Rebhan, Michael (2017) Towards a systems approach for chronic diseases, based on health state modeling. F1000Research., 6. p. 309. ISSN 2046-1402

Abstract

Rising pressure from chronic diseases means that we need to learn how to deal with challenges at a different level, including the use of systems approaches that better connect across fragments, such as disciplines, stakeholders, institutions, and technologies. By learning from progress in leading areas of health innovation (including Oncology and AIDS), as well as complementary indications (Alzheimer’s disease), we try to extract the most enabling innovation paradigms, and discuss their extension to additional areas of application within a systems approach. To facilitate such work, a Precision, P4 or Systems Medicine platform is proposed, which is centered on a theory of health states. Modeling of such health states should allow iterative optimization, as new longitudinal human data are added. This platform is designed to facilitate the discovery of links between opportunities related to a) the modernization of diagnosis, including the increased use of omics profiling, b) patient-centric approaches enabled by technology convergence, including Digital Health and connected devices c) increasing understanding of the pathobiological, clinical and health economic aspects of disease progression stages, and d) design of new interventions, including therapies as well as preventive measures. Probabilistic Markov models of health states and transitions, e.g. those used for health economy analysis in Alzheimer’s disease, are discussed as a pragmatic starting point for that platform. A path towards extension into other indications, data types and uses is discussed, with a focus on Regenerative Medicine, and pathobiology that reflects a dynamic balance of slowly accumulating tissue damage, and regenerative mechanisms.

Item Type:	Article
Date Deposited:	12 Apr 2017 00:45
Last Modified:	12 Apr 2017 00:45
URI:	https://oak.novartis.com/id/eprint/31977