ArticleCPT: pharmacometrics & systems pharmacology2025
Model-Informed Drug Development for Ligelizumab in Patients With Chronic Spontaneous Urticaria.
Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Ligelizumab Immunogenicity and Impact on Pharmacokinetics, Pharmacodynamics, Efficacy, and Safety in Patients With Chronic Spontaneous Urticaria.Clinical and translational science · 2026Trial
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Model-informed drug development (MIDD) has been increasingly applied to guide decision-making, ameliorate efficiency, and enhance the likelihood of successful trials. The development of ligelizumab, a humanized anti-IgE monoclonal antibody, in chronic spontaneous urticaria (CSU) illustrated how MIDD can be applied to support central aspects of drug development, such as dose selection and trial design, pediatric drug development and extrapolation, generation of evidence to support potential labeling, optimizing treatment outcomes, and enhancing patient access. In this manuscript, we provide an overview of the key modeling and simulation analyses that were part of the MIDD approach for the development of ligelizumab in CSU and how they were staggered around the availability of interim and final data from the Phase 2 and Phase 3 studies. Furthermore, we present details of the non-linear mixed-effects models characterizing the population pharmacokinetics and exposure-response relationship of ligelizumab for efficacy in adolescent and adult patients with CSU.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.