Ketoconazole-Associated Preferential Increase in Dopamine D2 Receptor Occupancy in Striatum Compared to Pituitary In Vivo
Bibliographic record
Abstract
Membrane transporters such as P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) are efflux pumps that remove drugs from the brain back to the peripheral blood compartment, serving as a functional component of the blood-brain barrier (BBB). We report here that coadministration of the P-gp and BCRP inhibitor ketoconazole with risperidone may preferentially increase D2 receptor occupancy in the striatum compared to pituitary. Four male patients with schizophrenia or schizoaffective disorder who had received at least 4 prior injections of the long-acting risperidone at a stable dose of 25 to 50 mg participated in this positron emission tomography study. Multiple-dose ketoconazole coadministration reduced the P-gp activity as shown by fexofenadine oral challenge. Importantly, we found a strong statistical trend in this sample of 4 subjects who consistently showed a decrease in striatal fluorine 18 (F)-fallypride binding (an indication of increased D2 receptor occupancy) after ketoconazole coadministration (P = 0.057), whereas the pituitary (a region that lies outside the BBB) F-fallypride binding did not change (P = 0.99). These observations warrant further research with selective drug transporter inhibitors. We suggest that in neuroimaging studies, the pituitary drug occupancy can serve as a useful new "positive control" to evaluate whether drug occupancy is preferentially increased in brain regions that fall inside the BBB after cotreatment with P-gp and BCRP inhibitors. This is a noteworthy study design consideration regarding the future clinical testing of novel adjunct interventions aimed at modulating membrane transporter function at the BBB, with the goal of augmenting drug access into the brain compartment, particularly in treatment-resistant psychiatric illness.
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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) | 0.001 | 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".