Jager Tjalling, Heugens Evelyn H W, Kooijman Sebastiaan A L M
FALW/Department of Theoretical Biology, Vrije Universiteit Amsterdam, De Boelelaan 1085, NL-1081 HV, Amsterdam, The Netherlands.
Ecotoxicology. 2006 Apr;15(3):305-14. doi: 10.1007/s10646-006-0060-x. Epub 2006 Apr 20.
The environmental risk of chemicals is routinely assessed by comparing predicted exposure levels to predicted no-effect levels for ecosystems. Although process-based models are commonly used in exposure assessment, the assessment of effects usually comprises purely descriptive models and rules-of-thumb. The problems with this approach start with the analysis of laboratory ecotoxicity tests, because only a limited amount of information is extracted. Standard summary statistics (NOEC, ECx, LC50) are of limited use in part because they change with exposure duration in a manner that varies with the tested species and the toxicant. As an alternative, process-based models are available. These models allow for toxicity measures that are independent of exposure time, make efficient use of the available data from routine toxicity tests, and are better suited for educated extrapolations (e.g., from individual to population, and from continuous to pulse exposure). These capabilities can be used to improve regulatory decisions and allow for a more efficient assessment of effects, which ultimately will reduce the need for animal testing. Process-based modeling also can help to achieve the goals laid out in REACH, the new strategy of the European Commission in dealing with chemicals. This discussion is illustrated with effects data for Daphnia magna, analyzed by the DEBtox model.
通过比较预测的生态系统暴露水平与预测的无效应水平,定期评估化学品的环境风险。虽然基于过程的模型通常用于暴露评估,但效应评估通常包括纯粹的描述性模型和经验法则。这种方法的问题始于实验室生态毒性试验的分析,因为提取的信息有限。标准汇总统计量(无观察效应浓度、有效浓度x、半数致死浓度)的用途有限,部分原因是它们随暴露持续时间而变化,且这种变化方式因受试物种和毒物而异。作为一种替代方法,有基于过程的模型可用。这些模型允许采用与暴露时间无关的毒性测量方法,有效利用常规毒性试验的现有数据,并且更适合进行有根据的外推(例如,从个体到种群,以及从连续暴露到脉冲暴露)。这些能力可用于改进监管决策,并实现更高效的效应评估,最终将减少动物试验的需求。基于过程的建模还可以帮助实现欧盟委员会处理化学品的新战略——《化学品注册、评估、授权和限制法规》(REACH)中提出的目标。本文通过用DEBtox模型分析的大型溞效应数据对此进行说明。