Chiral LC-PDA-ORD Method for The Separation of Linagliptin Enantiomers On Coated Polysaccharide Based Amylose Tris (3, 5-Dimethylphenylcarbamate) Stationary Phases
Bibliographic record
Abstract
Chiral normal phase high performance liquid chromatographic (chiral-HPLC) was designed and verified for the separation of linagliptin enantiomers using coated polysaccharide chiral stationary phases. The stationary phase was amylose tris (3, 5-dimethylphenylcarbamate) (250x4.6mm, 5 µm), while the mobile phase was a mixture of 50:50:0.1% v/v. With a flow rate of 1 mL/min, orthophosphoric acid was mixed with hexane, isopropyl alcohol, and diethyl amine to achieve a pH of 5.2. The detection was seen at 225 nm. The optical rotatory dispersion (ORD) polarimeter was connected in series to the PDA outlet in order to determine the enantiomer conformation. The linagliptin retention times were found to be 5.454 and 8.772 minutes. Between 3.9 and 23.4 µg/ml, enantiomers were discovered to be linear, with a correlation coefficient of 0.9995. This method was validated in terms of linearity, LOD, LOQ, precision, accuracy, and robustness studies in accordance with ICH requirements. Novelty: The proposed analytical method for the chiral analysis of linagliptin can be used by pharmaceutical industries quality control departments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".