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TRUVACE RECORD VERSION
record: TRV-2026-1151
version: 2
kind: revised
reason: Direction audit: filed as a gain but describes a problem.
timestamp: 2026-10-26T06:38:43.009402Z
status: published
lens: p_space
sector: policy
headline: Artificial Intelligence in Pharmaceutical Regulatory Science: Opportunities, Challenges, and Emerging Frameworks
dek: Digital transformation in pharmaceutical regulatory affairs is accelerating as global submissions grow in complexity and traditional document-based workflows reach their limits. Artificial intelligence (AI), particularly natural language processing (NLP), is increasingly being explored to support regulatory data management, document preparation, and decision support activities. This review examines AI adoption across pharmaceutical regulatory science, including initiatives from major regulatory agencies, AI-supp…
gain_title: (none)
problem_title: Robust evidence of sustained improvements in regulatory performance and long-term impact from AI in pharmaceutical regulation remains limited.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Robust evidence of sustained improvements in regulatory performance and long-term impact from AI in pharmaceutical regulation remains limited.
problem_evidence: (none)
quick_read: Digital transformation in pharmaceutical regulatory affairs is accelerating as global submissions grow in complexity and traditional document-based workflows reach their limits. Artificial intelligence (AI), particularly natural language processing (NLP), is increasingly being explored to support regulatory data management, document preparation, and decision support activities.

This review examines AI adoption across pharmaceutical regulatory science, including initiatives from major regulatory agencies, AI-supported regulatory workflows, and emerging governance and interoperability frameworks. The review further examines emerging regulatory data ecosystems and governance frameworks that may support the responsible integration of AI into regulatory processes.
limitation: 
tag: Evidence-backed problem
key_points: Digital transformation in pharmaceutical regulatory affairs is accelerating as global submissions grow in complexity and traditional document-based workflows reach their limits. | Artificial intelligence (AI), particularly natural language processing (NLP), is increasingly being explored to support regulatory data management, document preparation, and decision support activities. | This review examines AI adoption across pharmaceutical regulatory science, including initiatives from major regulatory agencies, AI-supported regulatory workflows, and emerging governance and interoperability frameworks.
rundown: Digital transformation in pharmaceutical regulatory affairs is accelerating as global submissions grow in complexity and traditional document-based workflows reach their limits. Artificial intelligence (AI), particularly natural language processing (NLP), is increasingly being explored to support regulatory data management, document preparation, and decision support activities.

This review examines AI adoption across pharmaceutical regulatory science, including initiatives from major regulatory agencies, AI-supported regulatory workflows, and emerging governance and interoperability frameworks. Current applications include document classification, data extraction, Common Technical Document (CTD) support, pharmacovigilance, and predictive analytics.
sources:
- peer_reviewed | The AAPS Journal | https://doi.org/10.1208/s12248-026-01283-2 | 2026-09-18
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