A quantitative systems pharmacology model for certolizumab pegol treatment in moderate-to-severe psoriasis

Frontiers in Immunology

Immunology

José Manuel Mas¹  Valentin Junet²  Filippo Guerri²  Cristina Segú-Vergés³  Guillem Jorba³  Pablo Coto-Segura⁴  Antonio Martorell⁵  David Moreno-Ramírez⁶  Xavier Daura⁷  Olaya Suárez-Magdalena⁸  Carlos Cara⁸  Sonya Abraham⁹  Baldomero Oliva^1,10 

[1] Anaxomics Biotech SL, Barcelona, Spain;Anaxomics Biotech SL, Barcelona, Spain;Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain;Anaxomics Biotech SL, Barcelona, Spain;Structural Bioinformatics Group, Research Programme on Biomedical Informatics, Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain;Dermatology Department, Hospital Vital Alvarez-Buylla de Mieres, Asturias, Spain;Dermatology Department, Hospital de Manises, Valencia, Spain;Dermatology Department, University Hospital Virgen Macarena, Andalusian Health Service, University of Seville, Seville, Spain;Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain;Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain;Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Cerdanyola del Vallès, Spain;Medical Affairs, UCB Pharma, Madrid, Spain;National Heart and Lung Institute (NHLI), Faculty of Medicine, Imperial College, London, United Kingdom;Medical Affairs, UCB Pharma, Brussels, Belgium;Structural Bioinformatics Group, Research Programme on Biomedical Informatics, Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain;

关键词: psoriasis;    anti-TNF;    certolizumab pegol;    mathematical modelling;    virtual population;    mechanism of action;   

DOI  :  10.3389/fimmu.2023.1212981

 received in 2023-04-27, accepted in 2023-08-07,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundPsoriasis is a chronic immune-mediated inflammatory systemic disease with skin manifestations characterized by erythematous, scaly, itchy and/or painful plaques resulting from hyperproliferation of keratinocytes. Certolizumab pegol [CZP], a PEGylated antigen binding fragment of a humanized monoclonal antibody against TNF-alpha, is approved for the treatment of moderate-to-severe plaque psoriasis. Patients with psoriasis present clinical and molecular variability, affecting response to treatment. Herein, we utilized an in silico approach to model the effects of CZP in a virtual population (vPop) with moderate-to-severe psoriasis. Our proof-of-concept study aims to assess the performance of our model in generating a vPop and defining CZP response variability based on patient profiles.MethodsWe built a quantitative systems pharmacology (QSP) model of a clinical trial-like vPop with moderate-to-severe psoriasis treated with two dosing schemes of CZP (200 mg and 400 mg, both every two weeks for 16 weeks, starting with a loading dose of CZP 400 mg at weeks 0, 2, and 4). We applied different modelling approaches: (i) an algorithm to generate vPop according to reference population values and comorbidity frequencies in real-world populations; (ii) physiologically based pharmacokinetic (PBPK) models of CZP dosing schemes in each virtual patient; and (iii) systems biology-based models of the mechanism of action (MoA) of the drug.ResultsThe combination of our different modelling approaches yielded a vPop distribution and a PBPK model that aligned with existing literature. Our systems biology and QSP models reproduced known biological and clinical activity, presenting outcomes correlating with clinical efficacy measures. We identified distinct clusters of virtual patients based on their psoriasis-related protein predicted activity when treated with CZP, which could help unravel differences in drug efficacy in diverse subpopulations. Moreover, our models revealed clusters of MoA solutions irrespective of the dosing regimen employed.ConclusionOur study provided patient specific QSP models that reproduced clinical and molecular efficacy features, supporting the use of computational methods as modelling strategy to explore drug response variability. This might shed light on the differences in drug efficacy in diverse subpopulations, especially useful in complex diseases such as psoriasis, through the generation of mechanistically based hypotheses.

【 授权许可】

Unknown   
Copyright © 2023 Coto-Segura, Segú-Vergés, Martorell, Moreno-Ramírez, Jorba, Junet, Guerri, Daura, Oliva, Cara, Suárez-Magdalena, Abraham and Mas