Evidence map›Paper›PMID 37461512›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Leveraging Generative AI to Prioritize Drug Repurposing Candidates: Validating Identified Candidates for Alzheimer's Disease in Real-World Clinical Datasets.

Chao Yan, Monika E Grabowska, Alyson L Dickson, Bingshan Li, Zhexing Wen, Dan M Roden, C Michael Stein, Peter J Embí, Josh F Peterson, QiPing Feng and 2 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Chao Yan
Monika E GrabowskaORCID 0000-0003-0708-676X
Alyson L Dickson
Bingshan Li
Zhexing Wen
Dan M Roden
C Michael Stein
Peter J Embí
Josh F Peterson
QiPing Feng
Bradley A Malin
Wei-Qi Wei
Vanderbilt University Medical Center · USVanderbilt University · USEmory University · US

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007347 · NIGMS · VANDERBILT UNIVERSITY · PI WILLIAMS, CHRISTOPHER S. · 1985 to 2023
$26.3M
Genetics and Triglycerides: opportunities for new approaches to identify therapiesR01HL163854 · NHLBI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI FENG, QIPING · 2022 to 2025
$3.1M
Computational drug repurposing for Alzheimer's diseaseF30AG080885 · NIA · VANDERBILT UNIVERSITY · PI Monika Eliana Grabowska · 2023 to 2026
$177k
NHLBI NIH HHS R01 HL163854NIA NIH HHS F30 AG080885NIGMS NIH HHS T32 GM007347
6 · The paper itself

Abstract

Drug repurposing represents an attractive alternative to the costly and time-consuming process of new drug development, particularly for serious, widespread conditions with limited effective treatments, such as Alzheimer's disease (AD). Emerging generative artificial intelligence (GAI) technologies like ChatGPT offer the promise of expediting the review and summary of scientific knowledge. To examine the feasibility of using GAI for identifying drug repurposing candidates, we iteratively tasked ChatGPT with proposing the twenty most promising drugs for repurposing in AD, and tested the top ten for risk of incident AD in exposed and unexposed individuals over age 65 in two large clinical datasets: 1) Vanderbilt University Medical Center and 2) the

Identifiers

PMID37461512
PMCPMC10350158
OpenAlexW4383618467

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.