Stability Indicating HPLC Method Development for a Marketed Retinol Acetate
Bibliographic record
Abstract
A rapid, sensitive, and accurate stability indicating high performance liquid chromatography for the determination of retinol acetate from the marketed sample was developed. Retinol acetate is a vitamin A acetate, useful in normal eye vision, also acts as a supportive anticancer, which works by binding to glycocalyx of colon slowing or stopping the growth of cancer cells. The chromatographic separation was performed on a HPLC system consisted of Plus intelligent LC pump® PU-2080 from Agilent, Germany equipped with a Agilent®UV-2075 Intelligent UV-Visible detector, an injector Rheodyne®7725 (Rheodyne, Cotati, CA, USA), along with Agilent chromapass chromatography data system software (Version 1.8.6.1). Column Purospher Star 5μm Agilent® RP C18 XDB (4.6 mm × 150 mm) using a sonicated, degassed mobile phase containing solvent A: acetonitrile and solvent B: methanol in ratio (89:11v/v) having pH 3.5 with a flow rate of1 mL/min. The elution was detected by a uv-visible detector at 360 nm. The total chromatographic runtime is 20.0 min with a retention time for sample BASF stabilized sample and standard Sigma Aldrirch internal standard was of 8.05 and 8.2 min, respectively. The method was validated over a dynamic linear range of 10-50µg/mL for retinol acetate with a correlation coefficient (r2) 0.999. The forced degradation study also revealed the susceptibility (sensitivity) of a drug towards heat, acid, base, hydrogen peroxide, light and photolytic degradation. This indicated photosensitivity and temperature sensitivity of the drug substance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".