In 2020, synthetic data company MDClone announced the creation of a global network of health systems to explore ideas together to improve patient health. One network member, Philadelphia-based Jefferson Health, recently described how it will leverage MDClone's synthetic data platform to accelerate academic research.
MDClone described its ADAMS Platform as a self-service data analytics environment that enables healthcare collaboration, research, and innovation. By making real-world data easier to access, the ADAMS Platform will help Jefferson researchers reduce the friction points to formulating academic research questions, identifying relevant data, analyzing the data, and producing results, the company said.
The ADAMS platform will deliver streamlined workflows, enabling Jefferson researchers to more easily access and analyze data from electronic health records, which is often difficult to access due to inconsistencies in the data and restrictive privacy regulations.
The platform also will provide Jefferson's students with anonymous, real-world data they can use to test their own theories and explore their own strategies for population health improvement. Additionally, the platform will create new opportunities for Jefferson to partner with life sciences companies to inform and accelerate new therapeutic discoveries.
"Academic researchers face significant challenges in accessing healthcare data, such as siloed systems, long timelines, and complex data models," said Billy Oglesby, dean of the Jefferson College of Population Health, in a statement. "Our collaboration with MDClone will create a more frictionless ecosystem for researchers to access clinical data, driving quicker timelines from idea to impact, including commercialization."
In addition to leveraging MDClone's self-service exploration and synthetic data platform to create a faster path to knowledge generation for Jefferson researchers, the organizations have established a commercial collaboration to provide third-party organizations with access to Jefferson's data assets. Through this arrangement, organizations such as life sciences companies and medical device manufacturers will gain the ability to discover insights to fuel the next generation of therapies, technologies, and solutions in a secure, efficient, and controlled environment.
"MDClone's state-of-the-art proprietary data synthesis process transforms patient-identifiable data into non-identifiable data while still retaining all the important statistical and contextual properties," said Ziv Ofek, co-founder and CEO of MDClone, in a statement. "Using both discrete and non-discrete variables of interest, synthetic data does not contain identifiable information because it uses a statistical approach to create a data-set that is non-reversible and the only method that fully prevents re-identification."
