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An information theoretic phase I–II design for molecularly targeted agents that does not require an assumption of monotonicity

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  • Pavel Mozgunov
  • Thomas Jaki

Abstract

For many years phase I and phase II clinical trials have been conducted separately, but there has been a recent shift to combine these phases. Although a variety of phase I–II model‐based designs for cytotoxic agents have been proposed in the literature, methods for molecularly targeted agents (TAs) are just starting to develop. The main challenge of the TA setting is the unknown dose–efficacy relationship that can have either an increasing, plateau or umbrella shape. To capture these, approaches with more parameters are needed or, alternatively, more orderings are required to account for the uncertainty in the dose–efficacy relationship. As a result, designs for more complex clinical trials, e.g. trials looking at schedules of a combination treatment involving TAs, have not been extensively studied yet. We propose a novel regimen finding design which is based on a derived efficacy–toxicity trade‐off function. Because of 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.

Suggested Citation

  • Pavel Mozgunov & Thomas Jaki, 2019. "An information theoretic phase I–II design for molecularly targeted agents that does not require an assumption of monotonicity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 68(2), pages 347-367, February.
  • Handle: RePEc:bla:jorssc:v:68:y:2019:i:2:p:347-367
    DOI: 10.1111/rssc.12293
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    Cited by:

    1. Kasianova, Ksenia & Kelbert, Mark & Mozgunov, Pavel, 2021. "Response adaptive designs for Phase II trials with binary endpoint based on context-dependent information measures," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    2. Pavel Mozgunov & Thomas Jaki, 2020. "An information theoretic approach for selecting arms in clinical trials," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1223-1247, December.

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