Protocol Design and Recruitment Risks: AI’s Hidden Compliance Traps in Clinical Trials | Husch Blackwell LLP
https://www.jdsupra.com/legalnews/protocol-design-and-recruitment-risks-2341966/
Publish Date: 2026-05-19 14:26:00
Source Domain: www.jdsupra.com
- Accelerated Timelines vs. Reproducibility: While AI speeds up protocol development and patient recruitment, the outputs are non-deterministic, creating challenges in validating protocols and ensuring reproducibility under regulatory standards like ICH E6(R2).
- Validation and Documentation Challenges: AI outputs can’t always be traced and explained, which disrupts the required audit trails and thorough documentation during FDA inspections. Incomplete validation can lead to significant compliance issues.
- Algorithmic Bias in Recruitment: AI recruitment algorithms risk systematically excluding certain populations due to biases in their training data, violating FDA guidelines that emphasize diverse participant enrollment for reliable scientific results.
- Regulatory and Compliance Implications: Sponsors remain liable for protocol quality and diverse enrollment, but AI tools’ complexity diffuses accountability across opaque algorithms, leading to potential FDA enforcement actions or non-compliance findings.
