Is IL-23 the Winner? Lessons from Inflammatory Bowel Disease (IBD) and Psoriasis (PsO)
Bibliographic record
Abstract
Key Takeaways • Interleukin-23 (IL-23), and the IL-23/Th-17 interaction, plays a pivotal role in the pathogenesis of immune‑mediated diseases, such as psoriasis (PsO) and inflammatory bowel disease (IBD). This has led to the development and commercialization of several anti-IL-23 therapies, all demonstrating high efficacy and safety in the management of these conditions. • Anti-IL-23 therapies, have been shown to be amongst the most highly effective treatments in PsO, achieving meaningful and durable treatment response (PASI-90) in over 80 per cent of participants in registrational clinical trials, while in IBD the meaningful one-year efficacy, based on the varied definitions of the studies’ primary endpoints, is achieved (at most) in just over 50 per cent of participants, though rates of achieving remission in Crohn’s disease are much lower. • Several ongoing studies examining the role of IL-23 inhibition in specific IBD populations (ex. perianal Crohn’s disease), and studies examining the combination of IL-23 inhibitors with other targeted therapies, capitalizes on the excellent safety and efficacy profile of anti-IL-23, reflecting the long-term importance of these therapies in the IBD treatment landscape.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.018 |
| Insufficient payload (model declined to judge) | 0.009 | 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".