Big Data, Artificial Intelligence, and the Promise of Precision Medicine: A Johns Hopkins Collaboration to Develop the Precision Medicine Analytics Platform

Abstract

Despite advances in knowledge and technology, approaches to health care discovery and delivery have not broadly kept pace with those advancements. While there have been notable improvements in shaping diagnosis and treatment resulting from knowledge made available through advances in technology, the field generally uses broad population characteristics as the basis for determining the health of, and how to treat, individuals. Today, with the confluence of big data and artificial intelligence (AI), we have an opportunity to tailor diagnoses and treatments precisely as needed for an individual—in other words, to practice precision medicine. The Johns Hopkins University Applied Physics Laboratory (APL) and Johns Hopkins Medicine (JHM), in partnership with the Bloomberg School of Public Health, Johns Hopkins Information Technology, and others across the institution, are working to usher in this new paradigm. These organizations jointly developed the Precision Medicine Analytics Platform (PMAP). This platform pulls data from many sources, aggregates the data, and then provisions needed data to approved researchers in a secure environment where they can apply advanced techniques and other tools to analyze the data. The guiding vision is to create and sustain the ability to accelerate gaining knowledge and value from data and from closing the loop between discovery and delivery, ultimately reducing health care costs and improving patient outcomes.