FDA’s Project Optimus Initiative for Oncology Drug Development
Oncology drugs have historically followed the dosing strategy that “more is better” until the maximum tolerated dose (MTD) is reached. This dates back to the genesis of chemotherapy. This conventional approach often requires post-marketing requirements to optimize the dose regimen with regard to safety and efficacy.
Finding the optimal dose regimen, that is, the dose level and frequency that produces a desirable benefit-risk profile with maximum clinical efficacy while maintaining acceptable safety is critical. Considering that biological and mechanistic evidence such as target engagement, receptor occupancy, or other pharmacokinetic/pharmacodynamic (PK/PD) properties are often dependent on the dose, it is particularly important to optimize the dose regimens for targeted therapies (such as kinase inhibitors) and immuno-oncology products (such as check-point inhibitors, bi-specific antibodies and T-cell redirecting agents). Since the target exposure (drug concentration) may drive the exposure-response (E-R) relationships for efficacy and safety, the optimized dose regimen could be determined by PK/PD and E-R modeling & simulations.
FDA’s Project Optimus Initiative:
The Oncology Center of Excellence’s (OCE) Project Optimus is an initiative by the Food and Drug Administration (FDA) to reform the dose optimization and dose selection paradigm in oncology drug development. The paradigm for dose selection is often based on cytotoxic chemotherapeutics, which lead to doses and schedules of molecularly targeted therapies that are inadequately characterized before initiating registration trials.
The goals for FDA’s Project Optimus are:
- To communicate expectations for dose-finding and dose optimization, through guidance documents, workshops, and public meetings,
- To provide opportunities for and encourage drug developers to meet with the FDA Oncology Review Divisions early in their development programs, well before conducting trials intended for registration, to discuss dose-finding and dose optimization, and
- To develop strategies for dose finding and dose optimization that leverage nonclinical and clinical data in dose selection, including randomized evaluations of a range of doses in trials. An emphasis of such strategies will be placed on performing these studies as early as possible in the development program and as efficiently as possible to bring promising new therapies to patients.
As the complexity of therapeutic modalities in cancer medicine continues to grow, an integrative model-informed drug development (MIDD) approach should be implemented to optimize the dose regimens for drug development for oncology products.
Points for Consideration: MIDD Approach to Support Project Optimus
Dose optimization using an MIDD approach in early clinical trials is the key to future success:
- Conduct pre-clinical research that supports a basic understanding of pharmacology and target therapeutic range. Select the target patient population using diagnostic tools as appropriate.
- Establish therapeutic target based on biomarker, target saturation, and/or translational PK/PD modeling to guide dose selection, see examples:
Translational Modeling Predicts Efficacious Therapeutic Dosing Range of Teclistamab for Multiple Myeloma of Teclistamab for Multiple Myeloma (Targeted Oncology, published on-line: 24 June 2022)
Development of Programmed Cell Death Receptor-1 (PD-1) mAbs:
Phase I Study of Pembrolizumab (MK-3475; Anti–PD-1 Monoclonal Antibody) in Patients with Advanced Solid Tumor (Clin Cancer Res; 21(19) 1 October 2015)
Nivolumab dose selection: challenges, opportunities, and lessons learned for cancer immunotherapy (Journal for Immuno Therapy of Cancer (2016) 4:72))
Pharmacokinetic-Based Criteria for Supporting Alternative Dosing Regimens of Programmed Cell Death Receptor-1 (PD-1) or Programmed Cell Death-Ligand 1 (PD-L1) Blocking Antibodies for Treatment of Patients with Cancer Guidance for Industry (The FDA’s Graft Guidance, Clinical Pharmacology/Clinical, August 2021)
- Model-based assessment to guide dose-ranging efficacy and safety assessments in early trials
- Design P1b/2 expansion with doses based on exposure-response simulations using FIH dose escalation data: Opportunities for breakthrough designation (BTD) and accelerated approval based on FIH/P1b/P2 data.
- Explore different dose-regimens based on simulations for exposure-efficacy and exposure-safety relationships
- Perform mechanism-based tumor reduction modeling analysis and disease progression modeling and simulations to forecast clinical benefit such as overall survival
Tumor Time-Course Predicts Overall Survival in Non-Small Cell Lung Cancer Patients Treated with Atezolizumab: Dependency on Follow-Up Time (CPT Pharmacometrics Syst. Pharmacol. (9) 2020)
- Choose dose regimens for the pre-registrational dose-finding study that will provide sufficient range of drug exposure: The lowest dose is the minimal dose expected to provide activity based on PK/PD analyses and the highest dose (chosen within safety allowance) is selected in consideration of whether dose increases result in increased activity with acceptable toxicity.
- Perform dose optimization early and apply MIDD approach for dose optimization in the pre-market setting to build a comprehensive scientific dose rationale to treat patients. This may prevent clinical holds from the healthy authorities, the need for additional studies later in development, or post-marketing requirements if an inadequate dose is selected.
- Engage with the FDA to discuss the dose-finding study design and dose selection approach (Pre-IND, EoP1, EoP2, etc.) in clinical development, as supported by available clinical PK, PK/PD, safety, and efficacy data.
On Wednesday, September 7, 2022 at 11am Eastern time, I will be joined by the FDA Office of Clinical Pharmacology (OCP) leaders Dr. Brian P. Booth and Dr. Hao Zhu to discuss FDA’s Project Optimus Initiative. Join us to gain critical information on:
- Why we need to optimize dose for oncology products
- Leveraging what we know
- The role of Model-Informed Drug Development (MIDD) in dose optimization
- Informative case studies
- And more
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