Evidence map›Paper›PMID 28303498›Full record

ArticleNeurochemical research2017

Validation of a Preclinical Drug Screening Platform for Pharmacoresistant Epilepsy.

Melissa L Barker-Haliski, Kristina Johnson, Peggy Billingsley, Jennifer Huff, Laura J Handy, Rizvana Khaleel, Zhenmei Lu, Matthew J Mau, Timothy H Pruess, Carlos Rueda and 6 more

Abstract readValidation Study
In one paragraph

Article in Neurochemical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. ENX-101, a GABAEpilepsia · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

16 authors.

Melissa L Barker-HaliskiDepartment of Pharmacy, University of Washington, Seattle, WA, 98195, USA. mhaliski@uw.edu.
Kristina JohnsonAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Peggy BillingsleyAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Jennifer HuffAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Laura J HandyAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Rizvana KhaleelAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Zhenmei LuAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Matthew J MauAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Timothy H PruessAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Carlos RuedaAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Gerald SaundersAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Tristan K UnderwoodAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Fabiola VanegasAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Misty D SmithAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Peter J WestAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.
Karen S WilcoxAnticonvulsant Drug Development Program, University of Utah, Salt Lake City, UT, 84112, USA.

Funding

NINDS NIH HHS HHSN271201100029C
6 · The paper itself

Abstract

The successful identification of promising investigational therapies for the treatment of epilepsy can be credited to the use of numerous animal models of seizure and epilepsy for over 80 years. In this time, the maximal electroshock test in mice and rats, the subcutaneous pentylenetetrazol test in mice and rats, and more recently the 6 Hz assay in mice, have been utilized as primary models of electrically or chemically-evoked seizures in neurologically intact rodents. In addition, rodent kindling models, in which chronic network hyperexcitability has developed, have been used to identify new agents. It is clear that this traditional screening approach has greatly expanded the number of marketed drugs available to manage the symptomatic seizures associated with epilepsy. In spite of the numerous antiseizure drugs (ASDs) on the market today, the fact remains that nearly 30% of patients are resistant to these currently available medications. To address this unmet medical need, the National Institute of Neurological Disorders and Stroke (NINDS) Epilepsy Therapy Screening Program (ETSP) revised its approach to the early evaluation of investigational agents for the treatment of epilepsy in 2015 to include a focus on preclinical approaches to model pharmacoresistant seizures. This present report highlights the in vivo and in vitro findings associated with the initial pharmacological validation of this testing approach using a number of mechanistically diverse, commercially available antiseizure drugs, as well as several probe compounds that are of potential mechanistic interest to the clinical management of epilepsy.

Indexed as

AnimalsAnticonvulsantsDrug Evaluation, PreclinicalDrug Resistant EpilepsyElectroshockKainic AcidKindling, NeurologicMaleMiceOrgan Culture TechniquesRatsRats, Sprague-DawleyAnticonvulsantsKainic Acid6 Hz testAnimal modelsAntiseizure drugsCorneal kindlingM-CPPN6-cyclopentyladenosineValproic acid

Identifiers

PMID28303498
PMCPMC7895462

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.