Exploring occupancy of the histamine H<sub>3</sub> receptor by pitolisant in humans using PET
Bibliographic record
Abstract
Background and Purpose BF2.649 (pitolisant, Wakix®) is a novel histamine H3 receptor inverse agonist/antagonist recently approved for the treatment of narcolepsy disorder. The objective of the study was to investigate in vivo occupancy of H3 receptors by BF2.649 using PET brain imaging with the H3 receptor antagonist radioligand [11C]GSK189254. Experimental Approach Six healthy adult participants were scanned with [11C]GSK189254. Participants underwent a total of two PET scans on separate days, 3 h after oral administration of placebo or after pitolisant hydrochloride (40 mg). [11C]GSK189254 regional total distribution volumes were estimated in nine brain regions of interest with the two tissue‐compartment model with arterial input function using a common VND across the regions. Brain receptor occupancies were calculated with the Lassen plot. Key Results Pitolisant, at the dose administered, provided high (84 ± 7%; mean ± SD) occupancy of H3 receptors. The drug was well‐tolerated, and participants experienced few adverse events. Conclusion and Implications The administration of pitolisant (40 mg) produces a high occupancy of H3 receptors and may be a new tool for the treatment of a variety of CNS disorders that are associated with mechanisms involving H3 receptors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".