History of Aerosol Therapy: Liquid Nebulization to MDIs to DPIs
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
Inhaled therapies have been used since ancient times and may have had their origins with the smoking of datura preparations in India 4,000 years ago. In the late 18th and in the 19th century, earthenware inhalers were popular for the inhalation of air drawn through infusions of plants and other ingredients. Atomizers and nebulizers were developed in the mid-1800s in France and were thought to be an outgrowth of the perfume industry as well as a response to the fashion of inhaling thermal waters at spas. Around the turn of the 20th century, combustible powders and cigarettes containing stramonium were popular for asthma and other lung complaints. Following the discovery of the utility of epinephrine for treating asthma, hand-bulb nebulizers were developed, as well as early compressor nebulizers. The marketing of the first pressurized metered-dose inhaler for epinephrine and isoproterenol, by Riker Laboratories in 1956, was a milestone in the development of inhaled drugs. There have been remarkable advances in the technology of devices and formulations for inhaled drugs in the past 50 years. These have been influenced greatly by scientific developments in several areas: theoretical modeling and indirect measures of lung deposition, particle sizing techniques and in vitro deposition studies, scintigraphic deposition studies, pharmacokinetics and pharmacodynamics, and the 1987 Montreal Protocol, which banned chlorofluorocarbon propellants. We are now in an era of rapid technologic progress in inhaled drug delivery and applications of aerosol science, with the use of the aerosolized route for drugs for systemic therapy and for gene replacement therapy, use of aerosolized antimicrobials and immunosuppressants, and interest in specific targeting of inhaled drugs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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