Evidence map›Paper›PMID 31326236›Full record

ReviewTrends in pharmacological sciences2019

Insights into Computational Drug Repurposing for Neurodegenerative Disease.

Manish D Paranjpe, Alice Taubes, Marina Sirota

Open access · greenAbstract readReview
In one paragraph

Review in Trends in pharmacological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
9.8field-weighted citation impact, top 2% of its field
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

46 citing papers in PubMed, 73 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. A Deep Subgrouping Framework for Precision Drug Repurposing via Emulating Clinical Trials on Real-world Patient Data.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2025
    Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Review
  16. Tackling neurodegenerationFrontiers in molecular neuroscience · 2024
    Review
  17. Article
  18. Review
  19. Review
  20. Review
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 at 2 institutions in 1 country.

Manish D ParanjpeBakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA. Electronic address: manish.paranjpe@ucsf.edu.
Alice TaubesGladstone Institutes, San Francisco, CA 94158, USA.
Marina SirotaBakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA; Gladstone Institutes, San Francisco, CA 94158, USA. Electronic address: marina.sirota@ucsf.edu.
University of California, San Francisco · USGladstone Institutes · US

Funding

PREDOCTORAL TRAINING IN BIOMEDICAL SCIENCEST32GM008568 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ANSEL, KARL MARK · 1995 to 2019
$6.3M
ApoE Genotype-Directed Drug Repositioning and Combination Therapy for Alzheimer's DiseaseR01AG057683 · NIA · J. DAVID GLADSTONE INSTITUTES · PI HUANG, YADONG, SIROTA, MARINA · 2017 to 2021
$4.3M
An Integrative Multi-Omics Approach to Elucidate Sex-Specific Differences in Alzheimers DiseaseR01AG060393 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SIROTA, MARINA · 2018 to 2022
$4.1M
Drug Repositioning for ApoE4-Mediated Alzheimer's DiseaseF31AG058439 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI TAUBES, ALICE LORRAINE · 2017 to 2017
$36k
NIA NIH HHS F31 AG058439NIA NIH HHS R01 AG057683NIA NIH HHS R01 AG060393NIGMS NIH HHS T32 GM008568
6 · The paper itself

Abstract

Computational drug repurposing has the ability to remarkably reduce drug development time and cost in an era where these factors are prohibitively high. Several examples of successful repurposed drugs exist in fields such as oncology, diabetes, leprosy, inflammatory bowel disease, among others, however computational drug repurposing in neurodegenerative disease has presented several unique challenges stemming from the lack of validation methods and difficulty in studying heterogenous diseases of aging. Here, we examine existing approaches to computational drug repurposing, including molecular, clinical, and biophysical methods, and propose data sources and methods to advance computational drug repurposing in neurodegenerative disease using Alzheimer's disease as an example.

Indexed as

AnimalsArtificial IntelligenceDrug RepositioningHumansNeurodegenerative DiseasesAlzheimer’s diseaseartificial intelligenceEHREMRmachine learningtranscriptomic analysis

Identifiers

PMID31326236
PMCPMC6771436
OpenAlexW2957470019

What OpenQuestion holds

Textmetadata
LicenceTDM
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.