Informatics and Artificial Intelligence–Guided Assessment of the Regulatory and Translational Research Landscape of First-in-Class Oncology Drugs in the United States, 2018-2022
Novel first-in-class cancer treatments are defined by diverse clinical indications, personalized molecular targets, dependence on expedited regulatory pathways, and translational research metrics reflecting this complex landscape. Biomedical informatics and AI provide scalable, data-driven ways to assess and even address important challenges in the drug development pipeline.
Authors
- Brett R. South
- Jay G. Ronquillo (ORCID: https://orcid.org/0000-0002-0438-7172)
- Rominder Singh (ORCID: https://orcid.org/0009-0001-8298-8176)
- Aida Habtezion (ORCID: https://orcid.org/0000-0002-4473-006X)
- Magdia De Jesus (ORCID: https://orcid.org/0000-0002-0713-8462)
- Stephen Watt (ORCID: https://orcid.org/0000-0003-1403-5493)
- Prakash S. Naik
Institutions
- Pfizer (United States) (US)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1200/cci.24.00087
- Citations
- 3
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 1.08