Mount Sinai taps Margolin to lead $200M big data efforts

The Icahn School of Medicine at Mount Sinai has tapped computational biologist Adam Margolin to head its big data initiatives.

Margolin, a leader in developing machine-learning algorithms to analyze large-scale molecular datasets, has been named professor and chair of the Department of Genetics and Genomic Sciences as well as senior associate dean of precision medicine.

In addition, Margolin—who was director of computational biology and professor of biomedical engineering at Oregon Health & Science University—will lead Mount Sinai’s Icahn Institute, which has been renamed the Icahn Institute for Data Science and Genomic Technology.

The organization is making a large investment in technology, starting a 10-year, $200 million big data initiative meant to predict new therapies for complex diseases.

“With Adam Margolin at the helm, Mount Sinai is committed to recruiting world-class data scientists—the same type of people who would otherwise be working in hedge funds or big tech startups—who can apply those skills to analyzing enormous amounts of data on patients,” says Dennis Charney, MD, dean of the Icahn School of Medicine and president for academic affairs of the Mount Sinai Health System.

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According to Mount Sinai, during the next 10 years the organization plans to recruit 30 new faculty members focused on data science and genomic technology as well as 25 data scientists to lead projects aimed at interpreting large-scale biomolecular data as well as launch cross-institutional, cross-disciplinary projects to discover new precision therapies in core disease areas, among other activities.

“We are committed to pursuing bold new initiatives that enable the best people to work together to unlock insights from massive datasets that will revolutionize our ability to treat a multitude of diseases,” adds Charney.

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According to Margolin, the $200 million team-oriented big data program will be based on three pillars—data science, genomic technology and clinical translation. Unlike traditional academic models organized around siloed individual labs, the program “will be built from the outset to enable world-class data scientists, technology innovators and disease experts to advance large-scale team-oriented goals,” he says.

“By fundamentally changing the understanding of complex diseases, we can customize diagnosis, prevention and treatment to individual patients,” Margolin adds. “We will bring together the top data scientists, genomic technology innovators and disease experts who will work side by side every day to understand the molecular causes of complex diseases, rapidly test new therapies derived from these insights, and bring these therapies to patients faster than ever before.”

He adds that artificial intelligence and machine learning are the foundation of the initiative to create insights from the large amounts of data.

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