Integrative data science in drug safety research: experiences, challenges, and perspectives
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- dc.contributor.author Sanz, Ferran
- dc.date.accessioned 2025-09-01T12:40:56Z
- dc.date.available 2025-09-01T12:40:56Z
- dc.date.issued 2025
- dc.description.abstract Pharmaceutical research and development largely depend on the quantity and quality of data that are available to support projects. The secondary use of data by means of collaborative and integrative approaches is yielding promising results in drug safety research. However, there are challenges that must be overcome in these integrative approaches, such as interoperability issues, intellectual property protection, and, in the case of clinical information, personal data safeguards. The OMOP common data model and the EHDEN and DARWIN EU platforms constitute successful examples of data sharing initiatives in the clinical domain, while the eTOX, eTRANSAFE, and VICT3R international projects are examples of corporate data sharing in toxicology research. The VICT3R project is using these shared data for generating virtual control groups to be applied in nonclinical drug safety assessment. Drug-related knowledge bases that integrate information from different sources also constitute useful tools in the drug safety domain.
- dc.description.sponsorship The author is cofounder and one of the shareholders of MedBioinformatics Solutions SL; DISGENET is a product of this company. The VICT3R project receives funding from the Innovative Health Initiative Joint Undertaking (IHI JU) under grant 101172693. The IHI JU receives support from the European Union's Horizon Europe research and innovation program and COCIR, EFPIA, Europa Bío, MedTech Europe, and Vaccines Europe and contributing partners. Views and opinions expressed are, however, those of the author only and do not necessarily reflect those of the aforementioned parties. None of the aforementioned parties can be held responsible for them.
- dc.format.mimetype application/pdf
- dc.identifier.citation Sanz F. Integrative data science in drug safety research: experiences, challenges, and perspectives. Annu Rev Biomed Data Sci. 2025 Aug;8(1):275-85. DOI: 10.1146/annurev-biodatasci-103123-095506
- dc.identifier.doi http://dx.doi.org/10.1146/annurev-biodatasci-103123-095506
- dc.identifier.issn 2574-3414
- dc.identifier.uri http://hdl.handle.net/10230/71088
- dc.language.iso eng
- dc.publisher Annual Reviews Inc
- dc.relation.ispartof Annu Rev Biomed Data Sci. 2025 Aug;8(1):275-85
- dc.relation.projectID info:eu-repo/grantAgreement/EC/HE/101172693
- dc.rights Copyright © 2025 by the author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See credit lines of images or other third-party material in this article for license information.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Data sharing
- dc.subject.keyword Drug safety
- dc.subject.keyword Drug-related knowledge bases
- dc.subject.keyword Integrative data science
- dc.subject.keyword Virtual control groups
- dc.title Integrative data science in drug safety research: experiences, challenges, and perspectives
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion