Development of a Novel In Vitro Model to Study Lymphatic Uptake of Drugs via Artificial Chylomicrons
Bibliographic record
Abstract
was developed to investigate the lymphatic uptake of drugs. The model was validated using cannabidiol, halofantrine, quercetin, and rifampicin. Remarkably, the uptake of these drugs closely mirrored what would transpire in vivo. Furthermore, adding peanut oil to the model system significantly increased the lymphatic uptake of rifampicin, consistent with meals containing fat stimulating lymphatic drug uptake. Conversely, the inclusion of pluronic L-81 was observed to inhibit the lymphatic uptake of rifampicin in the model. This in vitro model emerges as a valuable tool for investigating and predicting drug uptake via the lymphatic system. It marks the first phase in developing a physiologically based predictive tool that can be refined further to enhance the precision of drug interaction predictions with chylomicrons and their subsequent transport via the lymphatic system. Moreover, it can be employed to explore innovative drug formulations and excipients that either enhance or hinder lymphatic drug uptake. The insights gained from this study have significant implications for advancing drug delivery through the lymphatic system.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".