Regulatory Overview of Biosimilars: Current Scenario and Future Opportunities
Bibliographic record
Abstract
Background: Biosimilar products (biosimilars) are highly similar versions of approved and authorized biological medicines (which are used to treat a wide range of diseases including cancer, rheumatoid arthritis, diabetes and anemia) that have come as revolutionary paradigm in therapeutics. They are similar copies of already approved biologicals (reference products), produced by more reliable methods. Biosimilars are able to reduce the cost of the reference product by 20% to 35%. Objectives: This mini-review article has been planned to discuss the regulatory aspects of the biosimilars as well as basic facts about the biosimilars. Recent developments in the area of biosimilars will be discussed along with future opportunities and challenges in the field of manufacturing and marketing of the biosimilars in biopharmaceutical industry. Discussion: The main driving force behind the development of biosimilars is the expiry of patents for the approved biological products worldwide. The patent protection for the approved biological products have either expired or about to expire. Thus the market is opening for ‘biosimilars’. The global market for biosimilars is expected to reach USD 6.22 billion by 2020 from USD 2.29 billion in 2015. The regulatory requirements for the approval of biosimilars are not as easy as that of the conventional generic drugs. Europe, United States, China, India, Japan, Canada & World Health Organization have published guidelines for biosimilars but there is no harmonised pathway for regulation of biosimilars.
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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".