Using toxicological evidence from QSAR models in practice
Author(s) -
Emilio Benfenati
Publication year - 2013
Publication title -
altex
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.975
H-Index - 51
eISSN - 1868-8551
pISSN - 1868-596X
DOI - 10.14573/altex.2013.1.019
Subject(s) - quantitative structure–activity relationship , documentation , reliability (semiconductor) , computer science , process (computing) , bioconcentration , chemistry , machine learning , environmental chemistry , bioaccumulation , power (physics) , physics , quantum mechanics , programming language , operating system
Leading QSAR models provide supporting documentation in addition to a predicted toxicological value. Such information enables the toxicologist to explore the properties of chemical substances as well as to review and to increase the reliability of toxicity predictions. This article focuses on the use of this information in practice. We explore the supporting documentation provided by the EPISuite, T.E.S.T. and VEGA platforms when evaluating the bioconcentration factor (BCF) of three example compounds. Each compound presents a different challenge: to recognize high reliability, analyze complex evidence of reliability, and recognize uncertainty. In each case, we first describe and discuss the supporting documentation provided by the QSAR platforms. We then discuss the judgments on reliability across sectors from 28 toxicologists who used this supporting information and commented on the process. The article demonstrates both the use of QSAR models as tools to reduce or replace in vivo testing, and the need for scientific expertise and rigor in their use.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom