Evidence map›Paper›PMID 40808416›Full record

ArticleNeural regeneration research2026

Six promising drug repurposing candidates for Alzheimer's disease and their sex-specific mechanisms and efficacy.

Maria E Figueiredo-Pereira, Peter A Serrano, Patricia Rockwell

Abstract read
In one paragraph

Article in Neural regeneration research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Maria E Figueiredo-PereiraDepartment of Biological Sciences, Hunter College CUNY, New York, NY, USA.ORCID 0000-0001-5131-4315
Peter A SerranoDepartment of Psychology, Hunter College CUNY, New York, NY, USA.
Patricia RockwellDepartment of Biological Sciences, Hunter College CUNY, New York, NY, USA.

Funding

Drug repurposing for Alzheimer's disease using structural systems pharmacology.R01AG057555 · NIA · NORTHEASTERN UNIVERSITY · PI Lei Xie · 2018 to 2026
$6.7M
NIA NIH HHS R01 AG057555
6 · The paper itself

Abstract

Alzheimer's disease is a neurodegenerative disorder that leads to progressive memory loss, cognitive decline, and behavioral changes. Despite ongoing research, its exact causes and effective treatments remain elusive. Traditional approaches have focused on symptom management, but breakthroughs in bioinformatics and high-throughput drug screening are offering new pathways to potential therapies. This review highlights our recent efforts to identify novel drug candidates for Alzheimer's disease by leveraging computational methods and large-scale biological datasets. Our work introduces two key innovations in Alzheimer's disease research: addressing sex-specific differences and leveraging drug repurposing for accelerated treatment discovery. By combining sex-stratified preclinical data with machine learning and in vivo validation, we improve translational relevance and support precision medicine. Using the TgF344-AD rat model, which mimics human Alzheimer's disease spatial memory deficits and pathology, we explored the efficacy of various US Food and Drug Administration-approved and investigational drugs. These included ibudilast, timapiprant, RG2833, diazoxide/dibenzoylmethane (combined), and BT-11, which targeted key Alzheimer's disease-related molecular pathways such as amyloid-beta plaques, Tau tangles, and neuroinflammation. These drugs, at various stages of development, offer hope for not only managing symptoms but also addressing the underlying mechanisms of Alzheimer's disease. This review underscores the need for a multifaceted approach to Alzheimer's disease treatment, combining symptom relief with disease modification.

Indexed as

Alzheimer’s diseaseBT-11diazoxidedibenzoylmethanedrug repurposinghigh-throughput drug approachibudilastRG2833TgF344-AD rat modeltimapiprant

Identifiers

PMID40808416
PMCPMC13378927

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.