Calculating expected lung deposition of aerosolized administration of AAV vector in human clinical studies
Bibliographic record
Abstract
BACKGROUND: Cystic fibrosis is an autosomal recessive disease affecting approximately 1 in 2500 live births. Introducing the cDNA that codes for normal cystic fibrosis transmembrane conductance regulator (CFTR) to the small airways of the lung could result in restoring the CFTR function. A number of vectors for lung gene therapy have been tried and adeno-associated virus (AAV) vectors offer promise. The vector is delivered to the lung using a breath-actuated jet nebulizer. The purpose of this project was to determine the aerosolized AAV (tgAAVCF) particle size distribution (PSD) in order to calculate target doses for lung delivery. METHODS: A tgAAVCF solution was nebulized using the Pari LC Plus (n = 3), and the PSD was determined by coupling laser diffraction and inertial impaction (NGI) techniques. The NGI allowed for quantification of the tgAAVCF at each stage of impaction, ensuring that rAAV-CFTR vector is present and not empty particles. Applying the results to mathematical algorithms allowed for the calculation of expected pulmonary deposition. RESULTS: The mass median diameter (MMD) for the tgAAVCF was 2.78 +/- 0.43 microm. If the system works ideally and the patient only receives aerosol on inspiration, the patient would receive 47 +/- 0% of the initial dose placed in the nebulizer, with 72 +/- 0.73% of this being deposited beyond the vocal cords. CONCLUSIONS: This technology for categorizing the pulmonary delivery system for lung gene therapy vectors can be adapted for advanced aerosol delivery systems or other vectors.
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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) | 0.001 | 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".