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Pharmaceutical R & D pipeline management under trial duration uncertainty
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Gökalp, Elvan and Branke, Juergen (2020) Pharmaceutical R & D pipeline management under trial duration uncertainty. Computers & Chemical Engineering, 136 . 106782. doi:10.1016/j.compchemeng.2020.106782
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WRAP-pharmaceutical-pipeline-trial-uncertainty-Branke-2020.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0. Download (1211Kb) | Preview |
Official URL: http://dx.doi.org/10.1016/j.compchemeng.2020.10678...
Abstract
We consider a pharmaceutical Research & Development (R & D) pipeline management problem under two significant uncertainties: the outcomes of clinical trials and their durations. We present an Approximate Dynamic Programming (ADP) approach to solve the problem efficiently. Given an initial list of potential drug candidates, ADP derives a policy that suggests the trials to be performed at each decision point and state. For the classical R&D pipeline planning problem with deterministic trial durations, we compare our ADP approach with other methods from the literature, and find that it can find better solutions more quickly in particular for larger problem instances. For the case with stochastic trial durations, we compare the ADP algorithm with a myopic approach and show that the expected net profit obtained by the derived ADP policy is higher (almost 20% for a 10-drug portfolio).
| Item Type: | Journal Article | ||||||||
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| Subjects: | H Social Sciences > HD Industries. Land use. Labor Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > RS Pharmacy and materia medica |
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| Divisions: | Faculty of Social Sciences > Warwick Business School Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) |
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| Library of Congress Subject Headings (LCSH): | Pharmaceutical industry , Pharmaceutical industry -- Research, Heuristic algorithms, Pharmacy -- Data processing , Pharmacy informatics | ||||||||
| Journal or Publication Title: | Computers & Chemical Engineering | ||||||||
| Publisher: | Elsevier | ||||||||
| ISSN: | 0098-1354 | ||||||||
| Official Date: | 8 May 2020 | ||||||||
| Dates: |
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| Volume: | 136 | ||||||||
| Article Number: | 106782 | ||||||||
| DOI: | 10.1016/j.compchemeng.2020.106782 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| RIOXX Funder/Project Grant: |
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