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June 2011 Response-adaptive dose-finding under model uncertainty
Björn Bornkamp, Frank Bretz, Holger Dette, José Pinheiro
Ann. Appl. Stat. 5(2B): 1611-1631 (June 2011). DOI: 10.1214/10-AOAS445

Abstract

Dose-finding studies are frequently conducted to evaluate the effect of different doses or concentration levels of a compound on a response of interest. Applications include the investigation of a new medicinal drug, a herbicide or fertilizer, a molecular entity, an environmental toxin, or an industrial chemical. In pharmaceutical drug development, dose-finding studies are of critical importance because of regulatory requirements that marketed doses are safe and provide clinically relevant efficacy. Motivated by a dose-finding study in moderate persistent asthma, we propose response-adaptive designs addressing two major challenges in dose-finding studies: uncertainty about the dose-response models and large variability in parameter estimates. To allocate new cohorts of patients in an ongoing study, we use optimal designs that are robust under model uncertainty. In addition, we use a Bayesian shrinkage approach to stabilize the parameter estimates over the successive interim analyses used in the adaptations. This approach allows us to calculate updated parameter estimates and model probabilities that can then be used to calculate the optimal design for subsequent cohorts. The resulting designs are hence robust with respect to model misspecification and additionally can efficiently adapt to the information accrued in an ongoing study. We focus on adaptive designs for estimating the minimum effective dose, although alternative optimality criteria or mixtures thereof could be used, enabling the design to address multiple objectives. In an extensive simulation study, we investigate the operating characteristics of the proposed methods under a variety of scenarios discussed by the clinical team to design the aforementioned clinical study.

Citation

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Björn Bornkamp. Frank Bretz. Holger Dette. José Pinheiro. "Response-adaptive dose-finding under model uncertainty." Ann. Appl. Stat. 5 (2B) 1611 - 1631, June 2011. https://doi.org/10.1214/10-AOAS445

Information

Published: June 2011
First available in Project Euclid: 13 July 2011

zbMATH: 1223.62158
MathSciNet: MR2849788
Digital Object Identifier: 10.1214/10-AOAS445

Keywords: Dose-response , drug development , minimum effective dose , optimal design , shrinkage approach

Rights: Copyright © 2011 Institute of Mathematical Statistics

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Vol.5 • No. 2B • June 2011
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