AMPA Receptor Antagonists for the Treatment of CNS Disorders: Antiepileptics and Beyond
Bibliographic record
Abstract
The α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) glutamate receptors mediate fast excitatory synaptic transmission in the central nervous system (CNS). Given the abundant expression and functional significance of these receptors, disruption of AMPA receptor-mediated activity has been implicated in the pathophysiology of a variety of CNS disorders. Although such disorders may represent putative therapeutic targets for AMPA receptor antagonists, pharmacological limitations have, historically, hampered the development of AMPA receptor antagonists and few, therefore, have reached clinical trials. One AMPA receptor antagonist which has successfully completed clinical development is the antiepileptic drug perampanel, identified from a focused research effort that used high-throughput screening procedures combined with structure-activity analyses to optimise lead compounds. Perampanel has a favourable pharmacokinetic profile and broad-spectrum anticonvulsant activity in several animal models, as well as consistent efficacy for the treatment of refractory partial-onset seizures in three Phase III registration studies. As a result, perampanel is the first antiepileptic drug approved in Europe, the USA, Canada, Switzerland and more than 30 other countries, to inhibit excitation of postsynaptic membranes through the selective inhibition of AMPA receptors. Here, we explore the contribution of AMPA receptors to the pathophysiology of CNS disorders, and use the discovery and development of perampanel as an example of an effective strategy to target AMPA receptors to address an unmet clinical need. Looking to the future, we also consider potential applications of AMPA receptor antagonists beyond the field of epilepsy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".