The Future of Precision Medicine

Precision Medicine (PM) is a medical paradigm which integrates all data available on an individual patient, enabling a multifactorial approach to the tailoring of treatment to the individual.  For this discussion regarding the future of PM, we will apply a definition that includes "aligning and integrating diverse, unstructured, data sets into a comprehensive knowledge network”(Hawgood et al.).  The knowledge network drives PM in ways that enable physicians and patients to identify and implement tailored treatments and diagnostics by joining disparate data to answer complex questions.

PM includes the ability to join and distil different and relevant data elements into relevant information and real-world insights, as illustrated in Figure 2, and can range from sim

ple qualitative work to more sophisticated analytics, including in the form of machine learning.

The areas of greatest growth – and challenges – in PM will likely be in the joint presentation and utilization of diverse types of data (e.g., EMR, EHR, genomic) in clinical decision making, and in the regulation and approval of drugs through clinical trials into the real world.   A recent study overviewing the FDA’s Office of Pharmaceutical Quality illustrates the FDA “[emphasis on]  the importance of linking both biomarkers and drug quality attributes to the clinical performance, safety, and efficacy of a drug product”(Fisher et al.). 

As we begin to join data together to answer complex questions our current medical clinical system of treatment – though improving – remains highly linear and specialized in that a patient is often shuttled around multiple providers to better understand their condition(s), and the subsequent implications for its management.  Precision medicine will allow for the assessment of this person more holistically to help drive a targeted approach to treatment on a multifactorial evidence base, assuming that the provider has access to the various components of the patient’s records. A thought process reflected in a recent report from the Symposium of the International Society for Strategic Studies in Radiology, that states  "emerging discipline of radiogenomics, which links genotypic information to phenotypic disease manifestations at imaging should also significantly contribute to patient-tailored care"(Herold et al.). 

While the principles underlying PM are a natural progression in the evolution of medicine, there are tremendous challenges as well in its operationalization.  PM will require a renewed mindset that resets our approach to training our science students and clinicians, data are handled and shared, and ultimately utilized for care delivery. 


Fisher, A. C., et al. "Advancing Pharmaceutical Quality: An Overview of Science and Research in the Us Fda's Office of Pharmaceutical Quality." International Journal of Pharmaceutics 515.1-2 (2016): 390-402. Print.

Hawgood, S., et al. "Precision Medicine: Beyond the Infection Point." Science Translational Medicine 7.300 (2015). Print.

Herold, C. J., et al. "Imaging in the Age of Precision Medicine: Summary of the Proceedings of the 10th Biannual Symposium of the International Society for Strategic Studies in Radiology." Radiology 279.1 (2016): 226-38. Print.

About the Contributors

Stuart Rabinowitz, MBA, MSHI is the Director of Federal Health Data and Informatics programs within QuintilesIMS’s IMS Government Solutions organizations. Stuart holds an undergraduate degree from Temple University, an MBA from Lehigh University, and a Master’s of Science in Health Informatics from the University of Illinois at Chicago.

Maria Murray, PhD is a Senior Consultant in IMS Government Solutions, part of QuintilesIMS. She received her PhD from the University of Pennsylvania in Bioengineering. Previously, she worked as an AIMBE Policy Scholar at the Center for Devices and Radiological Health at the US Food and Drug Administration and Deloitte Consulting.

Nandini Selvam, PhD, MPH, VP, Real World Insights QuintilesIMS, IMS Government Solutions

Nandini is responsible for providing scientific input, and planning and managing resources within IMS Government Solutions, QuintilesIMS. Nandini received her Ph.D in Epidemiology, with a focus on infectious diseases, from the School of Public Health, Rutgers University (previously University of Medicine and Dentistry of New Jersey), and did her post-doc as an Epidemic Service Intelligence Officer at the Centers for Disease Control and Prevention.