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.

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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
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article

Quantify unmet medical need across the disease landscape – A large language model-based methodology

David C. Fajgenbaum, Nicholas Ronald Fragola, Lee Lancashire, Matthew M. Goddeeris et al.
PLoS Medicine
Health Systems, Economic Evaluations, Quality of Life
article

Quantify unmet medical need across the disease landscape – A large language model-based methodology

David C. Fajgenbaum, Nicholas Ronald Fragola, Lee Lancashire, Matthew M. Goddeeris, Charlotte Olivia Blewitt, Charlie Hempstead, Elliott W. Sharp
article en

Abstract

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.

PLoS MedicineVol. 23(3)
University of Pennsylvania (US)
Openalex Percentile: Top 28%
Health Systems, Economic Evaluations, Quality of Life
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