An Eco-Friendly RP-HPLC Method Development and Validation for Quantification of Favipiravir in Bulk and Tablet Dosage Form Followed by Forced Degradation Study
Bibliographic record
Abstract
In this work, an eco-friendly simple, precise reverse phase high-performance liquid chromatography (HPLC) method has been developed and validated for Favipiravir in bulk and tablet dosage form followed by its force degradation study. The proposed method was validated to obtain official requirements including stability, accuracy, precision, linearity, robustness and selectivity as per International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Guidelines. The estimation was developed on C (18) column reversed-phase using the mobile phase composition as methanol:water (10:90 v/v). The flow rate was set as 1 ml/min, and the maximum absorption was observed at 323 nm using Shimadzu Photo Diode Array detector. The Favipiravir, drug showed a precise and good linearity at the concentration ranges of 10-50 μg/mL. The Revearse Phase High Perforance Liquid Chromatography assay showed the highest purity ranging from 99.90 to 100.02% for Favipiravir, tablet dosage form, and 100.15% was the mean percentage purity. The percent recovery was found within the acceptance limit of (98.6-100.0%). Intra- and inter-day precision studies of the method were less than the maximum allowable limit percentage of relative standard deviation ≤ 2.0. The Favipiravir retention time was found to be 5.00 min. To examine the stability of the drug, various forced degradation studies were conducted on Favipiravir Active Pharmaceutical Ingredient. The developed method was validated according to the ICH guidelines. A very quick, cost-effective, precise and accurate HPLC method for the determination of Favipiravir has been developed and validated in compliance with ICH guidance Q2.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".