Enantiomeric separations of illicit drugs and controlled substances using cyclofructan‐based (LARIHC) and cyclobond I 2000 RSP HPLC chiral stationary phases
Bibliographic record
Abstract
Recently a novel class of chiral stationary phases (CSPs) based on cyclofructan (CF) has been developed. Cyclofructans are cyclic oligosaccharides that possess a crown ether core and pendent fructofuranose moieties. Herein, we evaluate the applicability of these novel CSPs for the enantiomeric separation of chiral illicit drugs and controlled substances directly without any derivatization. A set of 20 racemic compounds were used to evaluate these columns including 8 primary amines, 5 secondary amines, and 7 tertiary amines. Of the new cyclofructan-based LARIHC columns, 14 enantiomeric separations were obtained including 7 baseline and 7 partial separations. The LARIHC CF6-P column proved to be the most useful in separating illicit drugs and controlled substances accounting for 11 of the 14 optimized separations. The polar organic mode containing small amounts of methanol in acetonitrile was the most useful solvent system for the LARIHC CF6-P CSP. Furthermore, the LARIHC CF7-DMP CSP proved to be valuable for the separation of the tested chiral drugs resulting in four of the optimized enantiomeric separations, whereas the CF6-RN did not yield any optimum separations. The broad selectivity of the LARIHC CF7-DMP CSP is evident as it separated primary, secondary and tertiary amine containing chiral drugs. The compounds that were partially or un-separated using the cyclofructan based columns were screened with a Cyclobond I 2000 RSP column. This CSP provided three baseline and six partial separations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".