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Adaptive clinical trials in oncology

Nature Reviews Clinical Oncology volume 9, pages 199–207 (2012)Cite this article

Abstract

Modern oncology drug development faces challenges very different from those of the past and it must adapt accordingly. The size and expense of phase III clinical trials continue to increase, but the success rate remains unacceptably low. Adaptive trial designs can make development more informative, addressing whether a drug is safe and effective while showing how it should be delivered and to whom. An adaptive design is one in which the accumulating data are used to modify the trial's course. Adaptive designs are ideal for addressing many questions at once. For example, a single trial might identify the appropriate patient population, dose and regimen, and therapeutic combinations, and then switch seamlessly into a phase III confirmatory trial. Adaptive designs rely on information, including from patients who have not achieved the trial's primary end point. Longitudinal models of biomarkers (including tumor burden assessed via imaging) enable predictions of primary end points. Taking a Bayesian perspective facilitates building an efficient and accurate trial, including using longitudinal information. A wholly new paradigm for drug development exemplifying personalized medicine is evinced by an adaptive trial called I-SPY2, in which drugs from many companies are evaluated in the same trial—a phase II screening process.

Key Points

  • Adaptive clinical trial designs can make oncology drug development more informative, more accurate, and shorter

  • Adaptive designs are ideal for addressing many questions at once; a single trial might identify the appropriate patient population, dose and regimen, and therapeutic combinations

  • Seamless phase I–II and phase II–III trials can shorten the duration of a drug's development

  • The potential benefits of adaptive designs are greatest in complicated settings exemplified by personalized medical research

  • Modeling longitudinal information from individual patients is an important aspect of adaptive clinical trials in oncology

  • A Bayesian statistical approach facilitates building complicated but maximally informative clinical trials

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Figure 1: Possible dose combinations in a seamless phase I–II trial addressing agents A and B given concurrently and sequentially.33
Figure 2: A seamless phase II–III trial to evaluate two experimental drugs alone and in combination.
Figure 3: Therapeutic regimens followed in I-SPY2.

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Authors and Affiliations

  1. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, 4-5062 Pickens Academic Tower, Houston, 77030–1402, TX, USA

    Donald A. Berry

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Competing interests

D. A. Berry declares that he is a stock holder at Berry Consultants. Berry Consultants designs adaptive Bayesian clinical trials in all therapeutic areas for pharmaceutical and medical device companies, and for US NIH co-operative groups.

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Berry, D. Adaptive clinical trials in oncology. Nat Rev Clin Oncol 9, 199–207 (2012). https://doi.org/10.1038/nrclinonc.2011.165

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