A Model-Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in Oncology.

Abstract

The primary purpose of an oncology dose-finding trial for novel anticancer agents has been shifting from determining the maximum tolerated dose to identifying an optimal dose (OD) that is tolerable and therapeutically beneficial for subjects in subsequent clinical trials. In 2022, the FDA Oncology Center of Excellence initiated Project Optimus to reform the paradigm of dose optimization and dose selection in oncology drug development and issued a draft guidance. The guidance suggests that dose-finding trials include randomized dose-response cohorts of multiple doses and incorporate information on pharmacokinetics (PK) in addition to safety and efficacy data to select the OD. Furthermore, PK information could be a quick alternative to efficacy data to predict the minimum efficacious dose and decide the dose assignment. This article proposes a model-based trial design for dose optimization with a randomization scheme based on PK outcomes in oncology. A simulation study shows that the proposed design has advantages compared to the other designs in the percentage of correct OD selection and the average number of patients assigned to OD in various realistic settings.