The publication of Complete Response Letters (CRLs) from the FDA has increased transparency into regulatory decision-making. These letters provide detailed explanations of why applications are not approved, offering direct visibility into how regulators assess evidence, identify deficiencies, and justify their conclusions.

As the number of published CRLs grows, so does the opportunity to examine recurring themes and patterns across programs. AI-supported methods can assist in organizing and comparing this material, but interpretation and application remain dependent on regulatory expertise.

This white paper examines the potential and limits of learning from published Complete Response Letters.

Authors

Debra Aub Webster

SVP, Regulatory

Ingela Loell

Scientific Editor

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