The Expanding Role of Aerosols in Systemic Drug Delivery, Gene Therapy, and Vaccination
Bibliographic record
Abstract
Aerosolized medications have been used for centuries to treat respiratory diseases. Until recently, inhalation therapy focused primarily on the treatment of asthma and chronic obstructive pulmonary disease, and the pressurized metered-dose inhaler was the delivery device of choice. However, the role of aerosol therapy is clearly expanding beyond that initial focus. This expansion has been driven by the Montreal protocol and the need to eliminate chlorofluorocarbons (CFCs) from traditional metered-dose inhalers, by the need for delivery devices and formulations that can efficiently and reproducibly target the systemic circulation for the delivery of proteins and peptides, and by developments in medicine that have made it possible to consider curing lung diseases with aerosolized gene therapy and preventing epidemics of influenza and measles with aerosolized vaccines. Each of these drivers has contributed to a decade or more of unprecedented research and innovation that has altered how we think about aerosol delivery and has expanded the role of aerosol therapy into the fields of systemic drug delivery, gene therapy, and vaccination. During this decade of innovation, we have witnessed the coming of age of dry powder inhalers, the development of new soft mist inhalers, and improved pressurized metered-dose inhaler delivery as a result of the replacement of CFC propellants with hydrofluoroalkane. The continued expansion of the role of aerosol therapy will probably depend on demonstration of the safety of this route of administration for drugs that have their targets outside the lung and are administered long term (eg, insulin aerosol), on the development of new drugs and drug carriers that can efficiently target hard-to-reach cell populations within the lungs of patients with disease (eg, patients with cystic fibrosis or lung cancer), and on the development of devices that improve aerosol delivery to infants, so that early intervention in disease processes with aerosol therapy has a high probability of success.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".