Skin in the game: a review of computational models of the skin

With the vast advances in computing technology, computational (or in silico) modelling has emerged as a transformative tool in dermatology. These findings can provide novel insights into complex biological processes and aid in the development of innovative therapeutic and regenerative strategies for the skin. Modelling combines experimental data and knowledge across multiple disciplines, serving as a common framework to elucidate the workings of the skin. From a biomedical perspective, the mechanisms of skin diseases can be studied by simulating cellular interactions and signalling pathways. Computational investigations of these mechanisms can be categorised into two distinct approaches: data-driven and model-based. Data-driven approaches allow the diagnosis of skin diseases on the basis of data collection via imaging or feedback from portable sensors, often yielding performance exceeding that of their human counterparts. Model-based methods are well suited to address topics such as skin cell biology and biomechanics, contributing to wound healing and skin cancer research. Furthermore, such modelling has found utility in the development of virtual skin models and skin-on-chip devices, enabling the prediction of skin responses to various substances, including cosmetics and drugs. In the realm of dermatological surgery, computational tools have been instrumental in optimizing surgical planning and improving clinical outcomes. While significant advancements have been made, challenges such as data availability, model validation, and interdisciplinary collaboration persist. This review highlights the current state-of-the-art in computational modeling in dermatology, identifies key challenges, and outlines its prospects.