1. Statistical considerations Drs. Jan Welink Training workshop: Assessment of Interchangeable Multisource Medicines, Kenya, August 2009

2. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 2 |2 | Statistical considerations

3. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 3 |3 | Bioequivalence The primary concern in bioequivalence assessment is to limit the risk of a false declaration of equivalence. Statistical analysis of the bioequivalence trial should demonstrate that the clinically significant difference in bioavailability is unlikely….. [WHO working document multisource (generic) pharmaceutical products: Guidelines on registration requirements to establish interchangeability, Nov. 2005]

4. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 4 |4 | Bioequivalence Reference Test 2 pharmaceutical products Bioequivalent??

5. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 5 |5 | Bioequivalence Important PK parameters AUC: area under the concentration-time curve  measure of the extent of absorption Cmax: the observed maximum concentration of a drug  measure of the rate of absorption tmax: time at which Cmax is observed  measure of the rate of absorption C max T max AUC

6. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 6 |6 | Statistical considerations How similar is similar?

7. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 7 |7 | Statistical considerations

8. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 8 |8 | Statistical considerations Statistical test should take into account… The consumer (patient) risk of erroneously accepting bioequivalence (primary concern health authorities) Minimize the producer (pharmaceutical company) risk of erroneously rejecting bioequivalence Choice: - two one-side test procedure - confidence interval ratio T/R 100 (1-2  ) -  set at 5% (90% CI)

9. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 9 |9 | Statistical considerations

10. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 10 | Statistical considerations Consumer Risk The risk of declaring two product BE when they’re not is called the ‘consumer risk’ In statistical terms, this is a Type I error –The risk of rejecting the null hypothesis when it’s true The consumer risk is set at 5%

11. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 11 | Statistical considerations Producer Risk The risk of declaring two products NOT BE when they truly are BE is called the ‘producer risk’ In statistical terms, this is a Type II error –The risk of accepting the null hypothesis when it’s false

12. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 12 | Statistical considerations The risks are related If the consumer risk is reduced, the producer risk increases In statistical terms, if you lower the acceptable risk of making a Type I error, the risk of making a Type II error increases

13. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 13 | Statistical considerations Average Bioequivalence: two drug products are bioequivalent ‘on the average’ when the (1-2α) confidence interval around the Geometric Mean Ratio falls entirely within 80-125% (regulatory control of specified limit)

14. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 14 | Statistical considerations Some International Criteria Country/RegionAUC 90% CI Criteria Cmax 90% CI Criteria Canada (most drugs)80 – 125%none (point estimate only) Europe (some drugs)80 – 125%75 – 133% South Africa (most drugs) 80 – 125%75 – 133% (or broader if justified) Japan (some drugs)80 – 125%Some drugs wider than 80 – 125% Worldwide (WHO)80 – 125%“acceptance range for Cmax may be wider than for AUC”

15. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 15 | Statistical considerations

16. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 16 | Statistical considerations Least Square Means from ANOVA t-statistic with 0.05 in one tail Standard Error

17. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 17 | Statistical considerations BE Limits The concept of the  20% difference is the basis of BE limits (goal posts) If the concentration dependent data were linear, the BE limits would be 80-120% On the log scale, the BE limits are 80-125% The 90%CI must fit entirely within specified BE limits e.g. 80-125%

18. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 18 | Statistical considerations Variables..: Log transformation: –For all concentration dependent pharmacokinetic variables (AUC and Cmax) Analysis of log-transformed data by means of ANOVA (analysis of variance) –includes usually formulation, period, sequence or carry-over, and subject factors –parametric test (normal theory)

19. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 19 | Statistical considerations The sources of variance in the model are –Product –Period –Sequence –Subject (Sequence) –Residual variance These account for all the inter-subject variability This estimates Intra-subject variability

20. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 20 | Statistical considerations The width of the 90%CI depends on –The magnitude of the WSV (ANOVA-CV (residual variance) ) –The number of subjects in the BE study The bigger the WSV (within- or intra-subject variability), the wider the CI If the WSV is high, more subjects are needed to give statistical power compared with when the WSV is low

21. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 21 | Statistical considerations ANOVA CV intra-subject variability unexplained random variability subject by formulation interaction analytical variability

22. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 22 | Statistical considerations 80 100 125

23. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 23 | Statistical considerations why log-transformation:

24. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 24 | Statistical considerations Why parametric testing and not non-parametric: applicant: after log transformation not normal distributed! based upon test for normality, however these are insensitive and it concerns a small study normally after log transformation AUC and Cmax are normal distributed reason for non-normality should be explained

25. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 25 | Outliers  ‘Outliers’ FDefinition: ♦aberant/irregular values (e.g. no plasma concentration, ‘late’ high concentrations….)

26. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 26 | Outliers  ‘Outliers’ FExplanation: ♦ vomiting? ♦ non-compliant volunteers? ♦ bioanalytical failure? ♦ individual pharmacokinetics? ♦ protocol violations? ♦ ……

27. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 27 | Outliers  ‘Outliers’ FHandling: ♦“…pharmacokinetic data can only be excluded based on non-statistical reasons that have been defined previously in the protocol. ♦Exclusion of data can never be accepted on the basis of statistical analysis or for pharmacokinetic reasons alone, because it is impossible to distinguish between formulation effects and pharmacokinetic effects. ♦Results of statistical analyses with and without the excluded subjects should be provided.” (excerpt from Q&A Doc Ref: EMEA/CHMP/EWP/40326/2006)

28. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 28 | Power calculation

29. Assessment of Interchangeable Multisource Medicines, Kenya, August 2009 29 | End