A Micro-Configured Multiparticulate Reconstitutable Suspension Powder of Fixed Dose Rifampicin and Pyrazinamide: Optimal Fabrication and In Vitro Quality Evaluation
Bibliographic record
Abstract
The scarcity of age-appropriate pharmaceutical formulations is one of the major challenges impeding successful management of tuberculosis (TB) prevalence in minors. To this end, we designed and assessed the quality of a multiparticulate reconstitutable suspension powder containing fixed dose rifampicin and pyrazinamide (150 mg/300 mg per 5 mL) which was prepared employing solid−liquid direct dispersion coupled with timed dehydration, and mechanical pulverization. The optimized formulation had a high production yield (96.000 ± 3.270%), displayed noteworthy powder flow quality (9.670 ± 1.150°), upon reconstitution the suspension flow property was non-Newtonian and was easily redispersible with gentle manual agitation (1.720 ± 0.011 strokes/second). Effective drug loading was attained for both pyrazinamide (97.230 ± 2.570%w/w) and rifampicin (97.610 ± 0.020%w/w) and drug release followed a zero-order kinetic model (R2 = 0.990) for both drugs. Microscopic examinations confirmed drug encapsulation efficiency and showed that the particulates were micro-dimensional in nature (n < 700.000 µm). The formulation was physicochemically stable with no chemically irreversible drug-excipient interactions based on the results of characterization experiments performed. Findings from organoleptic evaluations generated an overall rating of 4.000 ± 0.000 for its attractive appearance and colour 5.000 ± 0.000 confirming its excellent taste and extremely pleasant smell. Preliminary cytotoxicity studies showed a cell viability above 70.000% which indicates that the FDC formulation was biocompatible. The optimized formulation was environmentally stable either as a dry powder or reconstituted suspension. Accordingly, a stable and palatable FDC antimycobacterial reconstitutable oral suspension powder, intended for flexible dosing in children and adolescents, was optimally fabricated.
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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 | 0.004 | 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 | 0.001 |
| 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".