AI for Bioanalytical Study Risk Assessment and Inspection Readiness
Description
Challenges in assessing large amounts of analytical/bioanalytical study information for risk assessment and inspection preparation in a short period of time
Detailed example
Summary including reanalysis, deviations from method SOPs or protocols, inconsistencies or gaps in data reporting, deviations from data acceptance criteria, and deviations from the method validation; description of potential impact on study outcome. Outputs are verified by FDA staff.
AI / analytics pattern
Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
Efficient and thorough review of bioanalytical portions of pivotal studies, enabling risk assessors and reviewers to identify and address potential issues. This benefit promotes public health by ensuring the welfare of study subjects, and helping the office verify the quality, study integrity, and regulatory compliance of Bioavailability/Bioequivalence (BA/BE) studies supporting CDER-regulated drugs.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
No FDA data were used to train, fine-tune or evaluate