Synthetic Data's Value In Clinical Research

Synthetic data is a form of generative artificial intelligence (AI) that, in the life sciences is especially valuable for enhancing datasets and increasing diversity in clinical trials. Explore the transformative role of synthetic data in clinical research and the potential to enhance AI models and improve data diversity. While real-world data (RWD) is prevalent in pharmaceutical studies, synthetic data provides a vital alternative by simulating diverse patient scenarios and safeguarding privacy. Key use cases include protecting patient identities, training AI with more comprehensive datasets, and filling gaps in existing RWD. By leveraging generative AI techniques, such as generative adversarial networks, researchers can foster innovation and improve efficiency, ultimately driving advancements in medical understanding and patient care.