Toxicity risk assessment of chemical mixture possesses huge challenges due to limited evidence on toxicity of compounds, the infinite number of chemical combinations makes the problem even more difficult. Normally, prediction of joint mixture toxicity depends on toxicological data of constituent compounds, although lack of information on dose-response of chemical mixture raises serious concerns on human health. Component-based approaches mainly use dose-addition or response-addition method to assess mixture toxicity risk exposure. Several models based on theoretical concepts of concentration/dose addition and independent/response action were also developed but these models do not address chemical interactions in mixture, and were mostly used to assess ecological risk exposure with limited or no information on human health risk assessment. This paper reviews available models to predict joint toxicity of chemical mixtures, and most applicable one to address human health risk exposure was identified. United States Environmental Protection Agency (US EPA) weight-of-evidence hazard index (HI) based approach seems to be most appropriate to predict joint toxicity of chemical mixtures, and applicability of model is explained using emerging contaminants as an example. The review also identified challenges in implementing the interaction-based EPA approach and highlighted the need for necessary future research actions.

由于化合物毒性的证据有限，化学混合物的毒性风险评估面临着巨大的挑战，无限数量的化学组合使问题变得更加棘手。通常，对关节混合物毒性的预测取决于组成化合物的毒理学数据，尽管缺乏有关化学混合物剂量反应的信息引起了人们对人体健康的严重关注。基于组分的方法主要使用剂量加法或响应加法来评估混合物毒性风险暴露。还开发了几种基于浓度/剂量添加和独立/响应作用的理论概念的模型，但这些模型未解决混合物中的化学相互作用，主要用于评估生态风险暴露，而有关人类健康风险评估的信息有限或没有。本文回顾了可预测化学混合物的联合毒性的可用模型，并确定了最适用于解决人类健康风险暴露的模型。美国环境保护署（US EPA）的基于证据重量危害指数（HI）的方法似乎最适合预测化学混合物的联合毒性，并且以新兴污染物为例对模型的适用性进行了解释。审查还确定了在实施基于交互作用的EPA方法时遇到的挑战，并强调了未来有必要采取必要的研究行动。美国环境保护署（US EPA）的基于证据重量危害指数（HI）的方法似乎最适合预测化学混合物的联合毒性，并且以新兴污染物为例对模型的适用性进行了解释。审查还确定了在实施基于交互作用的EPA方法时遇到的挑战，并强调了未来有必要采取必要的研究行动。美国环境保护署（US EPA）的基于证据重量危害指数（HI）的方法似乎最适合预测化学混合物的联合毒性，并且以新兴污染物为例对模型的适用性进行了解释。审查还确定了在实施基于交互作用的EPA方法时遇到的挑战，并强调了未来有必要采取必要的研究行动。