Maxwell Gavin, Mackay Cameron
Unilever Safety & Environmental Assurance Centre (SEAC), Sharnbrook, Bedfordshire, UK.
Altern Lab Anim. 2008 Nov;36(5):521-56. doi: 10.1177/026119290803600510.
We have developed an in silico model of the induction of skin sensitisation, in order to characterise and quantify the contribution of each pathway to the overall biological process. This analysis has been used to guide our research on skin sensitisation and in vitro test development programmes, and provides a theoretical rationale for the interpretation and integration of non-animal predictive data for risk assessment (RA) purposes. The in vivo mouse Local Lymph Node Assay (LLNA) is now in widespread use for the evaluation of skin sensitisation potential and potency. Recent changes in European Union (EU) legislation (i.e. the 7th Amendment to the EU Cosmetics Directive) have made the development of nonanimal approaches to provide the data for skin sensitisation RA a key business need. Several in vitro predictive assays have already been developed for the prediction of skin sensitisation. However, these are based on the determination of a small number of pathways within the overall biological process, and our understanding of the relative contribution of these individual pathways to skin sensitisation induction is limited. To address this knowledge gap, a "systems biology" approach has been used to construct a computer-based mathematical model of the induction of skin sensitisation, in collaboration with Entelos, Inc. The biological mechanisms underlying the induction phase of skin sensitisation are represented by nonlinear ordinary differential equations and defined by using information from over 500 published papers. By using the model, we have identified knowledge gaps for future investigative research, and key factors that have a major influence on the induction of skin sensitisation (e.g. TNF-alpha production in the epidermis). The relative contribution of each of these key pathways has been assessed by determining their contributions to the overall process (e.g. sensitiser-specific T-cell proliferation in the draining lymph node). This information provides a biologically-relevant rationale for the interpretation and potential integration of diverse types of non-animal predictive data. Consequently, the Skin Sensitisation Physiolab (SSP) platform represents one approach to integration that is likely to prove an invaluable tool for hazard evaluation in a new framework for consumer safety RA.
我们开发了一种皮肤致敏诱导的计算机模型，以表征和量化每条途径对整体生物学过程的贡献。该分析已用于指导我们关于皮肤致敏和体外试验开发项目的研究，并为出于风险评估（RA）目的解释和整合非动物预测数据提供了理论依据。体内小鼠局部淋巴结试验（LLNA）目前广泛用于评估皮肤致敏潜力和效力。欧盟（EU）立法的近期变化（即欧盟化妆品指令的第7次修订）使得开发非动物方法以提供皮肤致敏RA数据成为一项关键业务需求。已经开发了几种体外预测试验来预测皮肤致敏。然而，这些试验基于确定整体生物学过程中的少数途径，并且我们对这些个体途径对皮肤致敏诱导的相对贡献的理解是有限的。为了填补这一知识空白，已与Entelos公司合作，采用“系统生物学”方法构建了一个基于计算机的皮肤致敏诱导数学模型。皮肤致敏诱导阶段的生物学机制由非线性常微分方程表示，并通过使用来自500多篇已发表论文的信息来定义。通过使用该模型，我们确定了未来研究的知识空白以及对皮肤致敏诱导有重大影响的关键因素（例如表皮中TNF-α的产生）。通过确定这些关键途径对整体过程的贡献（例如引流淋巴结中致敏剂特异性T细胞增殖），评估了每条途径的相对贡献。这些信息为解释和潜在整合不同类型的非动物预测数据提供了生物学相关的依据。因此，皮肤致敏生理实验室（SSP）平台代表了一种整合方法，在新的消费者安全RA框架中可能被证明是用于危害评估的宝贵工具。
