Carter Laura J, Wilkinson John L, Boxall Alistair B A
Department of Environment and Geography, University of York, York YO10 5NG, UK.
Toxics. 2020 Feb 11;8(1):13. doi: 10.3390/toxics8010013.
In order to assess the environmental risk of a pharmaceutical, information is needed on the sorption of the compound to solids. Here we use a high-quality database of measured sorption coefficients, all determined following internationally recognised protocols, to evaluate models that have been proposed for estimating sorption of pharmaceuticals from chemical structure, some of which are already being used for environmental risk assessment and prioritization purposes. Our analyses demonstrate that octanol-water partition coefficient () alone is not an effective predictor of ionisable pharmaceutical sorption in soils. Polyparameter models based on pharmaceutical characteristics in combination with key soil properties, such as cation exchange capacity, increase model complexity but yield an improvement in the predictive capability of soil sorption models. Nevertheless, as the models included in this analysis were only able to predict a maximum of 71% and 67% of the sorption coefficients for the compounds to within one log unit of the corresponding measured value in soils and sludge, respectively, there is a need for new models to be developed to better predict the sorption of ionisable pharmaceuticals in soil and sludge systems. The variation in sorption coefficients, even for a single pharmaceutical across different solid types, makes this an inherently difficult task, and therefore requires a broad understanding of both chemical and sorbent properties driving the sorption process.
为了评估一种药物的环境风险，需要有关该化合物在固体上吸附的信息。在此，我们使用一个高质量的测量吸附系数数据库，所有数据均按照国际认可的协议测定，以评估已提出的用于从化学结构估算药物吸附的模型，其中一些模型已用于环境风险评估和优先级排序。我们的分析表明，仅辛醇 - 水分配系数（）并不是土壤中可电离药物吸附的有效预测指标。基于药物特性并结合关键土壤性质（如阳离子交换容量）的多参数模型增加了模型的复杂性，但提高了土壤吸附模型的预测能力。然而，由于本分析中包含的模型分别仅能预测化合物在土壤和污泥中吸附系数的最大值的71%和67%在相应测量值的一个对数单位范围内，因此需要开发新的模型以更好地预测可电离药物在土壤和污泥系统中的吸附。吸附系数的变化，即使对于单一药物在不同固体类型中的变化，都使得这成为一项本质上困难的任务，因此需要对驱动吸附过程的化学和吸附剂性质有广泛的了解。
