We are pleased to announce that the Food and Drug Administration (FDA) and the International Society of Pharmacometrics (IsoP) will jointly convene a workshop on model informed drug development for oncology products as part of a series of workshops to identify best practices for model informed drug development (MIDD), in accordance with section I of the PDUFA VI Performance Goals (Ensuring the Effectiveness of the Human Drug Review, part J, Enhancing Regulatory Decision Tools to Support Drug Development and Review).
The workshop will take place on February 1, 2018, at the FDA White Oak Campus in Silver Spring, MD, USA between 8.00am and 5.20pm, and is co-chaired by Yaning Wang and Amy McKee from FDA, and René Bruno and Jin Y Jin from ISoP.
Full details, a draft agenda and a registration form are available at https://www.fda.gov/Drugs/NewsEvents/ucm589449.htm. Registration is free but mandatory, and seats are limited, so please let us know if you’re coming as soon as possible! FDA will provide a free-of-charge, live webcast of this workshop for those not able to attend in person. We hope you’ll join us!
Over the past few decades, there has been extensive investment in oncology drug discovery and development. Despite greater understanding of disease biology and drug mechanisms of action, further progress in model-informed strategies is needed to continue advancements in oncology drug development. Innovations in clinical trial design utilizing more informative endpoints could help bring more effective treatment options to cancer patients faster by accelerating development of effective new drugs and reducing failure rates in expensive late-phase development.
As more effective and complex combination strategies and novel targets for cancer treatment evolve, exploring more informative and predictive endpoints to assess treatment response (e.g., response evaluation criteria in solid tumors- based endpoints (RECIST)) has become an active area of research. Alternative metrics that require shorter periods of observation or provide more precise assessment of treatment effects could lead to more rapid completion of clinical trials and require fewer patients. Promising among these alternative metrics are model-based metrics, such as those based on longitudinal continuous tumor size measurements. Additionally, model-informed approaches can help satisfy a need to optimize dosing regimens for patients. Investigations to refine dosing regimens often occur after new drug approval and/or are driven by pharmacometric modeling approaches. There is growing interest in using model-informed approaches to help balance the risks and benefits of oncology products by identifying optimal dosing regimens and broad stakeholder engagement and discussion around this topic can be beneficial.
- Discuss “best practices” in integrating human pharmacokinetic, pharmacodynamic, efficacy, and safety data into models that best inform oncology drug development.
- Describe novel imaging techniques and diagnostic and predictive biomarkers that may be utilized in oncology drug development.
- Describe disease- and mechanism-specific early endpoints to predict long-term efficacy.
- Evaluate the potential to shift from traditional RECIST-based endpoints such as Overall Response Rate (ORR) and Progression Free Survival (PFS) to modified RECIST approaches (e.g. imRECIST for immunotherapies) as well as to other (model-based) tumor kinetic metrics to support early decision making in Phase 1/2 as well as in confirmatory trials.
- Discuss potential regulatory implications of model-informed decisions in drug development, including, model-based target identification, dose/exposure justification based on preclinical evidence, dose selection for first-in-human trials, quality by design, early clinical study design, dose finding/titration, confirmatory trials, product labeling, and post-marketing studies.
Jin Jin & René Bruno
International Society of Pharmacometrics