Eliminating Security, Privacy, and Regulatory Burdens with Synthetic Data

There are many reasons why the sharing of medical data that could be used to gain new insight into diseases can be hampered. Privacy concern, regulatory burdens, and the need to manage security risks are among the significant impediments. Syntegra believes it can solve these problems through its artificial intelligence technology that creates synthetic datasets designed to mirror the statistical properties of real datasets while removing all links to the original patients behind the data. We spoke to Michael Lesh, co-founder and CEO of Syntegra, about the obstacles to data-sharing, how synthetic datasets are developed, and why they might accelerate the pace and lower the cost of research.