Evidence map›Paper›PMID 39856804›Full record

ArticleClinical pharmacology and therapeutics2025

On the Concepts, Methods, and Use of "Probability of Success" for Drug Development Decision-Making: A Scoping Review.

Aysun Cetinyurek Yavuz, Muhammad Bergas Nur Fayyad, Ce Jiang, Florie Brion Bouvier, Celine Beji, Sonia Zebachi, Ghinwa Y Hayek, Billy Amzal, Raphael Porcher, Julien Tanniou and 2 more

Abstract readScoping Review
In one paragraph

Article in Clinical pharmacology and therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Aysun Cetinyurek YavuzIQ Health Department, Radboud University Medical Center, Nijmegen, The Netherlands.ORCID 0000-0003-4024-8775
Muhammad Bergas Nur FayyadIQ Health Department, Radboud University Medical Center, Nijmegen, The Netherlands.ORCID 0009-0007-7835-2451
Ce JiangQuinten Health, Paris, France.ORCID 0009-0008-3775-7070
Florie Brion BouvierParis Cité University, Paris, France.
Celine BejiParis Cité University, Paris, France.
Sonia ZebachiQuinten Health, Paris, France.ORCID 0000-0003-1035-8690
Ghinwa Y HayekQuinten Health, Paris, France.ORCID 0000-0001-7046-209X
Billy AmzalQuinten Health, Paris, France.
Raphael PorcherParis Cité University, Paris, France.ORCID 0000-0002-5277-4679
Julien TanniouQuinten Health, Paris, France.ORCID 0000-0002-3806-2413
Kit RoesIQ Health Department, Radboud University Medical Center, Nijmegen, The Netherlands.ORCID 0000-0002-6775-1963
Laura RodwellIQ Health Department, Radboud University Medical Center, Nijmegen, The Netherlands.ORCID 0000-0002-5635-4997

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug development is a lengthy process with considerable uncertainty at each milestone. Several trials are needed to progress to confirmatory evaluation and establish a positive benefit-risk balance. One of the critical milestones is the decision to progress to phase III based on phase II trial results. Use of probability of success is becoming standard in pharmaceutical companies to support this decision. However, the lack of consistency in terminology makes it difficult to assess the comparative value of different approaches. By leveraging the availability of high-quality external data (e.g., real-world data, historical clinical trial data, etc.), probability of success-based procedures may further improve decision-making. We performed a scoping review of approaches to calculate the probability of success of a phase III trial depending on the available data sources and the availability of specific endpoints. Calculation of probability of success is relatively straightforward if data for the primary endpoint of the phase III trial are also available in phase II trials. Often, phase II trials are based on biomarker or surrogate outcomes, due to challenges associated with study duration and required sample size. Probability of success-based procedures as reviewed can incorporate external data sources, for example, from clinical trials testing the same or similar drug or real-world data on the targeted population-optimizing the calculation of probability of trial success and the projected drug candidate value. We conclude the paper by reflecting on alternative approaches and ideas for uses within pharmaceutical companies and academia.

Indexed as

Clinical Trials, Phase III as TopicDecision MakingDrug DevelopmentClinical Trials, Phase II as TopicHumansProbabilityResearch Design

Identifiers

PMID39856804
PMCPMC11924160

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.