A Correlative Model to Predict In Vivo AUC for Nanosystem Drug Delivery with Release Rate-Limited Absorption
Bibliographic record
Abstract
PURPOSE: Drug release from nanosystems at the sites of either absorption or effect biophase is a major determinant of its biological action. Thus, in vitro drug release is of paramount importance in gaining insight for the systems performance in vivo. METHODS: A novel in vitro in vivo correlation, IVIVC, model denoted as double reciprocal area method was presented and applied to 19 drugs from 55 nano formulations with total 336 data, gathered from literature. RESULTS: The proposed model correlated the in vitro with in vivo parameters with overall error of 12.4 ± 3.9%. Also the trained version of the model predicted the test formulations with overall error of 15.8 ± 3.7% indicating the suitability of the approach. A theoretical justification was provided for the model considering the unified classical release laws. CONCLUSION: The model does not necessitate bolus intravenous drug data and seems to be suitable for IVIVC of drugs with release rate-limited absorption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".