The ASA Biopharmaceutical Section Statistical Methods in Oncology Scientific Working Group and the LUNGevity Foundation organized in coordination with the US FDA Oncology Center of Excellence four forums on dose-optimization studies. Discussions at these forums were focused on statistical considerations in designing dose-optimization studies of products for treatment of cancer patients at pre- and post-approval stages. Several appealing ideas and methods were proposed and discussed at these forums. Although a consensus was not achieved on every point, speakers and panelists agreed that we should use better design options and strategies. The main ideas and discussion points from these forums will be summarized and reviewed in this presentation.

Oncology drugs are generally quite toxic and their toxicity is assumed to increase with dose. However, in many new immuno-oncology drugs, the efficacy cannot be assumed to increase with dose but may plateau with dose. Hence finding an optimal dose for safety and efficacy i.e. a dose of the drug that is not too toxic and is not sub-therapeutic is critical. This is why dose finding studies constitute a very important part of the drug development cycle in oncology. Many early phase oncology dose finding designs have been proposed to determine the dose of the study drug that can be used in later phase trials, resulting in a bewildering array of options. The traditional 3+3 design in oncology is a simple algorithm/rule-based design but several other algorithm-based, model-assisted and model-based frameworks for dose finding have been proposed more recently. We conduct a review of the current popular oncology dose finding frameworks, discuss their benefits and downsides, and compare them. We provide an overview of the options and a clear, concise set of guidelines to consider the dose finding frameworks and choose the design that best fits the needs of the current trial.

Efficient dose finding and optimization in general population and an individual patient have always been a critical issue of drug (including oncology drug) development. With advances in cancer biology and new molecular targeted agents and immunotherapies, pressing need for an improved oncology drug dose finding and optimization strategy has been highlighted, as demonstrated particularly by the recent Project Optimus from the FDA. The new strategy will require a multi-disciplinary collaboration to integrate all available nonclinical and clinical information, including pharmacokinetic (PK), pharmacodynamic (PD), activity or efficacy, safety and tolerability, and patient-disease-trial factor impacts and an understanding of dose- and exposure-response relationships for safety and efficacy. This presentation will provide an overview of current landscape of dose finding and optimization in the oncology drug development. A pragmatic and holistic approach integrating the totality of evidence at different stage of drug development for dose selection and optimization for general or specifical population will be discussed and illustrated using representative case examples.