BCS (Biopharmaceutical information system) and in vitro/in vivo correlation of bioequivalent studies
Bibliographic record
Abstract
Biopharmaceutical classification system is a scientific framework for classifying a drug substance in to the groups based on its aqueous solubility and intestinal permeability. When combined with the in vitro dissolution characteristics of the drug product, then there are three major factors: solubility, intestinal permeability and dissolution rate. All these three factors correspond closely with the rate and extent of oral drug absorption from IR solid oral- dosage forms. This work presents the overview about the BCS from two major points of view, from the site of the World health organization (WHO) and U.S. Food and drug administration (FDA), while the FDA guideline for biowaiver is fully cited in Czech language. Also reflection of in vitro in vivo correlations in IR drugs development according to BCS is mentioned. Further, the thesis is analyzing the bioequivalence studies of Czech pharmaceutical company Zentiva, k. s. in context of BCS and compares the results with data obtained from the Canadian CRO Anapharm, which is a contract partner of many pharmaceutical companies being engaged in a clinical research and bioequivalence studies. Keywords: Biopharmaceutical classification system, solubility, permeability, dissolution, in vivo/in vitro correlations, Caco-2 cells, bioequivalence, IR drug...
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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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".