Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity

被引：32

作者：

Ahlberg, Ernst ^{[1
]}

Amberg, Alexander ^{[2
]}

Beilke, Lisa D. ^{[3
]}

Bower, David ^{[4
]}

Cross, Kevin P. ^{[4
]}

Custer, Laura ^{[5
]}

Ford, Kevin A. ^{[6
]}

Van Gompel, Jacky ^{[7
]}

Harvey, James ^{[8
]}

Honma, Masamitsu ^{[9
]}

Jolly, Robert ^{[10
]}

Joossens, Elisabeth ^{[11
]}

Kemper, Raymond A. ^{[12
]}

Kenyon, Michelle ^{[13
]}

Kruhlak, Naomi ^{[14
]}

Kuhnke, Lara ^{[15
]}

Leavitt, Penny

Naven, Russell ^{[14
,18
]}

Neilan, Claire ^{[16
,19
]}

Quigley, Donald P.

Shuey, Dana ^{[16
]}

Spirkl, Hans-Peter

Stavitskaya, Lidiya

Teasdale, Andrew ^{[17
]}

White, Angela ^{[8
]}

Wichard, Joerg ^{[15
]}

Zwickl, Craig ^{[10
]}

Myatt, Glenn J. ^{[4
]}

机构：

[1] AstraZeneca, Molndal, Sweden

[2] Sanofi Aventis Deutschland GmbH, Frankfurt, Germany

[3] Toxicol Solut, San Diego, CA USA

[4] Leadscope, Columbus, OH USA

[5] Bristol Myers Squibb Co, New Brunswick, NJ USA

[6] Genentech Inc, San Francisco, CA USA

[7] Janssen Res & Dev, Beerse, Belgium

[8] GlaxoSmithKline, Ware, Herts, England

[9] Natl Inst Hlth Sci, Tokyo, Japan

[10] Eli Lilly & Co, Indianapolis, IN 46285 USA

[11] European Commiss, Joint Res Ctr, Ispra, Italy

[12] Vertex, Boston, MA USA

[13] Pfizer, Groton, CT USA

[14] US FDA, Ctr Drug Evaluat & Res, Silver Spring, MD USA

[15] Bayer HealthCare, Berlin, Germany

[16] Incyte Corp, Wilmington, DE USA

[17] AstraZeneca, Macclesfield, Cheshire, England

[18] Takeda, Cambridge, MA USA

[19] Gilead, Foster City, CA USA

来源：

REGULATORY TOXICOLOGY AND PHARMACOLOGY | 2016年 / 77卷

关键词：

ICH M7; Pharmaceutical impurities; Mutagenicity; (Q)SAR; Aromatic amines; SAR fingerprint; DISCRIMINATING STRUCTURAL FEATURES; GENETIC TOXICITY; BUILDING-BLOCKS; NITRENIUM IONS; DNA-BINDING; AMES TEST; CARCINOGENS; POTENCY; MODELS; QSAR;

D O I：

10.1016/j.yrtph.2016.02.003

中图分类号：

DF [法律]; D9 [法律]; R [医药、卫生];

学科分类号：

0301 ; 10 ;

摘要：

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (OJSAR 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. (C) 2016 Elsevier Inc. All rights reserved.

引用

页码：1 / 12

页数：12

共 40 条

[1] CHEMICAL-STRUCTURE, SALMONELLA MUTAGENICITY AND EXTENT OF CARCINOGENICITY AS INDICATORS OF GENOTOXIC CARCINOGENESIS AMONG 222 CHEMICALS TESTED IN RODENTS BY THE UNITED-STATES NCI/NTP [J].