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Open innovation: Towards sharing of data, models and workflows
Crit Path Inst, Quantitat Med, Tucson, AZ USA..
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.ORCID iD: 0000-0003-1258-8297
Crit Path Inst, Quantitat Med, Tucson, AZ USA..
Pharmetheus, Uppsala, Sweden..
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2017 (English)In: European Journal of Pharmaceutical Sciences, ISSN 0928-0987, E-ISSN 1879-0720, Vol. 109, p. S65-S71Article, review/survey (Refereed) Published
Abstract [en]

Sharing of resources across organisations to support open innovation is an old idea, but which is being taken up by the scientific community at increasing speed, concerning public sharing in particular. The ability to address new questions or provide more precise answers to old questions through merged information is among the attractive features of sharing. Increased efficiency through reuse, and increased reliability of scientific findings through enhanced transparency, are expected outcomes from sharing. In the field of pharmacometrics, efforts to publicly share data, models and workflow have recently started. Sharing of individual-level longitudinal data for modelling requires solving legal, ethical and proprietary issues similar to many other fields, but there are also pharmacometric-specific aspects regarding data formats, exchange standards, and database properties. Several organisations (CDISC, C-Path, IMI, ISoP) are working to solve these issues and propose standards. There are also a number of initiatives aimed at collecting disease-specific databases-Alzheimer's Disease (ADNI, CAMD), malaria (WWARN), oncology (PDS), Parkinson's Disease (PPMI), tuberculosis (CPTR, TB-PACTS, ReSeqTB)-suitable for drug-disease modelling. Organized sharing of pharmacometric executable model code and associated information has in the past been sparse, but a model repository (DDMoRe Model Repository) intended for the purpose has recently been launched. In addition several other services can facilitate model sharing more generally. Pharmacometric workflows have matured over the last decades and initiatives to more fully capture those applied to analyses are ongoing. In order to maximize both the impact of pharmacometrics and the knowledge extracted from clinical data, the scientific community needs to take ownership of and create opportunities for open innovation.

Place, publisher, year, edition, pages
2017. Vol. 109, p. S65-S71
Keywords [en]
Open innovation, Data sharing, Pharmacometric models, Modelling workflows, Drug development
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-345832DOI: 10.1016/j.ejps.2017.06.035ISI: 000415283100012PubMedID: 28684136OAI: oai:DiVA.org:uu-345832DiVA, id: diva2:1189738
Available from: 2018-03-12 Created: 2018-03-12 Last updated: 2018-03-12Bibliographically approved

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