European Commission, Joint Research Centre (JRC), Ispra, Italy; School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK(2).
European Commission, Joint Research Centre (JRC), Ispra, Italy; Oceansea Conservación del Medio Ambiente, Cádiz, Spain(2).
Environ Int. 2020 Oct;143:105978. doi: 10.1016/j.envint.2020.105978. Epub 2020 Aug 4.
Human biomonitoring (HBM) data can provide insight into co-exposure patterns resulting from exposure to multiple chemicals from various sources and over time. Therefore, such data are particularly valuable for assessing potential risks from combined exposure to multiple chemicals. One way to interpret HBM data is establishing safe levels in blood or urine, called Biomonitoring Equivalents (BE) or HBM health based guidance values (HBM-HBGV). These can be derived by converting established external reference values, such as tolerable daily intake (TDI) values. HBM-HBGV or BE values are so far agreed only for a very limited number of chemicals. These values can be established using physiologically based kinetic (PBK) modelling, usually requiring substance specific models and the collection of many input parameters which are often not available or difficult to find in the literature. The aim of this study was to investigate the suitability and limitations of generic PBK models in deriving BE values for several compounds with a view to facilitating the use of HBM data in the assessment of chemical mixtures at a screening level. The focus was on testing the methodology with two generic models, the IndusChemFate tool and High-Throughput Toxicokinetics package, for two different classes of compounds, phenols and phthalates. HBM data on Danish children and on Norwegian mothers and children were used to evaluate the quality of the predictions and to illustrate, by means of a case study, the overall approach of applying PBK models to chemical classes with HBM data in the context of chemical mixture risk assessment. Application of PBK models provides a better understanding and interpretation of HBM data. However, the study shows that establishing safety threshold levels in urine is a difficult and complex task. The approach might be more straightforward for more persistent chemicals that are analysed as parent compounds in blood but high uncertainties have to be considered around simulated metabolite concentrations in urine. Refining the models may reduce these uncertainties and improve predictions. Based on the experience gained with this study, the performance of the models for other chemicals could be investigated, to improve the accuracy of the simulations.
人体生物监测 (HBM) 数据可以提供有关多种化学物质从各种来源和随时间暴露的共同暴露模式的见解。因此，此类数据对于评估多种化学物质联合暴露的潜在风险特别有价值。解释 HBM 数据的一种方法是在血液或尿液中建立安全水平，称为生物监测等效物 (BE) 或 HBM 基于健康的指导值 (HBM-HBGV)。这些可以通过将已建立的外部参考值（如可耐受每日摄入量 (TDI) 值）转换来获得。迄今为止，仅针对非常有限数量的化学物质达成了 HBM-HBGV 或 BE 值。这些值可以使用基于生理学的动力学 (PBK) 模型来建立，通常需要特定物质的模型和收集许多输入参数，而这些参数通常在文献中不可用或难以找到。本研究旨在调查通用 PBK 模型在推导几种化合物的 BE 值方面的适用性和局限性，以期促进在筛选水平上使用 HBM 数据评估化学混合物。重点是使用两种通用模型，即 IndusChemFate 工具和高通量毒代动力学工具包，测试两种不同类别的化合物（酚类和邻苯二甲酸酯类）的方法学。使用丹麦儿童和挪威母亲和儿童的 HBM 数据来评估预测的质量，并通过案例研究说明在化学混合物风险评估背景下将 PBK 模型应用于具有 HBM 数据的化学类别总体方法。应用 PBK 模型可以更好地理解和解释 HBM 数据。然而，该研究表明，在尿液中建立安全阈值水平是一项困难且复杂的任务。对于以母体化合物形式在血液中分析的更持久的化学物质，该方法可能更为直接，但必须考虑到尿液中模拟代谢物浓度的高度不确定性。改进模型可以降低这些不确定性并提高预测的准确性。基于本研究获得的经验，可以研究模型对其他化学物质的性能，以提高模拟的准确性。
