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Regulatory Overview of Biosimilars: Current Scenario and Future Opportunities

2015· article· en· W2759170843 on OpenAlexaboutno aff
Ajmer Singh Grewal, Viney Lather, Shashikant Bhardwaj, Deepti Pandita

Bibliographic record

VenueApplied Clinical Research Clinical Trials and Regulatory Affairs · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsBiosimilarBiopharmaceuticalMedicineBusinessRisk analysis (engineering)Biotechnology

Abstract

fetched live from OpenAlex

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%. </p> <p> 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. </p> <p> 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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.104
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.756
GPT teacher head0.584
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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