Synthetic Control Arms (SCAs) use patient-level real-world data (RWD) to replace or supplement traditional control groups in clinical trials, improving efficiency and ethics. SCAs reduce reliance on placebos, accelerate timelines, and lower costs while enhancing validity and generalizability. Applications include oncology, rare diseases, and COVID-19 vaccine studies, where SCAs enabled ethical designs and faster approvals. AI is also being explored to generate synthetic datasets for hematologic neoplasms, addressing data gaps. Challenges remain in RWD quality, disease predictability, and regulatory alignment, but SCAs are becoming a cornerstone of modern trial design.

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