Biological patent thickets and delayed access to biosimilars, an American problem
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
Our study seeks to determine whether patent thickets covering biologic drugs are responsible for delayed biosimilar market entry. We compare patent assertions against the same biosimilar drugs across three countries. On average nine to twelve times more patents were asserted against biosimilars in the United States than in Canada and the United Kingdom. Biosimilars also enter the Canadian and UK markets more quickly than they do in the United States following regulatory approval. Later market entry is not a problem when the brand name drug company is asserting high quality patents (i.e. patents covering significant advances). Consequently, we drilled down into the U.S. patent portfolio of one major biologic, Abbvie's Humira drug, and found that it was made up of roughly 80% non-patentably distinct (duplicative) patents linked together by terminal disclaimers, which is permitted under United States Patent and Trademark Office (USPTO) rules. In contrast, there were far less non-duplicative European patents that covered Humira. Patent thickets can allow brand name drug companies to delay biosimilar entry by relying on the high cost of challenging many duplicative patents instead of the quality of their underlying patents. Accordingly, we suggest several policy interventions that may thin these biologic patent thickets.
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 | 0.002 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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