<p>The Climate is Changing for Metered-Dose Inhalers and Action is Needed</p>
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
Increases in global temperature are already having a significant impact on our climate. The hydrofluorocarbon (HFC) propellants used today in pressurized metered-dose inhalers (pMDIs) have global warming potential (GWP) many times that of carbon dioxide. Their use, together with all other emissive uses of HFCs, is being phased down under the Montreal protocol. This has prompted calls to switch patients to dry powder inhalers (DPIs). This paper presents a new analysis of the top 15 respiratory drug markets by drug class. It shows that a switch to DPIs would be economically feasible for most countries and most drugs. However, a wholesale switch of reliever medications, notably short-acting β-agonists, would lead to significant increases in the cost of these life-saving medications. Reviewing the evidence, whilst most patients are capable of using DPIs, the very young, very old and those undergoing an acute exacerbation still require a pMDI. Thus, there is a clinical and economic need to have both pMDIs and DPIs available. At the same time, it is projected that the reduction in non-medical uses of propellants is likely to give rise to a 5-fold increase in their cost for pMDI uses and is likely to hit the Western world in 2025. This may lead to a price increase in reliever medication that will make it unaffordable for the poorer communities in some markets. At the same time, opportunities to save money by developing new formulations using propellants with lower GWP, such as HFC 152a or HFO 1234ze(E), are described. Two companies have made this commitment, but neither currently have a strong presence in reliever medication. For them, or other companies, now is the time to act; 2025 is not far away in terms of product development timescales and the climate cannot wait.
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) | 0.000 | 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