Improving Dose-Finding for New Agents as Monotherapy and Add-On Therapy

Abstract

ABSTRACT With the recent advancement in immuno-oncology, next-stage early oncology development is focusing on identifying the best combinations of established immunotherapies with new agents to either overcome drug resistance or achieve synergic effects. Although the combination is the focus, safety profile of the new agent alone must be explored. Therefore, many trials have both monotherapy and add-on combination therapy arms. Finding the maximum tolerable dose (MTD) for the new agent in both arms is critical. Traditional oncology dose-finding methods and MTD estimation algorithm do not handle the correlation and interplay between the two arms and the selected MTDs may contradict with each other. To overcome these issues, we applied a two-dimensional pool-adjacent-violators algorithm to MTD estimation and modified the standard Bayesian optimal interval design (BOIN) to allow for information flow between arms during dose-finding. We also showed that a naïve adaptation of standard BOIN that is much simpler to implement demonstrated empirically similar performance. These new approaches were assessed with simulations and demonstrated improvement for trials with both monotherapy and add-on combination therapy arms. Albeit proposed in the context with immunotherapy as the backbone drug, our approaches can be applied to any new agent in combination with a fixed dose of another drug. Supplementary materials for this article are available online.