Prediction of the disposition of a P‐gp substrate in wild‐type and knockout mice tissues: Development of a physiologically based pharmacokinetic (PBPK) model and its global sensitivity analysis
Bibliographic record
Abstract
Abstract In order to improve understanding and prediction of drug disposition prior to in vivo experiments, we aimed to develop a PBPK model that accounts for the involvement of P‐glycoprotein activity and expression in mouse brain, liver, kidney and heart tissues. Model parameters of P‐gp activity and drug diffusion were mainly extrapolated from in vitro data. Model simulations, compared with tissue concentration of 3H‐domperidone intravenously administered toWT and KO mice, suggest the involvement of additional membrane transporters in heart and brain tissues. The global sensitivity analysis showed that the variability of model predictions is related to the variability of the unbound fraction to plasma protein, whereas the uncertainty of the model predictions is associated with the uncertainty of the parameters related to P‐gp genetic expression, and to the activity of additional transporters in heart and brain tissues. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".