Progress report on new antiepileptic drugs: A summary of the Fourteenth Eilat Conference on New Antiepileptic Drugs and Devices (EILAT XIV). I. Drugs in preclinical and early clinical development
Bibliographic record
Abstract
The Fourteenth Eilat Conference on New Antiepileptic Drugs and Devices (EILAT XIV) took place in Madrid, Spain, on May 13-16, 2018 and was attended by 168 delegates from 28 countries. The conference provided a forum for professionals involved in basic science, clinical research, regulatory affairs, and clinical care to meet and discuss the latest advances related to discovery and development of drugs and devices aimed at improving the management of people with epilepsy. This progress report provides a summary of findings on investigational compounds for which data from preclinical or early (phase I) clinical studies were presented. The compounds reviewed include adenosine and adenosine kinase inhibitors, BIS-001 (huperzine A), 2-deoxy-d-glucose, FV-082, FV-137, JNJ-40411813, JNJ-55511118 and analogs, ketone-enhanced antiepileptic drugs, oxynytones, OV329, TAK-935 (OV935), XEN901, and XEN1101. Many innovative approaches to drug development were presented. For example, some compounds are being combined with traditional antiepileptic drugs based on evidence of synergism in seizure models, some act as inhibitors of enzymes involved in modulation of neuronal activity, and some interact in novel ways with excitatory receptors or ion channels. Some of the compounds in development target the etiology of specific epilepsy syndromes (including orphan conditions) through precision medicine, and some offer hope of producing disease-modifying effects rather than symptomatic seizure suppression. Overall, the results summarized in the report indicate that important advances are being made in the effort to develop compounds with potentially improved efficacy and safety profiles compared with existing agents.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.014 |
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".