Patient-Specific Dose Adjustment in the Cancer Clinical Trial Setting
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Patient-Specific Dose Adjustment in the Cancer Clinical Trial Setting Andr´e Rogatko,1,2 Pulak Ghosh,1 Brani Vidakovic1 and Mourad Tighiouart1 1 2
Winship Cancer Institute, Emory University, Atlanta, Georgia, USA Cedars-Sinai Medical Center, Samuel Oschin Comprehensive Cancer Institute, Los Angeles, California, USA
Abstract
Clinical trials of new anticancer therapies are critically important tools in the search for more effective cancer treatments. According to the current paradigm for the clinical evaluation of new cancer therapies, (A) the dose of a therapeutic agent is not adjusted to accommodate individual patient differences, and (B) the exploration of a working-dose of new cancer therapies is mainly restricted to phase I trials. Rogatko et al. proposed that (A′) the dose should be finetuned using patient-specific attributes, and (B′) the search for the optimal dose should be extended beyond phase I and into phases II and III. In this paper, we discuss how phase I design methods can be used to update the working dose for phases II and III and how finetuning the dose may involve the utilization of patient-specific attributes to obtain a personalized treatment regimen. As a result, we expect that more patients will be treated with potentially therapeutic doses of promising agents and fewer patients will have to experience the detrimental effects of a toxic dose.
Dose adjustment of chemotherapeutic agents in the current treatment paradigm for cancer is empiric and does not account for individual patient differences in susceptibility to treatment effects. Typically, the working doses employed in phase II and III trials have been exclusively based on the toxicity experienced by a few heavily pretreated phase I patients, patients who have already exhausted all approved treatment options. However, recent improvements in our understanding of pharmacokinetics and the genetics of drug metabolism have made it clear that anticancer therapies need to accommodate intrinsic patient differences in drug tolerance. Such methods would adjust the dose level according to measurable patient characteristics in order to obtain an individualized target drug exposure. We therefore propose to adjust dose levels at each stage of the development process, using all available knowledge to guide these adjustments. We hypothesize that a toxic-response model can be defined by a set of covariates, the knowledge of which permits the rational selection of optimal dose; one that maximizes efficacy and minimizes toxicity. Our approach is designed to further improve cancer treatments. Its central feature is to provide each patient with the best possible dose at each stage. Clinical trials of new anticancer therapies are widespread, critically important tools in the search for more effective cancer
treatments. Cancer trials typically proceed through several distinct phases. The major objective in phase I trials is to identify a working dose for subsequent studies, whereas th
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