Bibliographic record
Abstract
Biotechnology derived medicinal products are presently the best characterized biologicals with considerable production and clinical experience, and have revolutionized the treatment of some of the most difficult-to-treat diseases, prolonging and improving the quality of life and patient care. They are also currently one of the fastest growing segments of the pharmaceutical industry market. The critical challenge that the biopharmaceutical industry is facing is the expiry of patents for the first generation of biopharmaceuticals, mainly recombinant DNA derived products, such as interferons, growth hormone and erythropoetin. The question that immediately arose was how should such copies of the originator products be licensed, bearing in mind that they are highly complex biological molecules produced by equally complex biological production processes with their inherent problem of biological variability. Copying biologicals is much more complex than copying small molecules and the critical issue was how to handle the licensing of products if relying in part on data from an innovator product. Since 2004 there has been considerable international consultation on how to deal with biosimilars and biological copy products. This has led to a better understanding of the challenges in the regulatory evaluation of the quality, safety and efficacy of "biosimilars", to the exchange of information between regulators, as well as to the identification of key issues. The aim of this article is to provide a brief overview of the scientific and regulatory challenges faced in developing and evaluating similar biotherapeutic products for global use. It is intended as an introduction to the series of articles in this special issue of Biologicals devoted to similar biotherapeutic products.
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 | 0.018 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.014 | 0.030 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.021 | 0.016 |
| Insufficient payload (model declined to judge) | 0.039 | 0.012 |
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".