Why Synthetic Data is the Antidote to Clinical Trials
To address the clinical burden and enhance R&D, companies are turning to virtual solutions. This involves synthetic data, digital twin models, and AI to speed analysis.
To address the clinical burden and enhance R&D, companies are turning to virtual solutions. This involves synthetic data, digital twin models, and AI to speed analysis.
By coupling synthetic data with simple, easy to use extraction and modeling tools, clinicians can be granted free access to the breadth of their health systems’ data, allowing them “self-service” to ask their own novel questions that can yield new insights to spur patient care quality improvement initiatives.
Enterprise EHR boosts scalability, interoperability, and governance for large healthcare systems.
Health analytics firm Aetion has acquired Replica Analytics, a company that specializes in synthetic data. Aetion said Replica will enable it to analyze previously inaccessible data while maintaining privacy and integrity of the original source data.
Clear use-cases to fully understand how the synthetic data will be deployed are an essential component of the decision making process, and although by nature synthetic data isn't ‘real’, its existence within the data supply chain should still fall under data governance and security policies.