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Guidelines for FAIR sharing of preclinical safety and off-target pharmacology data
- Source :
- Altex, 38(2), 187-197. Springer International Publishing AG, ALTEX
- Publication Year :
- 2021
-
Abstract
- Pre-competitive data sharing can offer the pharmaceutical industry significant benefits in terms of reducing the time and costs involved in getting a new drug to market through more informed testing strategies and knowledge gained by pooling data. If sufficient data is shared and can be co-analyzed, then it can also offer the potential for reduced animal usage and improvements in the in silico prediction of toxicological effects. Data sharing benefits can be further enhanced by applying the FAIR Guiding Principles, reducing time spent curating, transforming and aggregating datasets and allowing more time for data mining and analysis. We hope to facilitate data sharing by other organizations and initiatives by describing lessons learned as part of the Enhancing TRANslational SAFEty Assessment through Integrative Knowledge Management (eTRANSAFE) project, an Innovative Medicines Initiative (IMI) partnership which aims to integrate publicly available data sources with proprietary preclinical and clinical data donated by pharmaceutical organizations. Methods to foster trust and overcome non-technical barriers to data sharing such as legal and IPR (intellectual property rights) are described, including the security requirements that pharmaceutical organizations generally expect to be met. We share the consensus achieved among pharmaceutical partners on decision criteria to be included in internal clearance procedures used to decide if data can be shared. We also report on the consensus achieved on specific data fields to be excluded from sharing for sensitive preclinical safety and pharmacology data that could otherwise not be shared. This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777365 (“eTRANSAFE”). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA.
- Subjects :
- Guiding Principles
Drug Industry
Data field
Pharmacology
Intellectual property
Off-target pharmacology
Pooling data
03 medical and health sciences
Animals
Data Mining
Computer Simulation
FAIR
Pharmaceutical industry
0303 health sciences
business.industry
Information Dissemination
030311 toxicology
General Medicine
Multiple-criteria decision analysis
Preclinical
3. Good health
Data sharing
Medical Laboratory Technology
General partnership
Business
Subjects
Details
- Language :
- English
- ISSN :
- 1868596X
- Database :
- OpenAIRE
- Journal :
- Altex, 38(2), 187-197. Springer International Publishing AG, ALTEX
- Accession number :
- edsair.doi.dedup.....e61c505267ac8b6fa0b42d47100c81a2