An information-theoretic Phase I/II design for molecularly targeted agents that does not require an assumption of monotonicity

TL;DR

This paper introduces a new Phase I/II clinical trial design for molecularly targeted agents that does not rely on monotonicity assumptions, effectively handling complex dose-efficacy relationships and combination schedules.

Contribution

The authors develop a novel efficacy-toxicity trade-off based design that accurately selects regimens without parametric or monotonicity assumptions, suitable for complex molecularly targeted agent trials.

Findings

Effective regimen selection without monotonicity assumptions

Applicable to complex combination-schedule trials

Addresses practical issues like delayed responses and safety constraints

Abstract

For many years Phase I and Phase II clinical trials were conducted separately, but there was a recent shift to combine these Phases. While a variety of Phase~I/II model-based designs for cytotoxic agents were proposed in the literature, methods for molecularly targeted agents (TA) are just starting to develop. The main challenge of the TA setting is the unknown dose-efficacy relation that can have either an increasing, plateau or umbrella shape. To capture these, approaches with more parameters are needed to model the dose-efficacy relationship or, alternatively, more orderings of the dose-efficacy relationship are required to account for the uncertainty in the curve shape. As a result, designs for more complex clinical trials, for example, trials looking at schedules of a combination treatment involving TA, have not been extensively studied yet. We propose a novel regimen-finding design which is based on a derived efficacy-toxicity trade-off function. Due to its special properties, an accurate regimen selection can be achieved without any parametric or monotonicity assumptions. We illustrate how this design can be applied in the context of a complex combination-schedule clinical trial. We discuss practical and ethical issues such as coherence, delayed and missing efficacy responses, safety and futility constraints.