PREPARATION, CHARACTERIZATION, AND OPTIMIZATION OF MEBENDAZOLE SPHERICAL AGGLOMERATES USING MODIFIED EVAPORATIVE PRECIPITATION IN AQUEOUS SOLUTION (EPAS)
Bibliographic record
Abstract
Objective: Mebendazole is a popular benzimidazole class anthelmintic drug useful in the treatment of main infections of threadworms as well as other less common worm infections like whipworm, roundworm, and hookworm in adults and children over 2 y of age. It is poorly soluble in water resulting in poor absorption from the intestinal tract leading to a decrease in bioavailability. Moreover, Mebendazole has poor flowability due to the needle-shaped crystals. This work was carried out with the aim of increasing the flowability and solubility of Mebendazole. Methods: A 32 full factorial design was used to investigate the effect of the concentration of Mebendazole and the quantity of water as an external phase using evaporative precipitation into an aqueous solution. The prepared agglomerates were characterized for particle size distribution, shape, Hausner ratio, Carr’s index and % dissolved in 60 min (C60). Results: The prepared agglomerates were found to be monodispersed. They also showed a decrease in the Hausner ration and Carr’s index, indicating improved flowability. Increase in C60 indicated that the agglomerates were found to have increased water solubility. Conclusion: Scanning Electron Microscopy showed that the agglomerates were spherical in shape. Fourier Transformed Infra-Red studies showed no chemical change in the prepared spherical agglomerates. Differential Scanning Calorimetry and X-ray diffraction studies showed an increase in amorphous characteristics of prepared spherical agglomerates. This method may be used for drugs with similar characteristics as Mebendazole.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".