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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. und Jaki, Thomas
(2026)
The statistical software revolution in pharmaceutical development: challenges and opportunities in open source.
Drug Discovery Today 31 (2), S. 104613.
Veröffentlichungsdatum dieses Volltextes: 25 Feb 2026 08:21
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.78731
Zusammenfassung
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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| Dokumentenart | Artikel | ||||
| Titel eines Journals oder einer Zeitschrift | Drug Discovery Today | ||||
| Verlag: | Elsevier | ||||
|---|---|---|---|---|---|
| Band: | 31 | ||||
| Nummer des Zeitschriftenheftes oder des Kapitels: | 2 | ||||
| Seitenbereich: | S. 104613 | ||||
| Datum | 21 Januar 2026 | ||||
| Institutionen | Informatik und Data Science > Fachbereich Maschinelles Lernen und Data Science Informatik und Data Science > Fachbereich Maschinelles Lernen und Data Science > Chair for Computational Statistics (Prof. Dr. Thomas Jaki) | ||||
| Identifikationsnummer |
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| Stichwörter / Keywords | software, open source, statistics, clinical trials, pharmaceutical industry, academia | ||||
| Dewey-Dezimal-Klassifikation | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||
| An der Universität Regensburg entstanden | Zum Teil | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-787318 | ||||
| Dokumenten-ID | 78731 |
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