Dataset Information

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

ABSTRACT: The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

SUBMITTER: Nellaker C

PROVIDER: S-EPMC6681681 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

Nellåker Christoffer C Alkuraya Fowzan S FS Baynam Gareth G Bernier Raphael A RA Bernier Francois P J FPJ Boulanger Vanessa V Brudno Michael M Brunner Han G HG Clayton-Smith Jill J Cogné Benjamin B Dawkins Hugh J S HJS deVries Bert B A BBA Douzgou Sofia S Dudding-Byth Tracy T Eichler Evan E EE Ferlaino Michael M Fieggen Karen K Firth Helen V HV FitzPatrick David R DR Gration Dylan D Groza Tudor T Haendel Melissa M Hallowell Nina N Hamosh Ada A Hehir-Kwa Jayne J Hitz Marc-Phillip MP Hughes Mark M Kini Usha U Kleefstra Tjitske T Kooy R Frank RF Krawitz Peter P Küry Sébastien S Lees Melissa M Lyon Gholson J GJ Lyonnet Stanislas S Marcadier Julien L JL Meyn Stephen S Moslerová Veronika V Politei Juan M JM Poulton Cathryn C CC Raymond F Lucy FL Reijnders Margot R F MRF Robinson Peter N PN Romano Corrado C Rose Catherine M CM Sainsbury David C G DCG Schofield Lyn L Sutton Vernon R VR Turnovec Marek M Van Dijck Anke A Van Esch Hilde H Wilkie Andrew O M AOM

Frontiers in genetics 20190729

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our ...[more]

PMID: 31417602

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Project description:BackgroundWhile the integration of patient and public involvement (PPI) in clinical research is now widespread and recommended as standard practice, meaningful PPI in pre-clinical, discovery science research is more difficult to achieve. One potential way to address this is by integrating PPI into the training programmes of discovery science postgraduate doctoral students. This paper describes the development and formative evaluation of the Student Patient Alliance (SPA), a programme developed at the University of Birmingham that connects PPI partners with doctoral students.MethodsFollowing a successful pilot of the SPA by the Rheumatology Research Group at the University of Birmingham, the scheme was implemented across several collaborating Versus Arthritis / Medical Research Council (MRC) centres of excellence. Doctoral students were partnered with PPI partners, provided with initial information and guidance, and then encouraged to work together on research and public engagement activities. After six months, students, their PPI partners and the PPI coordinators at each centre completed brief surveys about their participation in the SPA.ResultsBoth doctoral students and their PPI partners felt that taking part in SPA had a positive impact on understanding, motivation and communication skills. Students reported an increased understanding of PPI and patient priorities and reported improved public engagement skills. Their PPI partners reported a positive impact of the collaboration with the students. They enjoyed learning about the student's research and contributing to the student's personal development. PPI coordinators also highlighted the benefits of the SPA, but noted some challenges they had experienced, such as difficulties matching students with PPI partners.ConclusionsThe SPA was valued by students and PPI partners, and it is likely that initiatives of this kind would enhance students' PPI and public engagement skills and awareness of patients' experiences on a wider scale. However, appropriate resources are needed at an institutional level to support the implementation of effective programmes of this kind on a larger scale.

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Dataset Information

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

Publications

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.

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