A high throughput<i>in vitro</i>mrp2 assay to predict<i>in vivo</i>biliary excretion
Bibliographic record
Abstract
Prediction of biliary excretion is a challenge for drug discovery scientists due to the lack of in vitro assays. This study explores the possibility of establishing a simple assay to predict in vivo biliary excretion via the mrp2 transport system. In vitro mrp2 activity was determined by measuring the ATP-dependent uptake of 5(6)-carboxy-2',7'-dichlorofluorescein (CDCF) in canalicular plasma membrane vesicles (cLPM) from rat livers. The CDCF uptake was time- and concentration-dependent (K(m) of 2.2 ± 0.3 µM and V(max) of 115 ± 26 pmol/mg/min) and strongly inhibited by the mrp2 inhibitors, benzbromarone, MK-571, and cyclosporine A, with IC(50) values ≤ 1.1 µM. Low inhibition of CDCF uptake by taurocholate (BSEP inhibitor; 57 µM) and digoxin (P-gp inhibitor; 101 µM) demonstrated assay specificity towards mrp2. A highly significant correlation (r(2) = 0.959) between the in vitro IC(50) values from the described mrp2 assay and in vivo biliary excretion in rats was observed using 10 literature compounds. This study demonstrated, for the first time, that a high throughput assay could be established with the capability of predicting biliary excretion in the rat using CDCF as a substrate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".