Next-Generation Technologies for Early Disease Detection and Treatment: Harnessing Intelligent Systems and Genetic Innovations for Improved Patient Outcomes
Mahesh Recharla, Sai Teja Nuka, Chaitran Chakilam, Karthik Chava, Sambasiva Rao Suura
Abstract
There are significant challenges to developing improved technologies for the early detection and treatment of emerging diseases. Early detection requires reducing the time it takes to identify and test potential reasons for emerging human diseases. New technological advancements in next-generation sequencing and the annotations of human genomes provide an opportunity to leverage such information to design new ways of testing individuals for the presence and progression of diseases. Deep-sequencing approaches toward the construction of human DNA, RNA, and protein annotations present new opportunities for understanding the pathophysiology underlying differences in individual responses to pathogens and other environmental factors. This paper discusses a vision of next-generation technologies and how the challenge of early disease detection motivates research aimed at developing a set of new sensor platforms. Such technologies may revolutionize early detection diagnostic tests and dramatically improve response times. Our goal is to support the development of advanced sensor technologies required to inform treatment decisions, to manage maladies ranging from day-to-day ailments to the horrors of newly emerging infectious diseases. Our approach—developing advanced sensors and associating rapidly with annotations of genomes to inform treatment decisions—will use a virus as a case study because it is a challenge for biomarker discovery that can be used in drug design and diagnostics development. As such, our approach provides proof of concept validation and advanced next-generation sequencing methods that will enable diagnostics development for other new diseases.