Clinical OMICS

MAR-APR 2019

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

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14 Clinical OMICs March/April 2019 Katharine Miller Contributing Editor P recision medicine springs from a paradox. On the one hand, researchers in the field seek to characterize ever smaller populations of patients—to the level of a single person (the so-called n-of-one). In that sense, "precision medicine is almost the antithesis of big data," said Shawn Sweeney, director of the American Asso- ciation for Cancer Research (AACR) Project GENIE (Genomics Evidence Neoplasia Information Exchange) Coordinating Center. On the other hand, achieving the desired level of precision will require a medical system that can learn from the experiences and genomic backgrounds of many, many people. This will require robust, reliable, and standardized analyses of deep, broad datasets that include genomic and other molecular data as well as clinical data about patients' journeys and outcomes. Companies aiming to provide pharmacogenomic precision medicine (the right drug to the right person at the right time) are already making significant progress toward gathering and integrating genomic and real-world clinical data to help inform pre- scribing decisions by pharmacies and clinicians. (see sidebar) But it's in the area of precision oncology that most of the action is happening— though significant challenges still loom. "Although we need it, we don't really have big data in healthcare yet," Sweeney said. "A lot of us are in this space to make the data big enough so we can enable automation to hap- pen later on." In addition to building deeper datasets, compa- nies striving to provide precision oncology decision support need to integrate genomic and real-world datasets, standardize and democratize the analyses of such datasets, and create a system that can han- dle ever-increasing types of genomic testing as the field expands. Despite the data challenges, some companies are already demonstrating the value of integrating genomic and real-world data. These projects include Progress Is Being Made Toward Using Big Data for Genomics-Guided Precision Medicine Big Data Clinical Genomics Guarav Singal, Chief Data Officer, Foundation Medicine and

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