Quantify unmet medical need across the disease landscape – A large language model-based methodology
This accessible, scalable methodology enables funders and researchers, across governments, universities, healthcare organizations, and disease groups to tailor prioritization efforts according to unmet medical need in the context of their organizational objectives, by selecting appropriate criteria and weighting of those criteria. This method creates a pragmatic and transparent tool to streamline research prioritization. Future research should consider expanding the disease set size used to create scores.
Authors
- David C. Fajgenbaum (ORCID: https://orcid.org/0000-0002-7367-8184)
- Nicholas Ronald Fragola (ORCID: https://orcid.org/0000-0002-3049-6145)
- Lee Lancashire (ORCID: https://orcid.org/0000-0003-4835-4847)
- Matthew M. Goddeeris (ORCID: https://orcid.org/0000-0001-6346-7220)
- Charlotte Olivia Blewitt
- Charlie Hempstead
- Elliott W. Sharp
Institutions
- University of Pennsylvania (US)
Publication Details
- Journal
- PLoS Medicine
- Published
- 2026-03-12
- DOI
- https://doi.org/10.1371/journal.pmed.1004798
- Primary Topic
- Health Systems, Economic Evaluations, Quality of Life
- Type
- article
- Field-Weighted Citation Impact
- 0.00