Comparative study of Two In Vitro Methods for Assessing Drug Absorption: Sartorius SM 16750 Apparatus Versus Everted Gut Sac
Bibliographic record
Abstract
PURPOSE: Oral drug administration remains the most common and most convenient way used in clinical therapy. The availability of a simple, rapid, economic and reproducible in vitro method to assess the rate, extent and mechanism of intestinal drug absorption is a very helpful tool. The purpose of this study was to compare the performance of Sartorius SM 16750 Absorption Simulator apparatus to Everted Gut Sac (EGS) technique in terms of predicting drug permeability. METHODS: Permeation studies across these two in vitro models were performed with six drugs selected across the Biopharmaceutics Classification System (BCS) categories: tramadol (class I of BCS), doxycycline (class I of BCS), diclofenac (class II of BCS), clopidogrel (class II of BCS), metformin (class III of BCS) and chlorothiazide (class IV of BCS). RESULTS: Apparent permeability coefficient (Papp) and diffusion profiles obtained with EGS and Sartorius SM 16750 apparatus were similar for diclofenac and metformin, whereas, we noticed significant differences (p ≤ 0.05), for tramadol, doxycycline, clopidogrel and chlorothiazide. CONCLUSION: Compared to Everted Gut Sac model, Sartorius SM 16750 absorption simulator apparatus seems to have limited application for the assessment of intestinal drug absorption since it does not take into consideration the involvement of others processes than the passive transcellular pathway as mechanism of drug absorption.
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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 | 0.003 | 0.003 |
| 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 | 0.001 |
| 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".