Independent Action Models and Prediction of Combination Treatment Effects for Response Rate, Duration of Response and Tumor Size Change in Oncology Drug Development

TL;DR

This paper introduces simple predictive models based on independent action concepts to forecast the efficacy of combination cancer therapies for early endpoints like response rate, tumor size change, and duration of response, aiding drug development.

Contribution

It extends independent action models to predict combination effects on early endpoints, providing practical tools for oncology drug development decision-making.

Findings

Models accurately predict combination effects from monotherapy data.

Application to early endpoints improves decision-making in oncology.

Facilitates efficient development of combination therapies.

Abstract

An unprecedented number of new cancer targets are in development, and most are being developed in combination therapies. Early oncology development is strategically challenged in choosing the best combinations to move forward to late stage development. The most common early endpoints to be assessed in such decision-making include objective response rate, duration of response and tumor size change. In this paper, using independent-drug-action and Bliss-drug-independence concepts as a foundation, we introduce simple models to predict combination therapy efficacy for duration of response and tumor size change. These models complement previous publications using the independent action models (Palmer 2017, Schmidt 2020) to predict progression-free survival and objective response rate and serve as new predictive models to understand drug combinations for early endpoints. The models can be applied to predict the combination treatment effect for early endpoints given monotherapy data, or to estimate the possible effect of one monotherapy in the combination if data are available from the combination therapy and the other monotherapy. Such quantitative work facilitates efficient oncology drug development.