A model-informed approach to assess the risk of immune checkpoint inhibitor-induced autoimmune myocarditis

Autor: Solveig A. van der Vegt, Ying-Jie Wang, Liudmila Polonchuk, Ken Wang, Sarah L. Waters, Ruth E. Baker
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Pharmacology, Vol 13 (2022)
Druh dokumentu: article
ISSN: 1663-9812
DOI: 10.3389/fphar.2022.966180
Popis: Immune checkpoint inhibitors (ICIs), as a novel immunotherapy, are designed to modulate the immune system to attack malignancies. Despite their promising benefits, immune-related adverse events (IRAEs) may occur, and incidences are bound to increase with surging demand of this class of drugs in treating cancer. Myocarditis, although rare compared to other IRAEs, has a significantly higher fatal frequency. Due to the overwhelming complexity of the immune system, this condition is not well understood, despite the significant research efforts devoted to it. To better understand the development and progression of autoimmune myocarditis and the roles of ICIs therein, we suggest a new approach: mathematical modelling. Mathematical modelling of myocarditis has enormous potential to determine which parts of the immune system are critical to the development and progression of the disease, and therefore warrant further investigation. We provide the immunological background needed to develop a mathematical model of this disease and review relevant existing models of immunology that serve as the mathematical inspiration needed to develop this field.
Databáze: Directory of Open Access Journals