Novel Chiral HPLC Method for Accurate Identification and Quantification of R&S Enantiomers in Ropivacaine on Immobilized Chiral Stationary Phase: Development and Validation
Bibliographic record
Abstract
Purpose: Ropivacaine is a widely used local anesthetic for managing postoperative pain, particularly in procedures such as caesarean sections. While historically used as a racemate, its structural similarity to mepivacaine and bupivacaine within the pipecoloxylidide group is notable. Both enantiomers of ropivacaine exhibit similar nerve-blocking properties, but the R enantiomer is associated with increased cardiotoxicity compared to the S-Ropivacaine, like bupivacaine. This study aimed to develop and validate precise and rapid chiral chromatographic techniques for quantifying potential (R&S enantiomers). Methods: We used normal phase chromatography with a (3,5-dimethylphenylcarbamate) immobilized- type polysaccharide stationary phase to quantify R&S enantiomers. The method followed ICH Q2(R1) guidelines, employing CHIRAL ART Amylose-SA for determining S-Ropivacaine enantiomeric purity in pharmaceutical drugs. The validation included accuracy and LOQ (limit of quantification) profiles, with measurement error assessments. Linear regression of accuracy profiles post square root transformations set acceptance limits at ±10%. Results: The method accurately quantified R&S enantiomers, adhering to ICH Q2(R1) guidelines. Validation showed high accuracy and precise LOQ profiles. Measurement error assessments confirmed reliability. Linear regression of accuracy profiles stayed within ±10% acceptance limits, confirming the method's suitability for determining S-Ropivacaine enantiomeric purity. Conclusion: The developed chiral chromatographic method provides an effective means of quantifying the enantiomeric purity of S-Ropivacaine in pharmaceutical drugs. Its adherence to ICH Q2(R1) guidelines ensures reliability and accuracy in measurement. This method enables precise determination of S-Ropivacaine content, which is crucial for optimizing therapeutic outcomes while minimizing the risk of cardiotoxicity associated with the R enantiomer.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".