Precision medicine for managing chronic diseases.

Abstract

Precision medicine (PM) is an important modern paradigm for combining new types of metrics with bigmedical datasets to create prediction models for prevention, diagnosis, and specific therapy of chronicdiseases. The aim of this paper was to differentiate PM from personalized medicine, to show potentialbenefits of PM for managing chronic diseases, and to define problems with implementation of PM intoclinical practice. PM strategies in chronic airway diseases, diabetes, and cardiovascular diseases showthat the key to developing PM is the addition of big datasets to the course of individually profiling diseasesand patients. Integration of PM into clinical practice requires the reengineering of the health careinfrastructure by incorporating necessary tools for clinicians and patients to enable data collection andanalysis, interpretation of the results, as well as to facilitate treatment choices based on new understandingof biological pathways. The size of datasets and their large variability pose a considerable technicaland statistical challenge. The potential benefits of using PM are as follows: 1) broader possibilities forphysicians to use the achievements of genomics, proteomics, metabolomics, and other "omics" disciplinesin routine clinical practice; 2) better understanding of the pathogenesis and epidemiology of diseases;3) a revised approach to prevention, diagnosis, and treatment of chronic diseases; 4) better integrationof electronic medical records as well as data from sensors and software applications in an interactivenetwork of knowledge aimed at improving the modelling and testing of therapeutic and preventativestrategies, stimulating further research, and spreading information to the general public.