Bibliographic record
Abstract
The first of its kind drug, recombinant human insulin(Humulin) received administrative approval in America in 1982. A quarter of a century later, recombinant protein drug represents a sector undergoing the fastest growth, accounting for 7%～8% of today's market of prescription drugs. Among the 82 recombinant proteins therapeutics licensed so far, 18 are block-busters with the annual sale of 27 billion dollars in 2005, which is 66% of the total sale of 41 billion for the whole sector. Year 2006 observed several landmark events in this field, including the approval of the first inhalational insulin by US and EU, and the marketing of the first recombinant drug produced in transgenic animals and the first generic recombinant drug in EU. While it is blooming, how long will the blossom last? In this article, the market of the recombinant protein therapeutics launched in US and EU was dissected by their group sale. In addition, the ongoing research and development efforts in this field were reviewed. Such information should be of help for better judgment of the market trend and for the strategic planning of innovation.
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.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".