eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved]
Integrative drug safety research in translational health informatics has rapidly evolved and included data that are drawn in from many resources, combining diverse data that are either reused from (curated) repositories, or newly generated at source. Each resource is mandated by different sets of me...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2022-03-01
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| Series: | F1000Research |
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| Online Access: | https://f1000research.com/articles/11-287/v1 |
| _version_ | 1811246345588047872 |
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| author | Katharina B. Lauer John-Michael Sauer Richard Liwski Niklas Blomberg Miranda Mourby Montse Camprubi Sirarat Sarntivijai Katharine Briggs Thomas Steger-Hartmann Johan van der Lei Alison Cave |
| author_facet | Katharina B. Lauer John-Michael Sauer Richard Liwski Niklas Blomberg Miranda Mourby Montse Camprubi Sirarat Sarntivijai Katharine Briggs Thomas Steger-Hartmann Johan van der Lei Alison Cave |
| author_sort | Katharina B. Lauer |
| collection | DOAJ |
| description | Integrative drug safety research in translational health informatics has rapidly evolved and included data that are drawn in from many resources, combining diverse data that are either reused from (curated) repositories, or newly generated at source. Each resource is mandated by different sets of metadata rules that are imposed on the incoming data. Combination of the data cannot be readily achieved without interference of data stewardship and the top-down policy guidelines that supervise and inform the process for data combination to aid meaningful interpretation and analysis of such data. The eTRANSAFE Consortium's effort to drive integrative drug safety research at a large scale hereby present the lessons learnt and the proposal of solution at the guidelines in practice at this Innovative Medicines Initiative (IMI) project. Recommendations in these guidelines were compiled from feedback received from key stakeholders in regulatory agencies, EFPIA companies, and academic partners. The research reproducibility guidelines presented in this study lay the foundation for a comprehensive data sharing and knowledge management plans accounting for research data management in the drug safety space - FAIR data sharing guidelines, and the model verification guidelines as generic deliverables that best practices that can be reused by other scientific community members at large. FAIR data sharing is a dynamic landscape that rapidly evolves with fast-paced technology advancements. The research reproducibility in drug safety guidelines introduced in this study provides a reusable framework that can be adopted by other research communities that aim to integrate public and private data in biomedical research space. |
| first_indexed | 2024-04-12T14:52:08Z |
| format | Article |
| id | doaj.art-fdab4225b8f14c9f93a0b10bf9a470c8 |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-04-12T14:52:08Z |
| publishDate | 2022-03-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-fdab4225b8f14c9f93a0b10bf9a470c82022-12-22T03:28:25ZengF1000 Research LtdF1000Research2046-14022022-03-011177731eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved]Katharina B. Lauer0https://orcid.org/0000-0002-4347-7525John-Michael Sauer1Richard Liwski2Niklas Blomberg3Miranda Mourby4Montse Camprubi5Sirarat Sarntivijai6https://orcid.org/0000-0002-2548-641XKatharine Briggs7https://orcid.org/0000-0002-2044-1159Thomas Steger-Hartmann8Johan van der Lei9Alison Cave10ELIXIR Hub, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UKPredictive Safety Testing Consortium, Critical Path Institute, Tucson, Arizona, 85718, USAPredictive Safety Testing Consortium, Critical Path Institute, Tucson, Arizona, 85718, USAELIXIR Hub, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UKCentre for Health, Law and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, OX2 7DD, UKSynapse Research Management Partners S.L., C. Diputació 237, Àtic 3a, 08007, Barcelona, SpainELIXIR Hub, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UKLhasa Limited, Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UKBayer AG, Research & Development, Pharmaceuticals, Investigational Toxicology, 13342 Berlin, GermanyDepartment of Medical Informatics, Erasmus University Rotterdam, EUR - Erasmus Medical Center (MC), Rotterdam, The NetherlandsUK Research and Innovation, Polaris House, North Star Avenue, Swindon, SN2 1FL, UKIntegrative drug safety research in translational health informatics has rapidly evolved and included data that are drawn in from many resources, combining diverse data that are either reused from (curated) repositories, or newly generated at source. Each resource is mandated by different sets of metadata rules that are imposed on the incoming data. Combination of the data cannot be readily achieved without interference of data stewardship and the top-down policy guidelines that supervise and inform the process for data combination to aid meaningful interpretation and analysis of such data. The eTRANSAFE Consortium's effort to drive integrative drug safety research at a large scale hereby present the lessons learnt and the proposal of solution at the guidelines in practice at this Innovative Medicines Initiative (IMI) project. Recommendations in these guidelines were compiled from feedback received from key stakeholders in regulatory agencies, EFPIA companies, and academic partners. The research reproducibility guidelines presented in this study lay the foundation for a comprehensive data sharing and knowledge management plans accounting for research data management in the drug safety space - FAIR data sharing guidelines, and the model verification guidelines as generic deliverables that best practices that can be reused by other scientific community members at large. FAIR data sharing is a dynamic landscape that rapidly evolves with fast-paced technology advancements. The research reproducibility in drug safety guidelines introduced in this study provides a reusable framework that can be adopted by other research communities that aim to integrate public and private data in biomedical research space.https://f1000research.com/articles/11-287/v1FAIR Data Research reproducibility Interoperability eTRANSAFE Drug Safety model validationeng |
| spellingShingle | Katharina B. Lauer John-Michael Sauer Richard Liwski Niklas Blomberg Miranda Mourby Montse Camprubi Sirarat Sarntivijai Katharine Briggs Thomas Steger-Hartmann Johan van der Lei Alison Cave eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved] F1000Research FAIR Data Research reproducibility Interoperability eTRANSAFE Drug Safety model validation eng |
| title | eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved] |
| title_full | eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved] |
| title_fullStr | eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved] |
| title_full_unstemmed | eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved] |
| title_short | eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain [version 1; peer review: 2 approved] |
| title_sort | etransafe building a sustainable framework to share reproducible drug safety knowledge with the public domain version 1 peer review 2 approved |
| topic | FAIR Data Research reproducibility Interoperability eTRANSAFE Drug Safety model validation eng |
| url | https://f1000research.com/articles/11-287/v1 |
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