Optimizing adaptive design for Phase 2 dose-finding trials incorporating long-term success and financial considerations: A case study for neuropathic pain

Jingjing Gao; Narinder Nangia; Jia Jia; James Bolognese; Jaydeep Bhattacharyya; Nitin Patel

doi:10.1016/j.cct.2017.03.011

Optimizing adaptive design for Phase 2 dose-finding trials incorporating long-term success and financial considerations: A case study for neuropathic pain

Contemp Clin Trials. 2017 Jun;57:69-86. doi: 10.1016/j.cct.2017.03.011. Epub 2017 Apr 4.

Authors

Jingjing Gao¹, Narinder Nangia², Jia Jia³, James Bolognese⁴, Jaydeep Bhattacharyya⁴, Nitin Patel⁴

Affiliations

¹ Abbvie Inc., North Chicago, IL, USA. Electronic address: jingjing.gao@abbvie.com.
² Alkermes, Waltham, MA, USA.
³ Abbvie Inc., North Chicago, IL, USA.
⁴ Cytel Inc., Cambridge, MA, USA.

PMID: 28385653
DOI: 10.1016/j.cct.2017.03.011

Abstract

In this paper, we propose an adaptive randomization design for Phase 2 dose-finding trials to optimize Net Present Value (NPV) for an experimental drug. We replace the traditional fixed sample size design (Patel, et al., 2012) by this new design to see if NPV from the original paper can be improved. Comparison of the proposed design to the previous design is made via simulations using a hypothetical example based on a Diabetic Neuropathic Pain Study.

MeSH terms

Analgesics / administration & dosage*
Analgesics / economics
Analgesics / therapeutic use
Clinical Trials, Phase II as Topic / methods*
Cost-Benefit Analysis
Diabetic Neuropathies / drug therapy*
Diabetic Neuropathies / economics
Dose-Response Relationship, Drug
Endpoint Determination / methods
Humans
Models, Theoretical
Pain Measurement
Randomized Controlled Trials as Topic / methods*
Treatment Outcome

Substances

Analgesics