Advances in spray drying technology for anti-tubercular formulation development: A comprehensive review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Global health is still seriously threatened by tuberculosis (TB), especially considering the increasing incidence of strains of the disease that are extensively drug-resistant (XDR) and multidrug-resistant (MDR). These TB superbugs necessitate innovative therapeutic strategies to improve treatment efficacy and patient compliance. Spray-drying technology has emerged as a promising method for the formulation of anti-TB therapies, offering advantages, such as enhanced drug stability, targeted delivery, and controlled release profiles. Key aspects include the principles of spray drying, the physicochemical characteristics of the resulting powders, and their impact on drug delivery to the lungs. Research focuses on optimizing these formulations to improve drug delivery directly to the lungs, enhance bioavailability, and abate side effects. This review underscores the transformative potential of these innovative spray-drying techniques, offering an effective and patient-friendly treatment regimen for TB. Additionally, the review highlights the potential of spray-dried formulations in developing host-directed therapies, antimicrobial peptides, vaccines, phages, and monoclonal antibodies. By integrating multidisciplinary approaches and cutting-edge technologies, spray-dried formulations promise to revolutionize TB treatment, ultimately contributing to better patient outcomes and the global effort to eradicate this persistent disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 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 it