Enabling Technologies for Personalized and Precision Medicine. Issue 5 (May 2020) - Ho, Dean; Quake, Stephen R.; McCabe, Edward R.B.; Chng, Wee Joo; Chow, Edward K.; Ding, Xianting; Gelb, Bruce D.; Ginsburg, Geoffrey S.; Hassenstab, Jason; Ho, Chih-Ming; Mobley, William C.; Nolan, Garry P.; et al.
Abstract : Individualizing patient treatment is a core objective of the medical field. Reaching this objective has been elusive owing to the complex set of factors contributing to both disease and health; many factors, from genes to proteins, remain unknown in their role in human physiology. Accurately diagnosing, monitoring, and treating disorders requires advances in biomarker discovery, the subsequent development of accurate signatures that correspond with dynamic disease states, as well as therapeutic interventions that can be continuously optimized and modulated for dose and drug selection. This work highlights key breakthroughs in the development of enabling technologies that further the goal of personalized and precision medicine, and remaining challenges that, when addressed, may forge unprecedented capabilities in realizing truly individualized patient care. Highlights: Engineering approaches to precision medicine will harness population-wide data to identify individualized treatment strategies. Personalized medicine harnesses a subject's own data to individualize their own care, from diagnosis through treatment selection and monitoring. Novel clinical trial designs will play a vital role in assessing the efficacy and safety of emerging therapies and diagnostics. Artificial intelligent platforms will globally optimize combination therapy from the preclinical through clinical stages of validation. The widespread deployment of precision and personalized medicine technologies will involve the convergence of several factors ranging from evolving education at the interface of engineering and medicine and policies that support new clinical trial designs, to scaling the use of electronic medical records (EMR) to drive clinical decision support.