TY - JOUR
T1 - Improving Clinical Trial Efficiency
T2 - Thinking outside the Box
AU - Mandrekar, Sumithra J.
AU - Dahlberg, Suzanne E.
AU - Simon, Richard
PY - 2015
Y1 - 2015
N2 - Clinical trial design strategies have evolved over the past few years as a means to accelerate the drug development process so that the right therapies can be delivered to the right patients. Basket, umbrella, and adaptive enrichment strategies represent a class of novel designs for testing targeted therapeutics in oncology. Umbrella trials include a central infrastructure for screening and identification of patients, and focus on a single tumor type or histology with multiple subtrials, each testing a targeted therapy within a molecularly defined subset. Basket trial designs offer the possibility to include multiple molecularly defined subpopulations, often across histology or tumor types, but included in one cohesive design to evaluate the targeted therapy in question. Adaptive enrichment designs offer the potential to enrich for patients with a particular molecular feature that is predictive of benefit for the test treatment based on accumulating evidence from the trial. This review will aim to discuss the fundamentals of these design strategies, the underlying statistical framework, the logistical barriers of implementation, and, ultimately, the interpretation of the trial results. New statistical approaches, extensive multidisciplinary collaboration, and state of the art data capture technologies are needed to implement these strategies in practice. Logistical challenges to implementation arising from centralized assay testing, requirement of multiple specimens, multidisciplinary collaboration, and infrastructure requirements will also be discussed. This review will present these concepts in the context of the National Cancer Institute's precision medicine initiative trials: MATCH, ALCHEMIST, Lung MAP, as well as other trials such as FOCUS4.
AB - Clinical trial design strategies have evolved over the past few years as a means to accelerate the drug development process so that the right therapies can be delivered to the right patients. Basket, umbrella, and adaptive enrichment strategies represent a class of novel designs for testing targeted therapeutics in oncology. Umbrella trials include a central infrastructure for screening and identification of patients, and focus on a single tumor type or histology with multiple subtrials, each testing a targeted therapy within a molecularly defined subset. Basket trial designs offer the possibility to include multiple molecularly defined subpopulations, often across histology or tumor types, but included in one cohesive design to evaluate the targeted therapy in question. Adaptive enrichment designs offer the potential to enrich for patients with a particular molecular feature that is predictive of benefit for the test treatment based on accumulating evidence from the trial. This review will aim to discuss the fundamentals of these design strategies, the underlying statistical framework, the logistical barriers of implementation, and, ultimately, the interpretation of the trial results. New statistical approaches, extensive multidisciplinary collaboration, and state of the art data capture technologies are needed to implement these strategies in practice. Logistical challenges to implementation arising from centralized assay testing, requirement of multiple specimens, multidisciplinary collaboration, and infrastructure requirements will also be discussed. This review will present these concepts in the context of the National Cancer Institute's precision medicine initiative trials: MATCH, ALCHEMIST, Lung MAP, as well as other trials such as FOCUS4.
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U2 - 10.14694/EdBook_AM.2015.35.e141
DO - 10.14694/EdBook_AM.2015.35.e141
M3 - Review article
C2 - 25993165
AN - SCOPUS:85018221048
SN - 1548-8756
SP - e141-e147
JO - American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Meeting
JF - American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Meeting
ER -