Interleukin 23p19 inhibitors in chronic plaque psoriasis with focus on mirikizumab: A narrative review
Bibliographic record
Abstract
Psoriasis, a T-cell mediated chronic dermatosis, has a complex etiopathogenesis. There has been extensive research into the aberrant immune response, which leads to the formation of clinical lesions, and the need for developing better and safer drugs has been unrelenting. The past two decades of research has opened up new areas of the immune pathway that can be targeted in order to control the disease. Therefore, we have seen the emergence of biologics which either target T-cell receptors or inhibit Tumor Necrosis Factor-alpha (TNF-α) or inhibit interleukins (IL) like IL-12, IL-17, IL-17 receptor, and more recently IL-23. Drugs specifically targeting the p19 subunit of IL-23 have shown promising results in the management of chronic plaque psoriasis. This has given way to the development of a new class of biologics, that is, the IL-23p19 inhibitors that have a better safety profile as compared to its predecessors. In this review, we shall scrutinize the role of IL-23 and Th17 cell signaling in the evolution of the psoriatic lesions and summarize the clinical experience with IL-23p19 inhibitors especially mirikizumab in the treatment of chronic plaque psoriasis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".