Going beyond probability of success: Opportunities for statisticians to influence quantitative decision‐making at the portfolio level

The pharmaceutical industry is plagued with long, costly development and high risk. Therefore, a company's effective management and optimisation of a portfolio of projects is critical for success. Project metrics such as the probability of success enable modelling of a company's pipeline a...

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Veröffentlicht in:Pharmaceutical statistics : the journal of the pharmaceutical industry 2024-05, Vol.23 (3), p.429-438
Hauptverfasser: Wiklund, Stig‐Johan, Thorn, Katharine, Götte, Heiko, Hacquoil, Kimberley, Saint‐Hilary, Gaëlle, Carlton, Alex
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container_end_page 438
container_issue 3
container_start_page 429
container_title Pharmaceutical statistics : the journal of the pharmaceutical industry
container_volume 23
creator Wiklund, Stig‐Johan
Thorn, Katharine
Götte, Heiko
Hacquoil, Kimberley
Saint‐Hilary, Gaëlle
Carlton, Alex
description The pharmaceutical industry is plagued with long, costly development and high risk. Therefore, a company's effective management and optimisation of a portfolio of projects is critical for success. Project metrics such as the probability of success enable modelling of a company's pipeline accounting for the high uncertainty inherent within the industry. Making portfolio decisions inherently involves managing risk, and statisticians are ideally positioned to champion not only the derivation of metrics for individual projects, but also advocate decision‐making at a broader portfolio level. This article aims to examine the existing different portfolio decision‐making approaches and to suggest opportunities for statisticians to add value in terms of introducing probabilistic thinking, quantitative decision‐making, and increasingly advanced methodologies.
doi_str_mv 10.1002/pst.2361
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source Wiley Online Library Journals Frontfile Complete
subjects drug development
optimisation
portfolio management
project metrics
title Going beyond probability of success: Opportunities for statisticians to influence quantitative decision‐making at the portfolio level
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