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The statistical software revolution in pharmaceutical development: challenges and opportunities in open source
Sabanés Bové, Daniel, Seibold, Heidi, Boulesteix, Anne-Laure, Manitz, Juliane, Gasparini, Alessandro, Günhan, Burak K., Boix, Oliver, Schüler, Armin, Fillinger, Sven, Nahnsen, Sven, Jacob, Anna E. and Jaki, Thomas
(2026)
The statistical software revolution in pharmaceutical development: challenges and opportunities in open source.
Drug Discovery Today 31 (2), p. 104613.
Date of publication of this fulltext: 25 Feb 2026 08:21
Article
DOI to cite this document: 10.5283/epub.78731
Abstract
Open-source statistical software development is increasingly the preferred solution for leveraging new statistical methods in the pharmaceutical industry. However, with a long history of relying on licensed analysis software, there are philosophical and organizational barriers to overcome. In particular, the sustainability, reliability, usability, and feasibility of maintaining open-source ...
Open-source statistical software development is increasingly the preferred solution for leveraging new statistical methods in the pharmaceutical industry. However, with a long history of relying on licensed analysis software, there are philosophical and organizational barriers to overcome. In particular, the sustainability, reliability, usability, and feasibility of maintaining open-source statistical software long-term must be ensured. Here, we describe the open-source revolution that is emerging in the pharmaceutical industry and how it facilitates greater scaling of innovative analytical methods in statistics. We discuss challenges to open-source software adoption and propose mitigation strategies. Furthermore, we illustrate the potential for open-source software development with examples of successful projects, which highlight the roles of cross-company collaboration, career paths, education, and community building.
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Details
| Item type | Article | ||||
| Journal or Publication Title | Drug Discovery Today | ||||
| Publisher: | Elsevier | ||||
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| Open Access Type: | CC-License | ||||
| Volume: | 31 | ||||
| Number of Issue or Book Chapter: | 2 | ||||
| Page Range: | p. 104613 | ||||
| Date | 21 January 2026 | ||||
| Institutions | Informatics and Data Science > Department Machine Learning & Data Science Informatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki) | ||||
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| Keywords | software, open source, statistics, clinical trials, pharmaceutical industry, academia | ||||
| Dewey Decimal Classification | 000 Computer science, information & general works > 004 Computer science | ||||
| Status | Published | ||||
| Refereed | Yes, this version has been refereed | ||||
| Created at the University of Regensburg | Partially | ||||
| URN of the UB Regensburg | urn:nbn:de:bvb:355-epub-787318 | ||||
| Item ID | 78731 |
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