Title: Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity
Authors: AHLBERG ErnstAMBERG AlexanderBEILKE Lisa D.BOWER DavidCROSS Kevin P.CUSTER LauraFORD Kevin A.VAN GOMPEL JackyHARVEY JamesHONMA MasamistuJOLLY RobertJOOSSENS ELISABETHKEMPER RayKENYON MichelleKRUHLAK NaomiKUHNKE LaraLEAVITT PennyNAVEN RussellNEILAN ClaireQUIGLEY Donald P.SHUEY DanaSPIRKL Hans-PeterSTAVITSKAYA LidiyaTEASDALE AndrewWHITE AngelaWICHARD JoergZWICKL CraigMYATT Glenn
Citation: REGULATORY TOXICOLOGY AND PHARMACOLOGY vol. 77 p. 1-12
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE
Publication Year: 2016
JRC N°: JRC97330
ISSN: 0273-2300
URI: http://www.sciencedirect.com/science/article/pii/S0273230016300265
http://publications.jrc.ec.europa.eu/repository/handle/JRC97330
DOI: 10.1016/j.yrtph.2016.02.003
Type: Articles in periodicals and books
Abstract: Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscope's expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated.
JRC Directorate:Institute for Health and Consumer Protection Historical Collection

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.