In this section
@article{Wu:2026,
author = {Wu, A and Le, Floch P and Duverdier, A and Irvine, A and Dubrac, S and Tanaka, R},
journal = {JID Innovations},
title = {Current research landscape and future prospects of in silico modeling approaches for atopic dermatitis},
year = {2026}
}
TY - JOUR
AB - Atopic dermatitis (AD) is a chronic, multifactorial inflammatory skin disease with complex, heterogeneous pathogenesis. Understanding its mechanisms, stratifying patients into biologically relevant endotypes, and predicting treatment responses remains challenging if we use empirical approaches alone. In silico approaches, including mathematical modeling, statistical and machine learning methods, enable the dissection of molecular and cellular interactions, identification of key clinical and biological drivers, and extraction of meaningful insights from high-dimensional, noisy datasets, while preserving a systems-level perspective. This review summarizes recent advancements in in silico approaches for AD and outlines strategies to enhance their translational and clinical utility in AD research.
AU - Wu,A
AU - Le,Floch P
AU - Duverdier,A
AU - Irvine,A
AU - Dubrac,S
AU - Tanaka,R
PY - 2026///
SN - 2667-0267
TI - Current research landscape and future prospects of in silico modeling approaches for atopic dermatitis
T2 - JID Innovations
ER -