Chiral bioanalytical methods in bioequivalence studies of intravenous vs. oral formulations of ibuprofen
Bibliographic record
Abstract
Abstract According to the Ibuprofen Product‐Specific Bioequivalence Guidance of the European Medicines Agency, achiral bioanalytical methods are considered acceptable for demonstration of bioequivalence of ibuprofen‐containing products. The aim of this investigation is to compare the bioequivalence outcomes obtained with individual R and S ibuprofen enantiomers and the sum of both enantiomers from bioequivalence studies in which new intravenous ibuprofen products were compared with oral ibuprofen products. Bioequivalence was assessed for S and R enantiomers of ibuprofen and the sum of both enantiomers, which was calculated to represent the results that would have been obtained with an achiral assay. The infusion rates of 15, 20, and 30 minutes modify the maximum concentration (Cmax) of the intravenous administrations. In contrast, the time when the maximum concentration is observed (Tmax) was insensitive to detect differences in input rate within this range of infusion times. The eutomer S‐ibuprofen is the least sensitive analyte to detect differences in input rate; therefore, the regulatory acceptance of achiral bioanalytical methods for ibuprofen bioequivalence studies is justified because the sum of both enantiomers is more discriminative than the chiral methods where only the eutomer is used for regulatory decisions.
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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 | 0.027 | 0.029 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".