Evidence map›Paper›PMID 40768367›Full record

ArticleEpilepsia2025

PAC-FOS: A novel translational concordance framework identifies preclinical seizure models with highest predictive validity for clinical focal onset seizures.

Lyndsey L Anderson, Kristopher M Kahlig, Melissa L Barker-Haliski, Lillian G Matthews, Hamish D Toop, Brian Hannigan, Jacqueline French, H Steve White, Marcio Souza, Steven Petrou

Abstract read
In one paragraph

Article in Epilepsia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Lyndsey L AndersonPraxis Precision Medicines, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-0037-0891
Kristopher M KahligPraxis Precision Medicines, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-9294-5276
Melissa L Barker-HaliskiDepartment of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington, USA.ORCID https://orcid.org/0000-0002-8175-0553
Lillian G MatthewsPraxis Precision Medicines, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-9781-5032
Hamish D ToopPraxis Precision Medicines, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0003-4637-4764
Brian HanniganPraxis Precision Medicines, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0008-1613-8406
Jacqueline FrenchDepartment of Neurology and Comprehensive Epilepsy Center, New York University Grossman School of Medicine, New York, New York, USA.ORCID https://orcid.org/0000-0003-2242-8027
H Steve WhiteDepartment of Pharmacy, Center for Epilepsy Drug Discovery, School of Pharmacy, University of Washington, Seattle, Washington, USA.ORCID https://orcid.org/0000-0003-4550-4408
Marcio SouzaPraxis Precision Medicines, Boston, Massachusetts, USA.ORCID https://orcid.org/0009-0004-6392-5104
Steven PetrouPraxis Precision Medicines, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-4960-6375

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCentral to the development of novel antiseizure medications (ASMs) is testing of antiseizure activity in preclinical models. Although various well-established models exist, their predictive validity across the spectrum of clinical epilepsies has been less clear. We sought to establish the translational concordance of commonly used preclinical models to define models with the highest predictive clinical validity for focal onset seizures (FOS).

methodsThe Praxis Analysis of Concordance (PAC) framework was implemented to assess the translational concordance between preclinical and clinical ASM response for 32 US Food and Drug Administration-approved ASMs. Preclinical ASM responses in historically used seizure models were collected. Protective indices based on reported median tolerability and median efficacy values were calculated for each ASM in each preclinical model. A weighted scale representing relative antiseizure effect was used to grade preclinical ASM response for each seizure model. Data depth was further scored based on the number of evaluated ASMs with publicly available data. Established reports of clinical ASM use in patients with FOS were similarly evaluated, and a weighted scale representing prescribing patterns and perceived efficacy was used to grade clinical ASM response. To assess the predictive validity of preclinical models, a unified translational scoring matrix was developed to assign a concordance score spanning the spectrum from complete discordance (-1) to complete concordance (1) between preclinical and clinical ASM responses. Scores were summed and normalized to generate a global translational concordance score.

resultsThe preclinical models with the highest translational concordance and greatest data depth for FOS were rodent maximal electroshock seizure (MES), mouse audiogenic seizure, mouse 6 Hz (32 mA), and rat amygdala kindling. SIGNIFICANCE: The PAC-FOS framework highlights mouse MES, mouse audiogenic, and mouse 6 Hz (32 mA) as three acute seizure models consistently demonstrating high predictive validity for FOS. We provide a pragmatic decision tree approach to support efficient resource utilization for novel ASM discovery for FOS.

Indexed as

AnticonvulsantsDisease Models, AnimalEpilepsies, PartialSeizuresTranslational Research, BiomedicalAnimalsDrug Evaluation, PreclinicalHumansMiceRatsReproducibility of ResultsAnticonvulsantsepilepsyfocal seizurespreclinical modelspredictive validitytranslational concordance

Identifiers

PMID40768367
PMCPMC12779320

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Registered trials

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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.