Sieving for gold: external comparator studies to prioritize drugs for late-stage clinical trial

External comparator (EC) studies can improve identification of compounds with the most promising performance in pre-pivotal single-arm trials (SAT). As SAT output lacks comparative insights, EC studies allow efficient contextualization of compound performance in early phases of drug development. Improving insights from pre-pivotal SATs allows more informed prioritization of compounds and investment choices and enables faster and more substantiated development of the most promising molecules to the benefit of patients. The extensive digitization of healthcare information routinely generated during patient treatment journeys makes EC studies using real-world data an attractive alternative to other approaches (such as systematic literature review and repurposed trial data). Using oncology as an illustration, this paper presents how real-world data EC studies can address some of the fundamental challenges the pharmaceutical sector faces in developing novel therapies, and especially those pertaining to emerging biopharma companies.

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Publication Details

Journal
Journal of Comparative Effectiveness Research
Published
2026-02-01
DOI
https://doi.org/10.57264/cer-2024-0201
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Sieving for gold: external comparator studies to prioritize drugs for late-stage clinical trial

B Osterwalder, E. Calvo, Samuel Vennin, C. Cantoni et al.
Journal of Comparative Effectiveness Research
Computational Drug Discovery Methods
article

Sieving for gold: external comparator studies to prioritize drugs for late-stage clinical trial

B Osterwalder, E. Calvo, Samuel Vennin, C. Cantoni, Benedikt Maissenhaelter, Will Sopwith, PM Valle, Bettina Ryll, Gerd Rippin
article en

Abstract

External comparator (EC) studies can improve identification of compounds with the most promising performance in pre-pivotal single-arm trials (SAT). As SAT output lacks comparative insights, EC studies allow efficient contextualization of compound performance in early phases of drug development. Improving insights from pre-pivotal SATs allows more informed prioritization of compounds and investment choices and enables faster and more substantiated development of the most promising molecules to the benefit of patients. The extensive digitization of healthcare information routinely generated during patient treatment journeys makes EC studies using real-world data an attractive alternative to other approaches (such as systematic literature review and repurposed trial data). Using oncology as an illustration, this paper presents how real-world data EC studies can address some of the fundamental challenges the pharmaceutical sector faces in developing novel therapies, and especially those pertaining to emerging biopharma companies.

Journal of Comparative Effectiveness ResearchVol. 15(2)
Stockholm School of Economics (SE), IQVIA (United Kingdom) (GB), Centro Oncológico de Galicia (ES), IQVIA (United States) (US), IQVIA (France) (FR), BG Consulting Engineers (Switzerland) (CH)
Openalex Percentile: Top 65%
Computational Drug Discovery Methods
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