Estimating Costs of Market Exclusivity Extensions For 4 Top-Selling Prescription Drugs in the US
Bibliographic record
Abstract
Importance: Brand-name drugs in the US are sold at high prices during market exclusivity periods defined by their patents, before prices are lowered by generic competition. Drug manufacturers use several strategies to extend these market exclusivity periods and delay generic competition, including obtaining overlapping thickets of patents. Objective: To estimate excess US spending associated with delays in generic competition due to extended market exclusivity for 4 top-selling drugs. Design, Setting, and Participants: This retrospective serial cross-sectional study focused on 4 top-selling drugs that experienced new generic competition between 2014 and 2018 to allow enough time for determining postexclusivity price trajectories: imatinib (Gleevec, cancer), glatiramer (Copaxone, multiple sclerosis), celecoxib (Celebrex, arthritis), and bimatoprost (Lumigan, glaucoma). Drug monthly spending data from 2011 to 2021 were retrieved from a large commercial claims database (Merative MarketScan) and a random sample of Medicare beneficiaries with at least 1 month of Medicare Parts A, B, and D coverage and adjusted for estimated rebates obtained from SSR Health, LLC. The analysis was performed between March 2023 and January 2024. Exposures: Extended market exclusivity was calculated as the time between expiration of the key patent and first generic marketing. Main Outcomes and Measures: The primary outcome was net monthly national drug spending in commercial insurance and Medicare Part D. Spending was estimated under 2 scenarios: (1) the status quo, reflecting observed spending trends, and (2) a counterfactual scenario, modeling spending in the absence of extended market exclusivity. Segmented linear regression analyses were used to assess level and slope changes in monthly spending following generic entry. Weights were applied to extrapolate sample-based estimates to the full US commercially insured and Medicare Part D populations. Results: Market exclusivity extensions beyond expiration of the key patent ranged from 7 (celecoxib) to 13 (glatiramer) months. In the absence of extended market exclusivity, and over a 2-year period following generic competition, net spending would have decreased by $3.5 billion, including $1.9 (95% CI, $1.3-$2.5) billion in commercial plans and $1.6 (95% CI, $1.1-$2.1) billion in Medicare-including $67 (95% CI, $22-$115) million for bimatoprost, $726 (95% CI, $516-$938) million for celecoxib, $1.7 (95% CI, $1.0-$2.4) billion for glatiramer, and $1.0 (95% CI, $0.8-$1.2) billion for imatinib. Conclusions and Relevance: This study found that promoting timely generic availability and avoiding extending market exclusivity for top-selling drugs may result in substantial savings for US patients and payers, including both public and private health insurance programs.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".