| Literature DB >> 31805565 |
Stefania Boccia1,2, Roberta Pastorino3, Walter Ricciardi4,3, Róza Ádány5, Floris Barnhoorn6, Paolo Boffetta7,8, Martina C Cornel9, Corrado De Vito10, Muir Gray11, Anant Jani12, Michael Lang13, Jim Roldan14, Annalisa Rosso10, José Manuel Sánchez14, Cornelia M Van Dujin15,16, Carla G Van El9, Paolo Villari10, Ma'n H Zawati13.
Abstract
Medical practitioners are increasingly adopting a personalized medicine (PM) approach involving individually tailored patient care. The Personalized Prevention of Chronic Diseases (PRECeDI) consortium project, funded within the Marie Skłodowska Curie Action (MSCA) Research and Innovation Staff Exchange (RISE) scheme, had fostered collaboration on PM research and training with special emphasis on the prevention of chronic diseases. From 2014 to 2018, the PRECeDI consortium trained 50 staff members on personalized prevention of chronic diseases through training and research. The acquisition of skills from researchers came from dedicated secondments from academic and nonacademic institutions aimed at training on several research topics related to personalized prevention of cancer and cardiovascular and neurodegenerative diseases. In detail, 5 research domains were addressed: (1) identification and validation of biomarkers for the primary prevention of cardiovascular diseases, secondary prevention of Alzheimer disease, and tertiary prevention of head and neck cancer; (2) economic evaluation of genomic applications; (3) ethical-legal and policy issues surrounding PM; (4) sociotechnical analysis of the pros and cons of informing healthy individuals on their genome; and (5) identification of organizational models for the provision of predictive genetic testing. Based on the results of the research carried out by the PRECeDI consortium, in November 2018, a set of recommendations for policy makers, scientists, and industry has been issued, with the main goal to foster the integration of PM approaches in the field of chronic disease prevention.Entities:
Keywords: Chronic diseases; Personalized medicine; Prevention; Recommendations
Mesh:
Year: 2019 PMID: 31805565 DOI: 10.1159/000504652
Source DB: PubMed Journal: Public Health Genomics ISSN: 1662-4246 Impact factor: 2.000