Review article: pharmacological aspects of anti-TNF biosimilars in inflammatory bowel diseases
Bibliographic record
Abstract
BACKGROUND: Anti-tumour necrosis factor (anti-TNF) monoclonal antibodies have shown efficacy in inflammatory bowel diseases (IBD). As these therapies lose patent protection, biosimilar versions of the originator products are being developed, such as the infliximab biosimilar CT-P13; however, some uncertainty exists regarding their pharmacology in IBD. AIM: To review the literature on anti-TNF biosimilars focusing on pharmacokinetics, pharmacodynamic properties and comparative effectiveness, related to their use in IBD. METHODS: A PubMed literature search was performed using the following terms individually or in combination: 'biosimilars,' 'CT-P13,' 'Crohn's disease,' 'inflammatory bowel disease,' 'ulcerative colitis,' 'anti-TNFα therapy,' 'infliximab,' 'adalimumab,' 'pharmacokinetics,' 'immunogenicity.' RESULTS: Bioequivalence of CT-P13 and infliximab was shown in ankylosing spondylitis (AS) and therapeutic equivalence in rheumatoid arthritis (RA). Preliminary results of CT-P13 in IBD come from small post-marketing registries and case series with a relatively short-term follow-up period and suggest comparable efficacy and safety to infliximab. Inter- and intra-individual differences in exposure and response are well known for the original molecules but dosing regimens and concomitant medications are different for RA compared to IBD, limiting the ability to translate some of the pharmacology data in RA to IBD. Uncertainty exists about cross-reactivity of anti-drug antibodies and whether similar exposure-response relationships will be observed for biosimilars and efficacy thresholds for therapeutic drug monitoring can be used interchangeably. CONCLUSIONS: It is likely that biosimilars will be widely used for the treatment of IBD due to their cost savings and comparable efficacy. Nevertheless, robust post-marketing studies and pharmacovigilance are warranted in the coming years.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".