  The conventional more-is-better dose selection paradigm, which targets the
maximum tolerated dose (MTD), is not suitable for the development of targeted
therapies and immunotherapies as the efficacy of these novel therapies may not
increase with the dose. The U.S. Food and Drug Administration (FDA) has
launched Project Optimus "to reform the dose optimization and dose selection
paradigm in oncology drug development", and recently published a draft guidance
on dose optimization, which outlines various approaches to achieve this goal.
One highlighted approach involves conducting a randomized phase II trial
following the completion of a phase I trial, where multiple doses (typically
including the MTD and one or two doses lower than the MTD) are compared to
identify the optimal dose that maximizes the benefit-risk tradeoff. This paper
focuses on the design of such a multiple-dose randomized trial, specifically
the determination of the sample size. We propose a MERIT (Multiple-dosE
RandomIzed Trial design for dose optimization based on toxicity and efficacy)
design that can be easily implemented with pre-calculated decision boundaries
included in the protocol. We generalized the standard definitions of type I
error and power to accommodate the unique characteristics of dose optimization
and derived a decision rule along with an algorithm to determine the optimal
sample size. Simulation studies demonstrate that the resulting MERIT design has
desirable operating characteristics. To facilitate the implementation of the
MERIT design, we provide software, available at www.trialdesign.org.
