Nonclinical evaluation of abuse liability of the dual orexin receptor antagonist lemborexant
Bibliographic record
Abstract
Lemborexant is a dual orexin receptor antagonist (DORA) approved in multiple countries including the United States, Japan, Canada and Australia for the treatment of adults with insomnia. As required for marketing approval of new compounds with central nervous system activity with sedating effects, the abuse potential of lemborexant was assessed in accordance with regulatory guidelines, which included three nonclinical studies. These assessments comprised physical dependence and drug discrimination studies in rats and a self-administration study in rhesus monkeys. There was no evidence of withdrawal signs following abrupt drug discontinuation, indicating that lemborexant does not induce physical dependence. In the drug discrimination study, lemborexant at doses up to 1000 mg/kg administered orally did not cross-generalize to the zolpidem training stimulus, although another DORA included in the same experiment, suvorexant, showed partial generalization with zolpidem. In rhesus monkeys, lemborexant treatment did not induce any gross behavioral changes, and there was no increase in self-administration rates compared with control, indicative of a lack of reinforcing effects of lemborexant. Collectively, these nonclinical studies support the position that lemborexant, which has been placed in Schedule IV by the United States Drug Enforcement Administration, has a low risk of abuse in humans.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".