Ceylan Seda, Demir Didem, Harris Cayla, İpek Semih Latif, Vavourakis Vasileios, Manca Marco, Dubrac Sandrine, Bauer Roman
Department of Bioengineering, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye.
Department of Chemistry and Chemical Process Technologies, Tarsus University, Mersin, Türkiye.
BioData Min. 2025 Aug 19;18(1):55. doi: 10.1186/s13040-025-00471-8.
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.
随着计算技术的巨大进步，计算（或虚拟）建模已成为皮肤病学中一种变革性工具。这些发现能够为复杂的生物学过程提供全新见解，并有助于开发创新的皮肤治疗和再生策略。建模结合了多学科的实验数据和知识，作为阐明皮肤运作机制的通用框架。从生物医学角度来看，可以通过模拟细胞相互作用和信号通路来研究皮肤疾病的机制。对这些机制的计算研究可分为两种不同方法：数据驱动型和基于模型型。数据驱动型方法能够基于通过成像或便携式传感器反馈收集的数据来诊断皮肤疾病，其性能往往超过人类同行。基于模型的方法非常适合解决皮肤细胞生物学和生物力学等主题，有助于伤口愈合和皮肤癌研究。此外，这种建模在虚拟皮肤模型和芯片上皮肤设备的开发中也有应用，能够预测皮肤对各种物质（包括化妆品和药物）的反应。在皮肤科手术领域，计算工具在优化手术规划和改善临床结果方面发挥了重要作用。尽管已取得重大进展，但数据可用性、模型验证和跨学科合作等挑战依然存在。本综述重点介绍了皮肤病学计算建模的当前技术水平，确定了关键挑战，并概述了其前景。
