PAC: A novel translational concordance framework identifies preclinical seizure models with highest predictive validity for clinical focal onset seizures
ABSTRACT/SUMMARYO_ST_ABSObjectiveC_ST_ABSCentral to the development of novel antiseizure medications (ASMs) is testing of anticonvulsant activity in preclinical models. While 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 FDA-approved ASMs. Preclinical ASM responses in historically used seizure models were collected. Protective indices based on reported TD50 and ED50 values were calculated for each ASM in each preclinical model. A weighted scale representing relative anticonvulsant 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 used to grade clinical ASM response for each indication. To assess the predictive validity of preclinical models, a unified translational scoring matrix was developed to assign a concordance score spanning the spectrum of 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 (32mA) and rat amygdala kindling. SignificanceThe PAC-FOS framework highlights mouse MES, mouse audiogenic and mouse 6 Hz (32mA) 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. KEY POINT BOXUsing a newly developed translational scoring matrix, we provide novel insights into the clinical validity of common preclinical seizure models for FOS. O_LIThe PAC-FOS Framework identifies mouse MES, audiogenic and 6-Hz 32 mA as three acute models with greatest predictive validity and versatility for FOS drug discovery. C_LIO_LIWe present a pragmatic approach and decision tree to support efficient use of drug discovery resources and in consideration of the 3Rs of animal ethics. C_LIO_LIThe work presented would allow for faster and more effective screening of ASMs, while potentially reducing future patient exposures to likely ineffective drugs. C_LI