Wolf Douglas C, Bachman Ammie, Barrett Gordon, Bellin Cheryl, Goodman Jay I, Jensen Elke, Moretto Angelo, McMullin Tami, Pastoor Timothy P, Schoeny Rita, Slezak Brian, Wend Korinna, Embry Michelle R
a Syngenta Crop Protection LLC , Greensboro , NC , USA.
b ExxonMobil Biomedical Sciences, Inc. , Annandale , NJ , USA.
Crit Rev Toxicol. 2016;46(1):43-53. doi: 10.3109/10408444.2015.1082973. Epub 2015 Oct 9.
The HESI-led RISK21 effort has developed a framework supporting the use of twenty-first century technology in obtaining and using information for chemical risk assessment. This framework represents a problem formulation-based, exposure-driven, tiered data acquisition approach that leads to an informed decision on human health safety to be made when sufficient evidence is available. It provides a transparent and consistent approach to evaluate information in order to maximize the ability of assessments to inform decisions and to optimize the use of resources. To demonstrate the application of the framework's roadmap and matrix, this case study evaluates a large number of chemicals that could be present in drinking water. The focus is to prioritize which of these should be considered for human health risk as individual contaminants. The example evaluates 20 potential drinking water contaminants, using the tiered RISK21 approach in combination with graphical representation of information at each step, using the RISK21 matrix. Utilizing the framework, 11 of the 20 chemicals were assigned low priority based on available exposure data alone, which demonstrated that exposure was extremely low. The remaining nine chemicals were further evaluated, using refined estimates of toxicity based on readily available data, with three deemed high priority for further evaluation. In the present case study, it was determined that the greatest value of additional information would be from improved exposure models and not from additional hazard characterization.
由健康效应模拟研究所(HESI)牵头的“风险21”项目开发了一个框架,支持在获取和使用化学风险评估信息时运用21世纪的技术。该框架代表了一种基于问题表述、以暴露为驱动、分层数据采集的方法,当有足够证据时,可据此做出关于人类健康安全的明智决策。它提供了一种透明且一致的信息评估方法,以最大限度地提高评估为决策提供信息的能力,并优化资源利用。为展示该框架路线图和矩阵的应用,本案例研究评估了大量可能存在于饮用水中的化学物质。重点是确定哪些物质作为单一污染物应被优先考虑对人类健康构成的风险。该示例使用分层的“风险21”方法,并结合每一步信息的图形表示(使用“风险21”矩阵),评估了20种潜在的饮用水污染物。利用该框架,仅根据现有的暴露数据,20种化学物质中的11种被列为低优先级,这表明其暴露水平极低。其余9种化学物质则根据可得数据对毒性进行了更精确的估计,进一步评估,其中3种被视为高优先级需进一步评估。在本案例研究中,确定额外信息的最大价值将来自改进的暴露模型,而非额外的危害特征描述。