Patents And Regulatory Exclusivities On Inhalers For Asthma And COPD, 1986–2020
Bibliographic record
Abstract
Inhalers are the mainstay of treatment for asthma and chronic obstructive pulmonary disease (COPD). These products face limited generic competition in the US and remain expensive. To better understand the strategies that brand-name inhaler manufacturers have employed to preserve their market dominance, we analyzed all patents and regulatory exclusivities granted to inhalers approved by the Food and Drug Administration between 1986 and 2020. Of the sixty-two inhalers approved, fifty-three were brand-name products, and these brand-name products had a median of sixteen years of protection from generic competition. Only one inhaler contained an ingredient with a new mechanism of action. More than half of all patents were on the inhaler devices, not the active ingredients or other aspects of these drug-device combinations. Manufacturers augmented periods of brand-name market exclusivity by moving active ingredients from one inhaler device into another ("device hops"). The median time from approval of an originator product to the last-to-expire patent or regulatory exclusivity of branded follow-ons was twenty-eight years (across device hops on fourteen originator products). Regulatory and patent reform is critical to ensure that the rewards bestowed on brand-name inhaler manufacturers better reflect the added clinical benefit of new products.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".