Integrating genomic medicine and artificial intelligence for early and targeted health interventions

Abstract

There is an excess of scientific literature with limited coherence. The current practice of medicine is also all over the place with disciplinary boundaries and scope limitations, and clinicians work in a silo on narrow aspects of wellness and health. Artificial intelligence has created the ability to process vast amounts of information in a coordinated and coherent manner, and works without preconceptions on macro and micro aspects of life with no borders or end points of interest. Genomic medicine has advanced into an area of predictive medicine with the ability to find early risk factors for disease in people for whom there is a lack of clinical indication for testing. This lack of clinical indication is apparent in that genomic medicine testing is almost exclusively limited to family studies or testing of people sick with diseases that have a strong genetic contribution. It is predicted that clinicians will not practice genomic medicine until 2030.

With the further developments in the population-based initiatives that will require genomic medicine testing, the incorporation of genomic testing into a clinical workflow and guidance by AI to create targeted plans for disease prevention and specific monitoring protocols will be essential. The ability to predict a patient’s response to interventions based on biological realities can reduce the lag time associated with the application of novel discoveries to practice and the final reduction in morbidity and mortality. With advances in PCI and Population Data Science and the ever-increasing predictive power of AI, medicine will change from learning from disease, for the treatment of disease, to early and targeted intervention to prevent the actualization of risk for disease.