IVIVC Assessment of Two Mouse Brain Endothelial Cell Models for Drug Screening
Bibliographic record
Abstract
Since most preclinical drug permeability assays across the blood-brain barrier (BBB) are still evaluated in rodents, we compared an in vitro mouse primary endothelial cell model to the mouse b.End3 and the acellular parallel artificial membrane permeability assay (PAMPA) models for drug screening purposes. The mRNA expression of key feature membrane proteins of primary and bEnd.3 mouse brain endothelial cells were compared. Transwell® monolayer models were further characterized in terms of tightness and integrity. The in vitro in vivo correlation (IVIVC) was obtained by the correlation of the in vitro permeability data with log BB values obtained in mice for seven drugs. The mouse primary model showed higher monolayer integrity and levels of mRNA expression of BBB tight junction (TJ) proteins and membrane transporters (MBRT), especially for the efflux transporter Pgp. The IVIVC and drug ranking underlined the superiority of the primary model (r2 = 0.765) when compared to the PAMPA-BBB (r2 = 0.391) and bEnd.3 cell line (r2 = 0.019) models. The primary monolayer mouse model came out as a simple and reliable candidate for the prediction of drug permeability across the BBB. This model encompasses a rapid set-up, a fair reproduction of BBB tissue characteristics, and an accurate drug screening.
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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 | 0.000 |
| 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".