Evidence map›Paper›PMID 31035818›Full record

ArticleEpilepsy currents

CRAFTing a New Approach to Antiepileptic Drug Discovery.

Kyle A Lyman, Dane M Chetkovich

Open access · diamondAbstract readComment
In one paragraph

Article in Epilepsy currents. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 31% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Kyle A Lyman
Dane M Chetkovich

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Srivastava PK, van Eyll J, Godard P, Mazzuferi M, Delahaye-Duriez A, Steenwinckel JV, et al. A systems-level framework for drug discovery identifies Csf1R as an anti-epileptic drug target. Nat Commun. 2018;9(1):3561. doi:10.1038/s41467-018-06008-4. The identification of drug targets is highly challenging, particularly for diseases of the brain. To address this problem, we developed and experimentally validated a general computational framework for drug target discovery that combines gene regulatory information with causal reasoning ("Causal Reasoning Analytical Framework for Target discovery"-CRAFT). Using a systems genetics approach and starting from gene expression data from the target tissue, CRAFT provides a predictive framework for identifying cell membrane receptors with a direction-specified influence over disease-related gene expression profiles. As proof of concept, we applied CRAFT to epilepsy and predicted the tyrosine kinase receptor Csf1R as a potential therapeutic target. The predicted effect of Csf1R blockade in attenuating epilepsy seizures was validated in 3 preclinical models of epilepsy. These results highlight CRAFT as a systems-level framework for target discovery and suggest Csf1R blockade as a novel therapeutic strategy in epilepsy. The CRAFT is applicable to disease settings other than epilepsy.

Identifiers

PMID31035818
PMCPMC6610382
OpenAlexW2942563463

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.