Optimizing Drug Development Programs: Type 2 Diabetes Case Study

Therapeutic Innovation & Regulatory Science
Zoran AntonijevicKlas Bergenheim

Abstract

Recently, consideration was given to the impact of dose selection strategies in phase IIb on the overall success of drug development programs. A natural next step is to simultaneously optimize design aspects of both phase IIB and phase III. We used type 2 diabetes as an example, including realistic regulatory and commercial scenarios for this indication. The expected net present value (eNPV) has been selected as the primary outcome because it naturally accommodates optimization, providing an explicit trade-off between the probability of success (PoS) and time delays and trial costs. Our findings are that larger studies and/or implementation of an adaptive design over a fixed design in phase IIb provide more precise dose selection and reduce the bias of treatment effects and uncertainty in the estimated eNPV within the range of sample sizes that we examined. Developers also have to ensure that dose selection criteria are consistent with development strategy and objectives.

References

Jan 1, 1986·Statistics in Medicine·D J Spiegelhalter, L S Freedman
Nov 21, 2007·Journal of Biopharmaceutical Statistics·Björn BornkampFrank Shen
Sep 4, 2010·Politics and the Life Sciences : the Journal of the Association for Politics and the Life Sciences·Erik P Bucy

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Citations

Jan 30, 2019·Biometrical Journal. Biometrische Zeitschrift·Julia NiewczasFranz König
Sep 1, 2013·Therapeutic Innovation & Regulatory Science·Olga MarchenkoYanping Wang
Nov 16, 2019·Pharmaceutical Statistics·Daniele De Martini
Apr 28, 2018·Pharmaceutical Statistics·Meinhard KieserHeiko Götte
Mar 1, 2016·Therapeutic Innovation & Regulatory Science·Daniele De Martini
Mar 19, 2020·Journal of Biopharmaceutical Statistics·Jihane AouniBernard Sebastien
Dec 16, 2021·Pharmaceutical Statistics·Lisa V HampsonSteffen Ballerstedt

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Software Mentioned

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