Lung muscarinic receptor occupancy by tiotropium: translational PET studies in non-human primates and humans
Bibliographic record
Abstract
Abstract BackgroundThe aim of the present translational PET study was to estimate occupancy of tiotropium at muscarinic acetylcholine receptors (mAChR) in the lungs in vivo. The relationship between the tiotropium exposure and receptor occupancy (RO) in the lung was assessed in non-human primates (NHPs) after intravenous injection of tiotropium doses at a broad dose interval (0.1-1mg/kg). The feasibility of measuring mAChR occupancy in the human lung was then confirmed in seven healthy human subjects after inhalation of a single therapeutic dose of tiotropium (18mg). PET examinations were performed using radioligand [11C]VC-002. Occupancy in lungs was estimated using Lassen plot analysis of parametric images showing total radioligand binding (total distribution volume, VT).ResultsThere was an evident effect of tiotropium on [11C]VC-002 binding to mAChRs in lungs in both NHPs and humans. In NHPs, the occupancy was 11 to 78%, increasing in a dose dependent manner. The Lassen-plot based estimate of non-displaceable binding in NHPs was about 10% of the VT. In humans, occupancy was 6-65%, and non-displaceable binding (VND) was about 20% of total binding, VT at baseline. ConclusionsThe results demonstrated that [11C]VC-002 binds specifically to mAChRs in the lungs such that it allows for the detection and quantification of lung muscarinic receptor occupancy following administration of an intravenously administered or inhaled muscarinic antagonist drugs. The methodology has potential for dose finding and comparison of drug formulations in future applied studies. Clinical Trial Registration: ClinicalTrials.gov identifier: NCT03097380, registered: 31 March 2017, url: https://clinicaltrials.gov/ct2/show/NCT03097380
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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 | 0.001 |
| 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 | 0.001 |
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".