Mount Sinai opens biomedical blockchain research center
The Icahn School of Medicine at Mount Sinai and the Institute for Next Generation Healthcare announced the opening of the Center for Biomedical Blockchain Research to use new technologies and data to work on healthcare and medical science problems.
The new centers come as many health systems are curious about real-world use cases and deployments of blockchain and analyst firms IDC and Gartner tell IT executives that the time to create strategies around the technology or risk being left behind by rival hospitals that move first.
Joel Dudley, executive vice president of Precision Health at Mount Sinai, heads the new center. Dudley’s research focuses on machine intelligence to solve problems in biology and the new center will complement that work by developing predictive health applications from EHRs, wearables, and related digital health information.
He was the co-founder of a venture-backed health tech startup and served as a senior data scientist at Pivotal Software, where he delivered predictive models for multibillion-dollar companies in healthcare and biotech.
Mount Sinai said the new center’s research will lay the groundwork for its forthcoming industry partnership program aimed at companies looking to develop biomedical blockchain that helps identify and address problems in clinical medicine and biomedical research.
“This experience will allow us to address many of the most promising uses for blockchain in biomedicine with the goal of improving healthcare delivery and reducing costs,” Dudley said in a statement. “Many companies are already exploring the use of blockchain technologies in biology and healthcare.”
Potential applications include drug development, clinical research trials, improving quality control in the pharmaceutical industry to reduce counterfeit drugs, and enhance research reproducibility.
“Our aim is to understand how blockchain and associated technologies can be applied to unmet needs in healthcare and biomedicine,” Dudley added.
Dudley and his colleagues expect early use cases to emerge from areas where existing systems and approaches fall short.