Monoamine Oxidase-A Occupancy by Moclobemide and Phenelzine: Implications for the Development of Monoamine Oxidase Inhibitors
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Monoamine oxidase inhibitors (MAOIs) are being developed for major depressive disorder, Alzheimer's, and Parkinson's Disease. Newer MAOIs have minimal sensitivity to tyramine, but a key limitation for optimizing their development is that standards for in vivo monoamine oxidase-A (MAO-A) occupancy in humans are not well established. The objectives were to determine the dose-occupancy relationship of moclobemide and the occupancy of phenelzine at typical clinical dosing. METHODS: Major depressive episode (MDE) subjects underwent [(11)C]harmine positron emission tomography scanning prior to and following 6 weeks of treatment with moclobemide or phenelzine. RESULTS: Mean brain MAO-A occupancies were 74.23±8.32% for moclobemide at 300-600 mg daily (n = 11), 83.75±5.52% for moclobemide at 900-1200 mg daily (n = 9), and 86.82±6.89% for phenelzine at 45-60 mg daily (n = 4). The regional dose-occupancy relationship of moclobemide fit a hyperbolic function [F(x) = a(x/[b + x]); F(1,18) = 5.57 to 13.32, p = 0.002 to 0.03, mean 'a': 88.62±2.38%, mean 'b': 69.88±4.36 mg]. Multivariate analyses of variance showed significantly greater occupancy of phenelzine (45-60mg) and higher-dose moclobemide (900-1200 mg) compared to lower-dose moclobemide [300-600 mg; F(7,16) = 3.94, p = 0.01]. CONCLUSIONS: These findings suggest that for first-line MDE treatment, daily moclobemide doses of 300-600mg correspond to a MAO-A occupancy of 74%, whereas for treatment-resistant MDE, either phenelzine or higher doses of moclobemide correspond to a MAO-A occupancy of at least 84%. Therefore, novel MAO inhibitor development should aim for similar thresholds. The findings provide a rationale in treatment algorithm design to raise moclobemide doses to inhibit more MAO-A sites, but suggest switching from high-dose moclobemide to phenelzine is best justified by binding to additional targets.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it