Computational modelling in Next Generation Risk Assessment (NGRA) for Chemical Safety and Case Study
报告题目：Computational modelling in Next Generation Risk Assessment (NGRA) for Chemical Safety and Case Study
报告时间：2019年9月20日，星期五，下午3:00-5:00
报告地点：数学与统计学院 北五楼319会议室
报告人：Jin Li，Safety & Environmental Assurance Centre, Unilever
报告摘要：
The principles for the use of non-animal approaches in consumer safety risk assessments were recently outlined by the International Cooperation on Cosmetics Regulation (ICCR1). A key principle is that modern risk assessments should be exposure-led. This means that novel methods that are used to make decisions about human safety must be quantitative, so that any predictions relating to dose must be interpretable in the context of actual levels of consumer exposure. Interpreting dose-response data from in vitro toxicity assays requires an understanding of both cellular exposure in in vitro assays and how these relate to in vivo internal concentrations. Understanding both dosimetry and physiologically-based kinetic (PBK) modelling have been identified as essential components for robust decision-making in Next Generation Risk Assessments (NGRA).
For evaluation of systemic toxicity using NGRA approaches, a series of case study chemicals (including caffeine, curcumin and coumarin) are being evaluated in a joint research programme between Unilever and the US Environmental Protection agency (EPA). This uses selected ToxCast assays and high throughput transcriptomics together with in silico chemistry tools and PBK modelling. A key challenge with respect to the application of these tools for safety decision-making is a reliance on quantification of in vitro-to-in vivo extrapolation, where computational modelling plays a vital role.
This talk will briefly introduce the NGRA principles and focus on applications of computational modelling within the framework. Interdisciplinary research and development is always highly demanded in addressing real-world problems in industry.
1.Dent M et al (2018) Principles underpinning the use of new methodologies in the risk assessment of cosmetics. Computational Toxicology, 7, 20-26.
报告人简介：
李津博士在联合利华安全与环境保障中心工作12多年。 目前是一名资深高级毒理学风险评估师。他主要职责从事开发和应用非动物方法来进行化学物的毒理风险评估，包括 1）整合基于计算机预测，体外和体内多类别数据; 2)开发基于毒性通路的21世纪毒理风险评估方法。他同时协作编写法规部门所需在中国上市的化妆品风险评估案卷. 自2011年以来，李津一直积极促进中国科学家与来自欧盟和美国的西方科学家的对话交流，协作规划及积极组织举办多次国际研讨会/毒理学会议，教育培训班。并在中国创立多项前沿的科研及教育合作项目，包括与中国军事医学院，中国科学院，北京大学，北京蛋白质组的研究合作项目等以促进中国毒理学的发展和技术进步。同时他也积极与中检院，广东疾控所，以及上海食监局合作以促进以风险为基础的非动物替代方法在中国化妆品及化学物安全风险评估上的开发及应用。李津目前是中国毒理学会的会员，中国毒理学会毒理学替代法与转化毒理学专委会的常务委员, 以及计算毒理专委会及食品毒理学专委会的委员。他在中国获得 学士及硕士，于2000年获得了英国艾塞克斯大学计算机博士学位。于2006年加入联合利华研发部门。
