Arguments for Considering Uncertainty in QSAR Predictions in Hazard and Risk Assessments

被引:11
作者
Sahlin, Ullrika [1 ,2 ]
Golsteijn, Laura [3 ]
Iqbal, M. Sarfraz [1 ]
Peijnenburg, Willie [4 ,5 ]
机构
[1] Linnaeus Univ, Sch Nat Sci, Kalmar, Sweden
[2] Lund Univ, Ctr Environm & Climate Res, SE-22362 Lund, Sweden
[3] Radboud Univ Nijmegen, Inst Water & Wetland Res, Dept Environm Sci, NL-6525 ED Nijmegen, Netherlands
[4] RIVM, Lab Ecol Risk Assessment, Bilthoven, Netherlands
[5] Leiden Univ, Inst Environm Sci, Leiden, Netherlands
来源
ATLA-ALTERNATIVES TO LABORATORY ANIMALS | 2013年 / 41卷 / 01期
关键词
decision-making; non-testing information; probabilistic risk assessment; uncertainty analysis;
D O I
10.1177/026119291304100110
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Chemical regulation allows non-in vivo testing (i.e. in silico-derived and in vitro-derived) information to replace experimental values from in vivo studies in hazard and risk assessments. Although non-in vitro testing information on chemical activities or properties is subject to added uncertainty as compared to in vivo testing information, this uncertainty is commonly not (fully) taken into account. Considering uncertainty in predictions from quantitative structure-activity relationships (QSARs), which are a form of non-in vivo testing information, may improve the way that QSARs support chemical safety assessment under the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) system. We argue that it is useful to consider uncertainty in QSAR predictions, as it: a) supports rational decision-making; b) facilitates cautious risk management; c) informs uncertainty analysis in probabilistic risk assessment; d) may aid the evaluation of QSAR predictions in weight-of-evidence approaches; and e) provides a probabilistic model to verify the experimental data used in risk assessment. The discussion is illustrated by using case studies of QSAR integrated hazard and risk assessment from the EU-financed CADASTER project.
引用
收藏
页码:91 / 110
页数:20
相关论文
共 1 条
[1]   Evaluation of CADASTER QSAR Models for the Aquatic Toxicity of (Benzo)triazoles and Prioritisation by Consensus Prediction [J].
Cassani, Stefano ;
Kovarich, Simona ;
Papa, Ester ;
Roy, Partha Pratim ;
Rahmberg, Magnus ;
Nilsson, Sara ;
Sahlin, Ullrika ;
Jeliazkova, Nina ;
Kochev, Nikolay ;
Pukalov, Ognyan ;
Tetko, Igor V. ;
Brandmaier, Stefan ;
Durjava, Mojca Kos ;
Kolar, Boris ;
Peijnenburg, Willie ;
Gramatica, Paola .
ATLA-ALTERNATIVES TO LABORATORY ANIMALS, 2013, 41 (01) :49-64