are open to by chance findings particularly if not adequately powered Often only a small number of doses is studied 25

26 Phase II dose finding studies How to improve? Model based analysis! Modeling provides more information Smoothens dose estimates Interpolation between doses Confidence intervals for quantities of interest Standardized difference to placebo Dose 26

27 Phase II dose finding studies How to improve? True shape of dose response model is typically unknown Selecting a working model may have a substantial impact on the final dose estimate Model selection using observed data needs to account for the inherent uncertainty Useful to have a unified approach combining the advantages of dose response signal testing and modeling MCP-Mod: Combination of Multiple Comparison Procedures and Modelling Standardized difference to placebo Dose 27

28 Phase II dose finding studies MCP-Mod approach Source: 28

29 Phase II dose finding studies MCP-Mod approach MCP step Testing dose response signal based on a set of candidate models Out of the significant models, the model with the best fit is selected Mod step The dose response curve is estimated using the selected model (or by model averaging of significant models) Relevant parameters like ED50 (dose that achieves 50% of the maximum achievable effect) or the Minimal effective dose (MED) can be derived 29

30 Phase II dose finding studies MCP-Mod approach Source: 30

31 MCP-Mod Example Dose 31

32 MCP-Mod Example 32

33 MCP-Mod Example Dose 33

34 MCP-Mod Example 34

35 MCP-Mod Points to consider Moderate sample sizes allow well powered MCP-Mod studies for proof of concept, i.e. for establishing a dose response relationship A meaningfull precision for dose estimates (e.g. the MED) can only be achieved with higher sample sizes There is nothing like a free lunch MCP-Mod is clearly preferable to pairwise comparisons However, the full potential is associated with higher sample sizes 35

36 MCP-Mod Points to consider Planning is important and requires a joint effort of clinicians, pharmacologists and statisticians What are candidate dose response curves? What is the dose range, e.g. the maximum dose to be included? Which doses and number of doses shall be studied? What is the minimal clinically important effect? What precision is expected, e.g. for the MED? Involves simulation studies Takes more time 36

37 Agenda What is the problem? Dose finding requirements Dose finding approaches Challenges Conclusion 37

38 Implementing proper dose finding studies Challenges Time and financial pressure Lack of experience with methods Implementation and statistical analysis 38

39 Implementing proper dose finding studies Challenges Create awareness of importance of scientifically sound and meaningful dose finding studies Overcome adherence to what has been done in the past Regulatory guidances Examples 39

40 Implementing proper dose finding studies Challenges Convince your team that its worth the additional effort Much better decision making Better regulatory acceptance Better treatments If you buy cheaply (in Phase II), you pay dearly (in Phase III)! 40

41 Agenda What is the problem? Dose finding requirements Dose finding approaches Challenges Conclusion 41

42 Conclusions Phase II dose finding studies should be designed and analysed in order to get a good understanding of the dose response relationship More dose levels and cover the entire dose range Use modelling techniques (e.g. MCP-Mod) rather than pairwise comparions Proper dose finding studies allow much better decision making We could do better in drug research, we just have to start doing it Better methods are available and strongly supported by regulatory bodies Better research in phase II will pay off 42

43 Thank you very much! Rudolf Koehne-Volland