Aubakirova Bakhyt, Beisenova Raikhan, Boxall Alistair Ba
LN Gumilyov Eurasian National University, Astana, Kazakhstan.
Environment Department, University of York, Heslington, York, United Kingdom.
Integr Environ Assess Manag. 2017 Sep;13(5):832-839. doi: 10.1002/ieam.1895. Epub 2017 Mar 24.
Over the last 20 years, there has been increasing interest in the occurrence, fate, effects, and risk of pharmaceuticals in the natural environment. However, we still have only limited or no data on ecotoxicological risks of many of the active pharmaceutical ingredients (APIs) currently in use. This is partly due to the fact that the environmental assessment of an API is an expensive, time-consuming, and complicated process. Prioritization methodologies, which aim to identify APIs of most concern in a particular situation, could therefore be invaluable in focusing experimental work on APIs that really matter. The majority of approaches for prioritizing APIs require annual pharmaceutical usage data. These methods cannot therefore be applied to countries, such as Kazakhstan, that have very limited data on API usage. The present paper therefore offers an approach for prioritizing APIs in surface waters in information-poor regions such as Kazakhstan. Initially data were collected on the number of products and active ingredients for different therapeutic classes in use in Kazakhstan and on the typical doses. These data were then used alongside simple exposure modeling approaches to estimate exposure indices for active ingredients (about 240 APIs) in surface waters in the country. Ecotoxicological effects data were obtained from the literature or predicted. Risk quotients were then calculated for each pharmaceutical based on the exposure and the substances were ranked in order of risk quotient. Highest exposure indices were obtained for benzylpenicillin, metronidazole, sulbactam, ceftriaxone, and sulfamethoxazole. The highest risk was estimated for amoxicillin, clarithromycin, azithromycin, ketoconazole, and benzylpenicillin. In the future, the approach could be employed in other regions where usage information is limited. Integr Environ Assess Manag 2017;13:832-839. © 2017 SETAC.
在过去20年里,人们对药物在自然环境中的出现、归宿、影响和风险越来越感兴趣。然而,对于目前许多正在使用的活性药物成分(API)的生态毒理学风险,我们仍然只有有限的数据或根本没有数据。部分原因在于,对一种API进行环境评估是一个昂贵、耗时且复杂的过程。因此,旨在确定特定情况下最值得关注的API的优先排序方法,对于将实验工作聚焦于真正重要的API可能非常宝贵。大多数对API进行优先排序的方法都需要年度药物使用数据。因此,这些方法无法应用于像哈萨克斯坦这样API使用数据非常有限的国家。因此,本文提供了一种在像哈萨克斯坦这样信息匮乏地区对地表水中的API进行优先排序的方法。首先收集了哈萨克斯坦正在使用的不同治疗类别的产品数量和活性成分以及典型剂量的数据。然后将这些数据与简单的暴露建模方法一起用于估计该国地表水中活性成分(约240种API)的暴露指数。生态毒理学效应数据从文献中获取或进行预测。然后根据暴露情况为每种药物计算风险商数,并根据风险商数对物质进行排序。苄青霉素、甲硝唑、舒巴坦、头孢曲松和磺胺甲恶唑的暴露指数最高。阿莫西林、克拉霉素、阿奇霉素、酮康唑和苄青霉素的风险估计最高。未来,该方法可应用于其他使用信息有限的地区。《综合环境评估与管理》2017年;13:832 - 839。© 2017 SETAC。