Formulation And Evaluation Of Medicated Soft Lozenges Of Montelukast Sodium
Bibliographic record
Abstract
Lozenges are solid dosage forms that include one or more medications that are supposed to dissolve or disintegrate slowly in the mouth, or medicated candies that dissolve slowly in the mouth to lubricate and soothe sensitive throat tissue. The objective of the present study was formulation and evaluation of Medicated Soft Lozenges of Montelukast sodium by using PEG 1500 as a lozenges base while Dextrose as a sweetener. The drug excipients interaction study was done by FTIR, the compatibility of Montelukast sodium with PEG 1500 and Dextrose the studies of FTIR showed that all above characteristic peaks of Montelukast sodium were observed near about their respective values so it has been concluded that there is no incompatibility between excipients and pure drug. Formulations were prepared by melting and moulding technique. The Medicated Soft lozenges of Montelukast sodium were evaluated for physical appearance, thickness, weight variation, hardness, friability test, drug content, disintegration time, in- vitro drug release and stability study. All prepared batches showed good in- vitro dissolution studies. The best result from lozenges batches was from F2 which gives Thickness of 5.12 mm, Weight variation of 0.24 mg, Hardness of 6.5 kg/cm-1, Friability of 0.695%, Drug content of 98.32%, Disintegration time of 30 min and In- vitro drug release of 80%. The main selection criteria for the best formulation was in-vitro drug release of the formulations equal to the in-vitro drug release of the pure drug which is not less than 70%, which complies with the IP standards and hardness of the formulation batches. Hence it can be concluded that Medicated Soft Lozenges of Montelukast sodium can be successfully formulated by melting and mould technique
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".