Bornkamp, Bjoern, Zaoli, Silvia, Azzarito, Michela, Martin, Ruvie, Müller, Carsten Philipp, Moloney, Conor, Giulia, Capestro and Ohlssen, David (2024) Predicting subgroup treatment effects for a new study: Motivations, results and learnings from running a data challenge in a pharmaceutical corporation. Pharmaceutical statistics. ISSN 1539-1612

Abstract

We present the motivation, experience and learnings from a data challenge conducted at a large pharmaceutical corporation on the topic of subgroup identification. The data challenge aimed at exploring approaches to subgroup identification for future clinical trials. To mimic a realistic setting, participants had access to 4 Phase III clinical trials to derive a subgroup and predict its treatment effect on a future study not accessible to challenge participants. 30 teams registered for the challenge with around 100 participants, primarily from Biostatistics organisation. We outline the motivation for running the challenge, the challenge rules and logistics. Finally, we present the results of the challenge, the participant feedback as well as the learnings, and how these learnings can be translated into statistical practice.

Item Type:	Article
Keywords:	Common Task Framework; Data Science; Subgroup Analysis; Subgroup Identification; Machine Learning
Date Deposited:	20 Mar 2024 00:45
Last Modified:	20 Mar 2024 00:45
URI:	https://oak.novartis.com/id/eprint/50036