Interaction of drugs of abuse and maintenance treatments with human P-glycoprotein (ABCB1) and breast cancer resistance protein (ABCG2)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drug interaction with P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) may influence its tissue disposition including blood-brain barrier transport and result in potent drug-drug interactions. The limited data obtained using in-vitro models indicate that methadone, buprenorphine, and cannabinoids may interact with human P-gp; but almost nothing is known about drugs of abuse and BCRP. We used in vitro P-gp and BCRP inhibition flow cytometric assays with hMDR1- and hBCRP-transfected HEK293 cells to test 14 compounds or metabolites frequently involved in addiction, including buprenorphine, norbuprenorphine, methadone, ibogaine, cocaine, cocaethylene, amphetamine, N-methyl-3,4-methylenedioxyamphetamine, 3,4-methylenedioxyamphetamine, nicotine, ketamine, Delta9-tetrahydrocannabinol (THC), naloxone, and morphine. Drugs that in vitro inhibited P-gp or BCRP were tested in hMDR1- and hBCRP-MDCKII bidirectional transport studies. Human P-gp was significantly inhibited in a concentration-dependent manner by norbuprenorphine>buprenorphine>methadone>ibogaine and THC. Similarly, BCRP was inhibited by buprenorphine>norbuprenorphine>ibogaine and THC. None of the other tested compounds inhibited either transporter, even at high concentration (100 microm). Norbuprenorphine (transport efflux ratio approoximately 11) and methadone (transport efflux ratio approoximately 1.9) transport was P-gp-mediated; however, with no significant stereo-selectivity regarding methadone enantiomers. BCRP did not transport any of the tested compounds. However, the clinical significance of the interaction of norbuprenorphine with P-gp remains to be evaluated.
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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