Secukinumab, a fully human anti-interleukin-17A monoclonal antibody, exhibits minimal immunogenicity in patients with moderate-to-severe plaque psoriasis
Bibliographic record
Abstract
BACKGROUND: The proinflammatory cytokine interleukin (IL)-17A plays a pivotal role in psoriasis pathogenesis. Secukinumab, a fully human monoclonal antibody (mAb) that selectively targets IL-17A, has been demonstrated to be highly efficacious for the treatment of moderate-to-severe psoriasis, starting at early time points, with a sustained effect and a favourable safety profile. mAb therapies may be associated with production of antidrug antibodies (ADAs) that can affect drug pharmacokinetics, diminish response or cause hypersensitivity reactions. OBJECTIVES: To investigate the immunogenicity of secukinumab across six phase III clinical trials in which patients with plaque psoriasis were treated with secukinumab for up to 52 weeks and additionally followed up at week 60. METHODS: Immunogenicity in patients with plaque psoriasis exposed to secukinumab was evaluated at baseline and at weeks 12, 24, 52 and 60. Treatment-emergent (TE)-ADAs were defined as a positive ADA signal detected in post-treatment samples from patients with a negative baseline signal. Confirmed positive samples were further analysed for their drug-neutralizing potential. RESULTS: Among 2842 patients receiving secukinumab and evaluated for ADAs, 11 (0·4%) developed TE-ADAs. Associations between TE-ADAs and secukinumab dose, frequency or mode of administration were not observed. Neutralizing antibodies were detected in three of nine evaluable patients with TE-ADAs. CONCLUSIONS: Secukinumab immunogenicity was low, as shown by TE-ADA detection in only 11 of 2842 (0·4%) patients with moderate-to-severe plaque psoriasis treated with secukinumab. All but one of the patients with TE-ADAs were biologic naive. Neither TE-ADAs nor neutralizing antibodies were associated with loss of secukinumab efficacy or issues of clinical concern.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".