Future directions in translating basic science into clinical studies

1. Future directions in translating basic science into clinical studies Martijn Lolkema, MD/PhD MedicalOncologist Erasmus MC Cancer Institute

2. Content Pitfalls in target identification and trial design How to tackle the most important problems Somethoughts on biomarkersandpharmacodynamics

3. Pitfalls in target identification

5. Drug development in oncology Oncology Drug Development Preclinical hypothesis/ compound generation Phase I Phase II Phase III/IV Patient with cancer Beyond Standard of Care Standard of Care Diagnosis

6. Fase I studies: Target identification

7. Pitfalls in target identification

8. STOP KrasLSL.G12D G12D * Kras I II III IVa IVb STOP p53LSL·R172H R172H * AUG p53 I II III IV V VI VII VIII IX X XI PdxCre Cre Pdx Pro. tg Predictive nature of pre-clinical research: example of the best available evidence KPC

9. KPC mice develop of spectrum of lesions identical to human PDA Wild typePanIN1PanIN2PanIN3PDA KRAS 0 35 ND 86 95 CDKN2A 0 24 55 71 95 TP53 0 0 ND 21 75 DPC4 0 0 0 31 75 Mouse Human

10. % Initial Volume Abdominal tumors can be quantified high resolution ultrasonography Endpoints: ill health, >20% weight loss or ascites 2-6 months: Palpate abdomen to detect mass Ultrasound: 6-9mm tumours eligible

11. Smoothened inhibition facilitates gemcitabine delivery and extends survival K. P. Olive et al., Science 324, 1457 -1461 (2009) Published by AAAS

12. Predictive nature of pre-clinical research: clinical outcome

13. Why aren’t we doing better in translating science to the benefit of patients ? By CARL ZIMMER, April 16, 2012 April 5, 2012

14. Conclusions Preclinical studies needto more rigorous, endpointsneedtobevalidatedandbecome as predictive as possibleif we want to base clinical trial on these data. Notevery target is validand we needto accept clinical trials mayfail: “theproof of the pudding is in theeating”

15. How to tackle the most important problems

17. % x x x = There are >900 drugs in development Only 5% of novel drugs in cancer treatment become FDA/EMA approved Success rate 100% ~30% ~40% ~70% ~5% ~60% 90 80 70 60 50 40 30 20 10 0 Phase I Phase II Phase III Registration Overall Phases in the drug development process SOURCE: I. Kola, J. Landis “Can the pharmaceutical industry reduce attrition rates?” Nature Reviews drug discovery, ‘04

18. Whereshould we look forimprovements?

19. Success in phase I essential, phase II less important • Onderzoeker bepaald • Inclusief bevestigde & onbevestigde tumorrespons

20. How toimprovetranslation Adjusttheclinical trial paradigm Efficacy/ Efficacy/ Efficacy

21. Drug development in oncology Efficacy Safety Preclinical hypothesis/ compound generation Phase I Phase II Phase III/IV

22. Fase II onderzoek Traditional Modern Phase III Phase II Phase I

23. Focussedphase I trials Proof of concept! Kwak EL, et al. N Engl J Med. 2010;363:1693-703. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. After screening tumor samples from approximately 1500 patients with non–small cell lung cancer for the presence of ALK rearrangements, we identified 82 patients with advanced ALK-positive disease The overall response rate was 57%; 27 patients (33%) had stable disease. A total of 63 of 82 patients (77%) were continuing to receive crizotinib at the time of data cutoff, and the estimated probability of 6-month progression-free survival was 72%, with no median for the study reached.

24. Challenges in performing these studies All cancer patients without standard treatment options Disease and Mutation specific All-comer Disease specific Mutation specific

25. Challenges in thenovel trial paradigm Findingthe right population of patientswith tests that are outside of the standard of care Findingthe right balancebetween hope andreality: whatmaypatientsexpectfrom a trial Managing a trial unit: howmany different trials do youneedto open toaccomodateallpatients

26. Findingthe right population • Making sureallpatientsthat want toparticipate in studies canbereferred (Localnetwork) • Optimizeuse of genomic data available (CPCT) • Making surethe trial portfolio in large academic centers accomodatesmany different patientpopulations (Size of the unit)

27. Understanding patients that enter phase I studies Lack of standard therapy: pursue studies or symptom oriented care contemplation First visit: discuss phase I study proposal information Predecisional period Second visit: sign informed consent to phase I study decision

28. Balancing hope andexpectation

29. Response in phase I studies Elizabeth Horstmann, B.A. et all. N Engl J Med 2005; 352:895-904

30. Building a large phase I unit Logistics of phase I trials are increasinglybecoming a burden Allprocessesfromaquisition, start-up, patient care andclosing of studyneedtobeperformed at high speed Patientscannotwaitforlongerperiodsto enter thestudythey want to

31. Ourstudy unit organisation Studylogistics Patientlogistics

32. Conclusions • The mainproblem in earlyphaseoncology drug development we face is lack of efficacy of many drugs entering theclinic. • To tackle thisproblem we are changingthephase I studyparadigmtobecome more targetedtowardsspecificpatientpopulations • For the research community/ society this means: • Findingthe right patients is notthat easy anymore • Explainingthe benefits vsburden is more difficult • We needlargersize units toexecute these trials

33. Somethoughts on biomarkersandpharmacodynamics

34. RCT Targeted therapy placebo Active agent 50% response can be detected easily! Patient population RCT Chemotherapy placebo Active agent 5% response cannot be detected, but: 50% response in the blue dots could!

35. Biomarkers: I-SPY trial anexample of howtoperformbiomarker studies Rugo HS et al. N Engl J Med 2016;375:23-34.

36. Resultsfrom I-SPY study: Her2 negativepatientswereselectedforrandomization Rugo HS et al. N Engl J Med 2016;375:23-34.

37. Outcome: based on pathologic complete response Rugo HS et al. N Engl J Med 2016;375:23-34.

38. Conclusion on I-SPY trial Well-designed studies thatincludebiomarkerbasedstratification and randomization are essential in determiningpredictivebiomarkers Early and well-definedoutcomevariable are essential in producingresultsthatcanbeinterpreted BUT: we needconfirmation in a phase III trial…….

39. MSI: the first approved context independent, predictivebiomarker

40. Anti-PD1 in MSI high patients

41. Why is MSI the first? Biology over ontology! Strong biological rationale (Lynch syndrome/ high immune infiltrate/ high mutational load) Canbedetectedeasily (routine diagnosticsexist/ IHC and PCR based) Correlationwith response robustamong different tumor types

42. So do we incorporate PD/ biomarker research in allearlyphase trials? Sweiss et al JCO 2016

43. Impact of biopsies A statistically significant biomarker result was reported in 17% of studies (n = 12) Sweiss et al JCO 2016

44. Biomarkers in clinicalpractice Ifyouaddinvasive procedures: make themobligatorysoyou get thenumbers Thinkaboutwaystoobviatetheneedforinvasive procedures The best placeto do thiswouldbe at the end of phase I studies. Onceyou have a biomarkers make sureyou get thepatientnumbers

45. Overall conclusions We need more real predictivebiomarkers We needtorealizetheroadtocommercialization of a biomarker is as long as for a drug Real biomarkersimprove care forpatients Choosethe right time toaskpatientsundergoinvasive procedures; make sureyourefforts matter!

46. Dank voor uwaandacht