Semantic Graph Analytics Can Propel The Advent of 'Personalized Medicine'

By Dr. Jans Aasman, CEO, Franz Inc.

Analyzing massive stores of medical data can be overwhelming. Still, it’s an important mission: data analysis could provide new, more tailored treatments. Terms like “personalized medicine,” “precision medicine,” and “individualized medicine” all refer to a data-driven approach toward to goal of customizing medical treatment for every patient’s unique genetic and molecular composition. However noble, that goal is somewhat limited.

Personalized medicine, often described as a way to provide “the right patient with the right drug at the right dose at the right time,” in fact goes beyond custom treatment – it encompasses the entire healthcare process, from prevention, to treatment, to disease management, and considers each patient as an individual.

In his 2015 State of Union address, President Barack Obama promised to dedicate $215 million in the 2016 budget to the Precision Medicine Initiative. This project, which Obama says has bipartisan support in Congress, will fund research aimed at understanding how to best develop personalized medical treatments.

Planned disbursements include $130 million for the National Institutes of Health (NIH) to form a research group of one million volunteers who will contribute their health data for analysis, $10 million to the U.S. Food and Drug Administration (FDA) to build the necessary databases, and $5 million to secure patient data. The budget also includes $70 million for a pilot project by the National Cancer Institute (NCI), aimed at developing precision treatments for cancer.

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