Issues in Drug Delivery: Concepts and Practice
Bibliographic record
Abstract
Understanding the transport and deposition of inhaled aerosols is of fundamental importance to inhalation therapy. Herein we address issues that affect drug delivery from experimental and theoretical perspectives. Accordingly, we shall limit our comments to a focused review of laboratory work (ie, an in vitro perspective) and the development of a computer-based 3-dimensional (3D) oral morphology with related computational fluid dynamics (CFD) and particle deposition studies (ie, an "in silico" perspective). To describe the oral region, morphometric data from the literature were employed. With Maya Unlimited, a third-party animation software package, coronal images were used to create initial spline curves, which served as the foundation of a nonuniform rational B-spline surface, representing a 3D morphology. To the best of our knowledge, this study is the first medical application of Maya Unlimited. We have demonstrated that the code can be employed to construct 3D biological structures and perform 3D CFD simulations of aerosols from dry powder inhalers and metered-dose inhalers. A study was also conducted using Fluent, a commercially available software package that has been used extensively in our laboratory for 3D CFD computations. The Maya Unlimited software can generate physiologically realistic oral structures; it has great potential for use in the medical arena, because it requires neither advance technical training nor substantial peripheral ( eg, hardware) support, it allows for the introduction of medical devices ( eg, dry powder inhalers) into simulations, and it predicts 3D CFDpatterns consistent with experimental observations and results of more rigorous software ( Fluent). In the in vitro perspective we considered numerous salient topics, including the performances of dry powder inhalers and metered-dose inhalers, their respective operating characteristics, and relevance to in vivo data. We advocate that 3D CFD software be employed in a complementary manner, in real time, with aerosol therapy protocols in the medical arena, to promote the targeted delivery of inhaled drugs and thereby enhance their efficacies.
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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 | 0.000 | 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".