High-throughput Caco-2 cell permeability screening by cassette dosing and sample pooling approaches using direct injection/on-line guard cartridge extraction/tandem mass spectrometry
Bibliographic record
Abstract
A method for high-throughput Caco-2 permeability screening of drug candidates has been developed using thirteen generic drugs as test compounds. The high throughput was achieved by either a sample pooling or a cassette dosing approach, along with the use of a rapid, simple and sensitive direct injection/on-line guard cartridge extraction/tandem mass spectrometric assay that was also developed in this study. It was of concern that possible drug-drug interactions (e.g., inhibition of P-glycoprotein-mediated transport of a drug by another, and/or competition of the drugs for transport pathways), when the cassette dosing regimen was implemented, may give rise to inconsistent results compared with those attained by a traditional single-drug dosing approach. However, the apparent permeability coefficients of the test drugs across Caco-2 monolayers measured by the sample pooling or cassette dosing (up to five drugs co-administered in this study) strategy were in good conformity with the data obtained by single-drug dosing followed by discrete sample analysis.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".