A membrane vesicle-based assay to enable prediction of human biliary excretion
Bibliographic record
Abstract
1. Prediction of biliary excretion is a challenge due to the lack of in vitro assays. Our laboratory previously demonstrated a highly significant correlation between in vitro IC50 values against mrp2 using rat canalicular liver plasma membrane vesicles and in vivo biliary excretion (Colombo et al., 2012). This study explores the possibility of predicting in vivo biliary excretion in human using membrane vesicles prepared from MDCKII cells transfected with human ABCC2. 2. In vitro MRP2 activity was determined by measuring the ATP-dependent uptake of 5(6)-carboxy-2',7'-dichlorofluorescein (CDCF) in inside-out membrane vesicles isolated from MDCK-ABCC2 cells. CDCF uptake was time- and concentration-dependent (Km of 4.0 ± 1.2 µM and a Vmax of 7.8 ± 0.9 pmol/mg/min) and inhibited by benzbromarone and MK-571 with IC50 values of 1.2 and 7.6 µM, respectively. 3. A significant linear correlation (r(2 )= 0.790) between the in vitro IC50 values from the described MRP2 assay and in vivo biliary excretion in humans was observed using 11 well-documented drugs covering low to high biliary excretions. 4. This study demonstrates, for the first time, that inhibition of CDCF uptake in MDCKII-ABCC2 vesicles not only provides a screening assay to assess MRP2 drug-drug interaction potential, but is also predictive of human MRP2-mediated biliary excretion.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".