Cedars-Sinai is adopting a synthetic data platform to enhance research and clinical care, enabling teams to work with AI-generated datasets that mimic real patient data while maintaining privacy and security.
The Los Angeles-based health system is partnering with Amsterdam-based Syntho, which uses AI to generate fully anonymous datasets that mimic real patient information. Unlike de-identified data, which removes patient identifiers from real records, synthetic data is entirely artificial but preserves patterns and relationships in the original data.
Craig Kwiatkowski, PharmD, Cedars-Sinai’s senior vice president and chief information officer, said in an Oct. 15 press release that the move supports the health system’s goal of building a connected data ecosystem that gives teams easier access to a wider range of information.
Synthetic data can replicate patient profiles and treatment scenarios within an hour, reducing the time needed to prepare real patient records. Researchers, students, and trainees can use these datasets for studies, tool development, and analyses without privacy concerns or lengthy approval processes.
Jason Moore, PhD, chair of the Department of Computational Biomedicine, and Nicholas Tatonetti, PhD, vice chair, are leading the research. They said the approach could enable faster studies, more collaboration, and research on complex conditions such as rare diseases.
Cedars-Sinai is also integrating synthetic data with its new Digital Innovation Platform, working with internal teams, investors, and Redesign Health to develop tools addressing pressing healthcare challenges.
