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Enabling the Clinical Adoption of Genomics to Solve Mystery Diagnoses and Improve Patient Outcomes

Sivan Bercovici (SV Bio)
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A rapid decline in the cost of next-generation genome sequencing (NGS) and concomitant increases in accuracy are enabling a fundamental shift in how we manage patients. But to close the gap between the promise of personalized medicine and actual implementation within the clinical setting will require widespread clinical adoption of genomic-based medicine to inform decision-making. It is now possible for clinical providers to take advantage of rapidly-expanding genomic information within a typical clinical workflow, reaching diagnostic clarity for mystery diseases that have been so vexing, and identifying treatment pathways and/or facilitating new targeted research that could yield new therapeutic options. A new diagnostics platform has recently been developed that can determine with clinical grade sensitivity and specificity which genetic variants within a patient’s DNA sequence are influencing a disease or condition. The clinical reports are clinician-friendly – with actionable summaries that enable medical practitioners to apply the results to patient care. The first case study will focus on recent collaborative efforts with a premier US healthcare system and their Center for Individualized Medicine to accelerate and improve the interpretation and presentation of genomic data and will describe integration of the platform into the largest CAP/CLIA esoteric DNA testing laboratory in the country to deliver timely, targeted diagnoses and treatment decisions. The second case study will describe the clinical utility of comprehensive genetic testing as a front-line diagnostic strategy. This case involved a family who had been through an exhausting three-year search for a cause to the debilitating disease suffered by two of their five children, which was diagnosed quickly and inexpensively using this new diagnostic platform. Unfortunately, this is not an isolated case. Up to 40 percent of individuals suffering from a genetic disease never achieve a molecular diagnosis. As a result, millions of individuals are searching in vain for effective care; a rapid molecular-based diagnosis may open up important clinical opportunities for those patients.

Photo of Sivan  Bercovici

Sivan Bercovici

SV Bio

Sivan Bercovici is a member of the founding team at SV Bio, and serves as the company’s Chief Technology Officer. Throughout his academic carrier, his primary research interest has been developing and applying machine-learning to problems in human genetics and to the study of human disease. Over the years, his growing emphasis has been on deriving efficient and effective methods for the analysis of large amounts of data stemming from studies of large cohorts and their genomes. In particular, he has developed genetic mapping methods of medical relevance, including contributions to the study of families via linkage-analysis, hidden-relatedness via identity-by-descent genetic mapping, and uncovering the hidden relation between ancestry and genetic disorders via admixture-mapping, offering new ways to predict inherited risks of diseases, with immediate implications on preventive and therapeutic solutions.
Dr. Bercovici holds a Ph.D. in Computer Science from the Technion – Israel Institute of Technology. He also received an M.A. in Computer Science from the Technion. Dr. Bercovici was a postdoctoral researcher at Stanford’s Artificial Intelligence Laboratory, where he continues to contribute as a senior research scientist.

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