Abstract
Abstract Artificial Intelligence (AI) has impacted a board range of scientific disciplines that are important to public health, ranging from clinical diagnosis and prognosis, drug and food safety, disease prevention, precision medicine and nutrition. The rise of AI has also offered both opportunities and challenges to regulatory agencies with questions such as (1) how to assess and evaluate AI-based products and (2) how to develop and implement AI-based application to improve the agencies functions. In this presentation, the current thinking and on-going efforts at FDA in the area of AI will be discussed with examples from drug safety and biomarker discovery and development. The guiding principle and best practice of applying AI in regulatory science research will also be discussed with respect to a proposed framework, called TRIAL, for AI transparency, reproducibility, interpretability, applicability and liability. Citation Format: Weida Tong. Artificial intelligence for regulatory science research [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr IA-26.
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