Work

Harmonization and integration of big data of relevance for personalized medicine into in silico modelling? – Recommendations for technically feasible, and ethico-legal sustainable avenues

Year: 2021

Type: report

Abstract: This report is the second deliverable of WP3 in the EU-STANDS4PM project. WP3 is responsible for providing guidance on the legal, ethical and policy considerations arising from data integration for in silico modelling for personalized medicine. In our first deliverable, we provided a legal and ethical analysis based on the data sources relevant for development of in silico models. The report included: 1. a survey of the international and European data protection and clinical trials regulation as well as legal and ethical regulation relevant for protection of equal access to health, and right to information and self-determination relevant for harmonization and integration of data in in silico modelling, and 2. an assessment of the challenges and opportunities this regulation provides for harmonization and integration of data for in silico modelling. The aim of this report is to explore solutions to the challenges identified in the first report and outline technically feasible as well as legally and ethically sustainable avenues for harmonization/integration of big data of relevance for personalized medicine into in silico modelling.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.5729334

Authors: Ó Cathaoir, Katharina, Gefenas, Eugenijus, Hartlev, Mette, Mourby, Miranda, Lukaseviciene, Vilma

Institutions: University of Copenhagen, Vilnius University, University of Oxford

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funder: European Commission