Regulatory aspects and review - PowerPoint Presentation

1. Regulatory aspects and review of EMA authorized biosimilarsSession “Biosimilar Development”, 15 MayJohanna Mielke, Bernd Jilma, Franz Koenig, Byron JonesFranz KönigMedical University of ViennaSection of Medical StatisticsFranz.Koenig@meduniwien.ac.atwww.meduniwien.ac.athttp://www.ideas-itn.eu/Session

2. Acknowledgements & Disclaimer2This project has received funding by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 999754557 (Novartis: JM, BJo) and from the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 633567 (MUW: FK, BJi). The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Swiss Government and should not be linked to any affiliations the authors are associated with. http://www.ideas-itn.eu/

3. Introduction: BIOSIMILAR“A biosimilar medicine is a biologicalmedicine that is developed to be similarto an existing biological medicine(the ‘reference medicine’). [...]When approved, its variabilityand any differences between it andits reference medicine will havebeen shown not to affect safety oreffectiveness.”3Source: Christian Schneider, Chair EMA Biosimilar Working Party: http://www.ema.europa.eu/docs/en_GB/document_library/Medicine_QA/2009/12/WC500020062.pdf

4. QuestionsWhich type of clinical trials have to be undertaken for getting approval in Europe?How much and in which way do the development programs differ?Is there a unified approach for biosimilars with the same active substance?How close are the studies in the submitted applications following the recommendations in the EMA guidelines?How is multiplicity addressed when planning and analyzing biosimilar trials?4

5. Main Data SourceEuropean Public Assessment Reports (EPAR)5Available online at http://www.ema.europa.eu Detailed information about the application:Drug: active substance, indications, ...Non-clinical: toxicology, ...Clinical development program: study design, endpoints, sample size, ...EMA leading agency with 28 approved biosimilars on 11 different biologics (April 2017)Review conducted in June 2016 (Mielke et al., 2016)

6. Methods: EPARs analysedReview based on 21 approved biosimilars on 7 different biologics (June 2016)Focused on approved biosimilars (no refused, no withdrawn products)Sponsors collaborated & submitted identical clinical trials,but products were marketed separately Example: biosimilar to active substance epoetin zetaSilapo (Stada Arzneimittel AG) - Retacrit (Hospira UK Ltd)  13 different applications6

7. MethodsComparison of the submitted applications in terms ofSample size/Number of clinical trialsTrial designEndpointsStatistical modelsEquivalence marginsApproved indications, extrapolation to other indications7

8. Overview of results8First Biosimilar in 2006

9. Sample size PK/PD vs. Phase IIIPK/PD trials1-5 trials24-269 subjectsPhase III1-3 trials120-1295 subjects9Number of PK/PD trialsNumber phase III trials

10. Sample size PK/PD vs. Phase III10Epoetin Alfa/ZetaFilgrastimInfliximabFollitropin AlfaOthers

11. Sample size PK/PD vs. Phase III11Epoetin Alfa/ZetaFilgrastimInfliximabFollitropin AlfaOthers

12. Trial designPK/PDGuidelines: 2x2 crossover, mostly followedExceptions: Remsima/Inflectra (parallel groups design, but was allowed in product specific guideline)Epoetin Alfa Hexal/Abseamed/Binocrit (pivotal PK/PD is a parallel groups design, contradicts product specific guideline)Phase IIIParallel groups design recommended, followed Exceptions Zarzio/Filgrastim Hexal and Grastofil/Accofil (single arm design, but accepted in product specific guideline)12

13. Endpoints, equivalence margins & statistical models: PKMetrics for bioequivalence testing: AUC, CmaxApproach: calculation of geometric mean ratio with confidence intervals, if confidence intervals fully lie within pre-specified limits bioequivalenceRecommendation in guideline for PK studies: Equivalence margins: 80-125%90% confidence intervalsMostly followed, exceptions:Silapo/Retacrit: wider equivalence range for CmaxOvaleap, Benepali: no details given in EPAR and publication, unclear if formal testing was done13

14. Endpoints, equivalence margins & statistical models: PKIf criteria are not fully fulfilled, approval is possible: Example Zarzio/Filgrastim Hexal:PK/PD-studies in five different doses, for lower doses and after multiple subcutaneous doses: AUC and Cmax not within limitsSponsor claimed “differences in level of purity”  adjustment to doses Nonetheless, for three settings outside of equivalence regionSponsor provided modelling results and explanations for mechanism of action  approval14

15. Endpoints, equivalence margins & statistical models: PK15Grastofil/Accofil: Study KWI-300-101

16. Endpoints, equivalence margins & statistical models: PK16“The location and the width of the confidence interval should also be taken into account in the interpretation of similarity. For example, statistically significant differences in 90% CIs within the justified acceptance range regarding relevant PK parameters would need to be explained and justified as not to preclude biosimilarity. On the other hand, if the 90% CI crosses the prespecified boundaries the applicant would need to explain such difference and explore root causes.”Source: http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2015/01/WC500180219.pdf

17. Endpoints, equivalence margins & statistical models: PD173 applications without any PD assessmentEndpoints are drug specificEquivalence margins: 80-125% or narrowerExample Epoetin Alfa Hexal/Abseamed/Binocrit: “the acceptance range was then changed to 97–103% by protocol amendment based on haemoglobin (Hb) concentration changes defined as equivalence margins in Phase III studies”Similarly to PK, approval is possible if not all endpoints meet the target

18. Endpoints, equivalence margins & statistical models: Phase IIIEndpoint, margins, statistical models are disease specificMargins: no explicit explanation for choice n in publications and EPARMainly one primary endpointOnly few exceptions (with 2 and 4 primary endpoints)No multiplicity adjustment in EPARs mentioned18

19. Endpoints, equivalence margins & statistical models: Phase III19

20. Endpoints, equivalence margins & statistical models: Phase III20Endpoint, margins, statistical models are disease specificVariation within a substance: Ovaleap and Bemfola (follitropin alfa)Same endpoint used (number oocytes retrieved)Slightly different equivalence marginsStatistical methodsOvaleap: Zero-inflated Poisson (ZIP) regression modelBemfola: Mann-Whitney TOST or Schuirmann’s TOST (data dependent) Flexibility for the sponsors how to analyse the data

21. Indication & ExtrapolationPhase III in one indication only, but approval in all indications of the reference product  ExtrapolationOnly in 2 out of 13 applications, the approved indications are not essential identical to the one of the reference productExample for not all indications granted: Silapo/Retacrit “Reduction of allogeneic blood transfusions in adult non-iron deficient patients prior to major elective orthopaedic surgery” was not grantedReason: lack of shown equivalence for the subcutaneous administration route in Phase III21

22. Indication & ExtrapolationExample of successful extrapolation: Remsima/InflectraOne Phase III trial in patients with active rheumatoid arthritisAccording to the EPAR, the sponsor provided: A literature review of the therapeutic indication and also of the mechanism of action of the drug Preliminary data on 23 patients with either Crohn's disease or ulcerative colitis Additional post-marketing trials were promised Licensed for all indications of the reference product (rheumatoid arthritis, ankylosing spondylitis, psoriatic arthritis, psoriasis, adult and paediatric Crohn's disease and adult and paediatric ulcerative colitis)22

23. MultiplicityMultiple hypothesis tests several doses, routes of administration (IV, SC), different populations, endpoints (e.g.,Cmax, AUC), …If ALL test must be significant, NO adjustment neededBUT – not always all tests have been statistically significant.What about defining the success criteria differently? ”success”: k out of m tests are statistically significantWhat is the impact on sample sizes needed?PSI Conference 201723

24. For k out of m: which multiple testing strategy?Bonferroni (might be too conservative, but controls FWER)No adjustment (inflation of FWER for k<m)Or aim at controlling a different error rate instead of FWER: the k-FWERk-FWER = P(reject at least k true null hypothesis, irrespectively which and how many are true null)k-FWER adjustment:  24Lehmann & Romano (2005), Hommel & Hoffmann (1998), Victor (1982)

25. ResultsPSI Conference 201725

26. ResultsPSI Conference 201726

27. ResultsPSI Conference 201727

28. ResultsPSI Conference 201728

29. ResultsPSI Conference 201729

30. EPARsVery helpful to evaluate regulatory standardsEven more helpful if reports were more standardizedLength (25p – 105p)Depth of information differsUnified structure (e.g., including overview tables on PK/PD trials)All crucial information should be included (e.g., explanation for choice of margins) EPARs should be linked to other EMA transparency initiativesE.g., EudraCT should be mentioned for all trials mentioned in EPARPSI Conference 201730

31. ConclusionsHigh variability between submitted trials High variety also within an active substance  case by case decision of the regulatorsRecommendation in product specific guidelines and overarching guidelines were mostly followed, but also exceptionsAlign sample sizes for multiple tests and success criteriaIt is possible to gain approval even though not all pre-specified primary endpoints meet the targetBusiness Use Only31

32. ReferencesMielke, J., Jilma, B., Koenig, F., & Jones, B. (2016). Clinical trials for authorized biosimilars in the European Union: a systematic review. British Journal of Clinical Pharmacology, 82(6), 1444-1457.OPEN ACCESS: http://dx.doi.org/10.1111/bcp.13076Mielke, J., Jones, B., Jilma, B., & Koenig, F. (2017). Sample Size for multiple hypothesis testing in biosimilar development. Submitted.32

33. This project was supported by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 999754557. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Swiss Government. The project is part of the IDEAS European training network (http://www.ideas-itn.eu/) from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 633567.