Eslicarbazepine acetate for the treatment of focal epilepsy: an update on its proposed mechanisms of action
Bibliographic record
Abstract
Eslicarbazepine acetate (ESL) is a once daily antiepileptic drug (AED) approved by the European Medicines Agency (EMA), the Food and Drug Administration (FDA) and Health Canada as an adjunctive therapy in adults with partial-onset seizures (POS). In humans and in relevant animal laboratory species, ESL undergoes extensive first pass hydrolysis to its major active metabolite eslicarbazepine that represents ∼95% of circulating active moieties. ESL and eslicarbazepine showed anticonvulsant activity in animal models. ESL may not only suppress seizure activity but may also inhibit the generation of a hyperexcitable network. Data reviewed here suggest that ESL and eslicarbazepine demonstrated the following in animal models: (1) the selectivity of interaction with the inactive state of the voltage-gated sodium channel (VGSC), (2) reduction in VGSC availability through enhancement of slow inactivation, instead of alteration of fast inactivation of VGSC, (3) the failure to cause a paradoxical upregulation of persistent Na(+) current (I NaP), and (4) the reduction in firing frequencies of excitatory neurons in dissociated hippocampal cells from patients with epilepsy who were pharmacoresistant to carbamazepine (CBZ). In addition, eslicarbazepine effectively inhibited high- and low-affinity hCaV3.2 inward currents with greater affinity than CBZ. These preclinical findings may suggest the potential for antiepileptogenic effects; furthermore, the lack of effect upon KV7.2 outward currents may translate into a reduced potential for eslicarbazepine to facilitate repetitive firing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".