Imperial College London
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Professor Reiko J. Tanaka

Faculty of Engineering, Department of Bioengineering

Professor of Computational Systems Biology & Medicine
 
 
 
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Contact

 

+44 (0)20 7594 6374r.tanaka Website

 
 
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Location

 

RSM 3.10Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Miyano:2021:10.1101/2021.02.08.21251317,
author = {Miyano, T and Irvine, AD and Tanaka, RJ},
doi = {10.1101/2021.02.08.21251317},
title = {A mathematical model to identify optimal combinations of drug targets for dupilumab poor responders in atopic dermatitis},
url = {http://dx.doi.org/10.1101/2021.02.08.21251317},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - UNPB
AB  - <jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Several biologics for atopic dermatitis (AD) have demonstrated good efficacy in clinical trials, but with a substantial proportion of patients being identified as poor responders. This study aims to understand the pathophysiological backgrounds of patient variability in drug response, especially for dupilumab, and to identify promising drug targets in dupilumab poor responders.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We conducted model-based meta-analysis of recent clinical trials of AD biologics and developed a mathematical model that reproduces reported clinical efficacies for nine biological drugs (dupilumab, lebrikizumab, tralokinumab, secukinumab, fezakinumab, nemolizumab, tezepelumab, GBR 830, and recombinant interferon-gamma) by describing systems-level AD pathogenesis. Using this model, we simulated the clinical efficacy of hypothetical therapies on virtual patients.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Our model reproduced reported time courses of %improved EASI and EASI-75 of the nine drugs. The global sensitivity analysis and model simulation indicated the baseline level of IL-13 could stratify dupilumab good responders. Model simulation on the efficacies of hypothetical therapies revealed that simultaneous inhibition of IL-13 and IL-22 was effective, whereas application of the nine biologic drugs was ineffective, for dupilumab poor responders (EASI-75 at 24 weeks: 21.6% vs. max. 1.9%).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Our model identified IL-13 as a potential predictive biomarker to stratify dupilumab good responders, and simultaneous inhibition of IL-13 and IL-22 as a promising drug therapy for dupilumab poor responders. This mod
AU  - Miyano,T
AU  - Irvine,AD
AU  - Tanaka,RJ
DO  - 10.1101/2021.02.08.21251317
PY  - 2021///
TI  - A mathematical model to identify optimal combinations of drug targets for dupilumab poor responders in atopic dermatitis
UR  - http://dx.doi.org/10.1101/2021.02.08.21251317
ER  -
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