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Integrating QSAR and read-across for environmental assessment
被引:9
|作者:
Benfenati, E.
[1
]
Roncaglioni, A.
[1
]
Petoumenou, M. I.
[1
]
Cappelli, C. I.
[1
]
Gini, G.
[2
]
机构:
[1] IRCCS, Ist Ric Farmacol Mario Negri, Milan, Italy
[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy
关键词:
read-across;
BCF;
REACH;
QSAR;
log P;
BIOCONCENTRATION FACTOR BCF;
CHEMICALS;
MODELS;
D O I:
10.1080/1062936X.2015.1078408
中图分类号:
O6 [化学];
学科分类号:
0703 ;
摘要:
Read-across and QSAR have different traditions and drawbacks. We address here two main questions: (1) How do we solve the issue of the subjectivity in the evaluation of data and results, which may be particularly critical for read-across, but may have a role also for the QSAR assessment? (2) How do we take advantage of the results of both approaches to support each other? The QSAR model starts from the training set. The presence of similar chemicals with property values close to that predicted can support the result. The approach in read-across is the opposite. The assessment is focused on the few substances similar to the target. The data quality of the similar chemicals is fundamental. A risk is poor standardization in the definition of similarity', because different approaches may be applied. Inspired by the principles of high transparency and reproducibility, a new program for read-across, called ToxRead, has been developed and made freely available (www.toxgate.eu). The output of ToxRead can be compared and integrated with the output of QSAR, within a weight-of-evidence strategy. We discuss the evaluation and integration of ToxRead and QSAR with examples of the assessment of bioconcentration factors of chemicals.
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页码:605 / 618
页数:14
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