Evidence map›Paper›PMID 39323347›Full record

ReviewCNS & neurological disorders drug targets2025

Revolutionising Neurological Therapeutics: Investigating Drug Repurposing Strategies.

Meenakshi Attri, Asha Raghav, Jyoti Sinha

Abstract readReview
PubMed Publisher
In one paragraph

Review in CNS & neurological disorders drug targets, 2025. 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.

No citing paper in PubMed yet.

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.

Meenakshi AttriSchool of Medical & Allied Sciences, K.R. Mangalam University, Gurugram, Haryana 122103, India.ORCID 0000-0003-1605-177X
Asha RaghavDepartment of Pharmaceutics, School of Health Sciences, Sushant University, Gurugram, Haryana 122003, India.ORCID 0000-0002-5724-6912
Jyoti SinhaDepartment of Pharmaceutics, School of Health Sciences, Sushant University, Gurugram, Haryana 122003, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Repurposing drugs (DR) has become a viable approach to hasten the search for cures for neurodegenerative diseases (NDs). This review examines different off-target and on-target drug discovery techniques and how they might be used to find possible treatments for non-diagnostic depressions. Off-target strategies look at the known or unknown side effects of currently approved drugs for repositioning, whereas on-target strategies connect disease pathways to targets that can be treated with drugs. The review highlights the potential of experimental and computational methodologies, such as machine learning, proteomic techniques, network and genomics-based approaches, and in silico screening, in uncovering new drug-disease correlations. It also looks at difficulties and failed attempts at drug repurposing for NDs, highlighting the necessity of exact and standardised procedures to increase success rates. This review's objectives are to address the purpose of drug repurposing in human disorders, particularly neurological diseases, and to provide an overview of repurposing candidates that are presently undergoing clinical trials for neurological conditions, along with any possible causes and early findings. We then include a list of drug repurposing strategies, restrictions, and difficulties for upcoming research.

Indexed as

Drug RepositioningNervous System DiseasesNeurodegenerative DiseasesAnimalsDrug DiscoveryHumansartificial Intelligence (AI)computational methodDrug Repurposingexperiment-basedgenomics-based methodin-silico based methodmachine learning.network-based methodneurodegenerative diseases (NDs)

Identifiers

What OpenQuestion holds

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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.