NBI-921352, a first-in-class, NaV1.6 selective, sodium channel inhibitor that prevents seizures in Scn8a gain-of-function mice, and wild-type mice and rats
Bibliographic record
Abstract
NBI-921352 (formerly XEN901) is a novel sodium channel inhibitor designed to specifically target Na V 1.6 channels. Such a molecule provides a precision-medicine approach to target SCN8A -related epilepsy syndromes ( SCN8A -RES), where gain-of-function (GoF) mutations lead to excess Na V 1.6 sodium current, or other indications where Na V 1.6 mediated hyper-excitability contributes to disease (Gardella and Møller, 2019; Johannesen et al., 2019; Veeramah et al., 2012). NBI-921352 is a potent inhibitor of Na V 1.6 (IC 50 0.051 µM), with exquisite selectivity over other sodium channel isoforms (selectivity ratios of 756 X for Na V 1.1, 134 X for Na V 1.2, 276 X for Na V 1.7, and >583 Xfor Na V 1.3, Na V 1.4, and Na V 1.5). NBI-921352is a state-dependent inhibitor, preferentially inhibiting inactivatedchannels. The state dependence leads to potent stabilization of inactivation, inhibiting Na V 1.6 currents, including resurgent and persistent Na V 1.6 currents, while sparing the closed/rested channels. The isoform-selective profile of NBI-921352 led to a robust inhibition of action-potential firing in glutamatergic excitatory pyramidal neurons, while sparing fast-spiking inhibitory interneurons, where Na V 1.1 predominates. Oral administration of NBI-921352 prevented electrically induced seizures in a Scn8a GoF mouse,as well as in wild-type mouse and ratseizure models. NBI-921352 was effective in preventing seizures at lower brain and plasma concentrations than commonly prescribed sodium channel inhibitor anti-seizure medicines (ASMs) carbamazepine, phenytoin, and lacosamide. NBI-921352 waswell tolerated at higher multiples of the effective plasma and brain concentrations than those ASMs. NBI-921352 is entering phase II proof-of-concept trials for the treatment of SCN8A- developmental epileptic encephalopathy ( SCN8A -DEE) and adult focal-onset seizures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".