How <scp>AI</scp> Transforms Regulatory Submission: Current Clinical Implementation and Future Prospects
Artificial Intelligence (AI) is transforming drug development and regulatory submission by enabling advanced data analytics, predictive modeling and intelligent decision support systems. Beyond efficiency gains, AI establishes a translational bridge between model-informed drug development (MIDD) and clinical implementation, turning regulatory evidence into actionable insights that enhance therapeutic precision and patient outcomes. This perspective paper explores AI's current applications, regulatory integrations, and future prospects in accelerating data-driven, patient-centered drug development.
Authors
- Jagdeep T. Podichetty (ORCID: https://orcid.org/0009-0001-3922-3549)
- Anna‐Marika Bauer (ORCID: https://orcid.org/0000-0001-8914-389X)
- Nick Henscheid (ORCID: https://orcid.org/0000-0002-9361-6976)
- Klaus Romero (ORCID: https://orcid.org/0000-0002-8576-8638)
- Rachel Xu (ORCID: https://orcid.org/0000-0002-4651-5099)
- Adnan Shahid Khan (ORCID: https://orcid.org/0000-0002-3924-3646)
- Wes Anderson
- Shu Chin (ORCID: https://orcid.org/0009-0002-0343-1861)
- Hien Q. Huynh (ORCID: https://orcid.org/0000-0002-7295-7595)
Institutions
- Critical Path Institute (US)
Publication Details
- Journal
- Clinical and Translational Science
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1111/cts.70434
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65
Funders
- U.S. Department of Health and Human Services