Resumen: Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in
health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed
computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on
Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a
human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards humanbased
methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the
limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental
and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The
effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with
experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary
approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines
and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships
supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and
overcome in each specific setting. Idioma: Inglés DOI: 10.1093/europace/euv320 Año: 2015 Publicado en: Europace 18, 9 (2015), 1287 - 1298 ISSN: 1099-5129 Factor impacto JCR: 4.021 (2015) Categ. JCR: CARDIAC & CARDIOVASCULAR SYSTEMS rank: 32 / 124 = 0.258 (2015) - Q2 - T1 Factor impacto SCIMAGO: 2.412 - Physiology (medical) (Q1) - Cardiology and Cardiovascular Medicine (Q1)