Clinical trial design in the current age of immunotherapy and - PowerPoint PPT Presentation

Clinical trial design in the current age of immunotherapy and targeted therapy Martijn Lolkema, MD/PhD Medical Oncologist Erasmus MC Cancer Institute

Content  Clinical trial design: the old paradigm  The challenges posed by immunotherapy  The challenges posed by targeted therapy  How to deal with the exploding trial portfolio

CLINICAL TRIAL DESIGN: THE OLD PARADIGM

Drug development in oncology Oncology Drug Development Preclinical hypothesis/ compound generation Phase I Phase II Phase III/IV

Phase I studies  Dose selection  Toxicity determination  PK analysis  PD analysis

Phase I: dose selection

PK = Pharmacokinetics  What does the body do to the drug?

PD = Pharmacodynamics  What does drug to its target?

Phase II study

Phase 3 studies Standard of care R (Standard of care +) novel treatment

Conclusies

HOW TO TACKLE THE MOST IMPORTANT PROBLEMS IN ONCOLOGY DRUG DEVELOPMENT

There are >900 drugs in development Only 5% of novel drugs in cancer treatment become FDA/EMA approved Success rate 100% x x x = ~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

Where should we look for improvements?

Success in phase I essential, phase II less important 100 75 %Change From Baseline 50 (Sum of Lesion Size) 25 0 -25 -50 -75 Onderzoeker bepaald -100 Inclusief bevestigde & onbevestigde tumorrespons

How to improve translation  Efficacy/ Efficacy/ Efficacy Adjust the clinical trial paradigm

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

Fase II onderzoek Traditional Modern Phase III Phase II Phase I

Focussed phase 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.

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

Patient Centered studies Patient population: Verkoop In study In study A TEST Patient In study B etc In study X

Basket and Umbrella studies

SOME THOUGHTS ON BIOMARKERS AND PHARMACODYNAMICS

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

Biomarkers: I-SPY trial an example of how to perform biomarker studies Rugo HS et al. N Engl J Med 2016;375:23-34.

Results from I-SPY study: Her2 negative patients were selected for randomization Rugo HS et al. N Engl J Med 2016;375:23-34.

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

The strength of Bayesian statistics

Conclusion on I-SPY trial  Well-designed studies that include biomarker based stratification and randomization are essential in determining predictive biomarkers  Early and well-defined outcome variable are essential in producing results that can be interpreted  BUT: we need confirmation in a phase III trial…….

MSI: the first approved context independent, predictive biomarker

Anti-PD1 in MSI high patients

Why is MSI the first?  Strong biological rationale (Lynch syndrome/ high immune infiltrate/ high mutational load)  Can be detected easily (routine diagnostics exist/ IHC and PCR based)  Correlation with response robust among different tumor types Biology over ontology!

So do we incorporate PD/ biomarker research in all early phase trials? Sweiss et al JCO 2016

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

Biomarkers in clinical practice  If you add invasive procedures: make them obligatory so you get the numbers  Think about ways to obviate the need for invasive procedures  The best place to do this would be at the end of phase I studies.  Once you have a biomarkers make sure you get the patient numbers

Overall conclusions  Old fashioned oncology drug development paradigm is linear in its thinking  Biggest problem we face in oncology drug development is the lack of early signs of efficacy  The trial design has developed into a more parallel thinking model: early studies gain in impact  Selection is the main item: we need to use better algorithms to select our patients for treatment

Thank you for your attention