Dourson M L, Felter S P, Robinson D
Toxicology Excellence for Risk Assessment (TERA), Cincinnati, Ohio 45223, USA.
Regul Toxicol Pharmacol. 1996 Oct;24(2 Pt 1):108-20. doi: 10.1006/rtph.1996.0116.
The science behind the use of uncertainty factors has progressed considerably. Increased knowledge of inter- and intraspecies sensitivity, mechanisms of action, and detailed evaluation of data bases can support the use of data-derived uncertainty factors, which ultimately results in a risk assessment with greater confidence. Papers that highlight available data for each of several areas of uncertainty are discussed, indicating that choice of the appropriate factor requires scientific judgement on a case-by-case basis. Case studies from EPA and Health Canada risk values illustrate the use of data in chemical specific risk assessments to support the selection of uncertainty factors other than the default value of 10-fold. In the case studies, the types of data that have been used to support a change in the default value are explicitly reviewed, as well as why the data support a different uncertainty factor, how the uncertainty was reduced, and what assumptions have been satisfied or replaced. Incorporation of all available scientific data into the risk assessment process fosters increased research and ultimately reduces uncertainty. The results of this review support the use of data-derived uncertainty factors when appropriate scientific data are available.
使用不确定性因素背后的科学已经取得了长足的进步。对种间和种内敏感性、作用机制的了解不断增加，以及对数据库的详细评估，都能支持使用源自数据的不确定性因素，这最终会带来更具可信度的风险评估。文中讨论了突出几个不确定性领域各自可用数据的论文，表明选择合适的因素需要根据具体情况进行科学判断。美国环境保护局（EPA）和加拿大卫生部风险值的案例研究说明了在化学品特定风险评估中使用数据来支持选择不同于默认值10倍的不确定性因素。在案例研究中，明确审查了用于支持改变默认值的数据类型，以及数据为何支持不同的不确定性因素、不确定性是如何降低的，以及满足或取代了哪些假设。将所有可用的科学数据纳入风险评估过程，有助于增加研究并最终减少不确定性。本综述的结果支持在有适当科学数据时使用源自数据的不确定性因素。
