Enhancement of the intestinal absorption of bortezomib by self-nanoemulsifying drug delivery system
Bibliographic record
Abstract
Purpose: Intestinal drug absorption is one of the main factors that govern the fraction of oral dose absorbed (Fa) of drugs. It is reported that oral absorption of bortezomib (BTZ) can be restricted by its low intestinal permeability. In this study, we aimed to evaluate the impact of self-nanoemulsifying drug delivery systems (SNEDDS) on the intestinal absorption and Fa of BTZ.Methods: Intestinal permeability studies were conducted using in situ single-pass intestinal perfusion (SPIP) technique in rats. Human intestinal absorption (Peff (Human)) and Fa values of BTZ and BTZ-SNEDDS were predicted based on SPIP data.Results: Based on the obtained data, Peff (rat) values of (3.36 ± 0.5) × 10−5 and (8.9 ± 3) × 10−5 cm/s (mean ± SEM) were calculated for BTZ and BTZ-SNEDDS, respectively. Meanwhile, Peff (human) values of (7 × 10−5) and (68 × 10−5) cm/sec were predicted for BTZ and BTZ-SNEDDS, respectively. Besides, Fa (human) values of 72.5 and 97% were estimated for BTZ and BTZ-SNEDDS, respectively.Conclusions: According to the obtained data, it is concluded that SNEDDS can be considered as a promising drug delivery system to improve the intestinal absorption and Fa values of BTZ.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".