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Supporting Literature Citations

1. Sutter, A., Amberg, A., Boyer, S., Brigo, A., Contrera, J.F., Custer, L.L., Dobo, K.L., Gervais, V., Gloienke, S., van Gompel, J., Greene, N., Muster, W., Nicolette, J., Reddy, M., Thybaud, V., Vock, E., White, A.T., and Muller, L. Use of in silico systems and expert knowledge for structure-based assessment of potentially mutagenic impurities. Regul. Toxicol. Pharmacol. (2013) 67(1): 39-52.

2. Jacobson-Kram, D. Contrera, J.F. Genetic toxicity assessment: Employing the best science for human safety evaluation part I: Early screening for potential human mutagens. Toxicol. Sci. 96 (2007)16-20.

3. Kruhlak, N.L. Contrera, J.F. Benz, R. D., Matthews, E. J. Progress in QSAR toxicity screening of pharmaceutical impurities and other FDA regulated products. Advan. in Drug Deliv. 59 (2007) 43-55.

4. McGovern, T., Jacobson-Kram, D. Regulation of Genotoxic and carcinogenic impurities in drug substances and products. Trends in Anal. Chem. 25 (2006) 790-795.

5. Contrera, J.F., Matthews, E.J., Benz, R.D. Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices. Regul. Toxicol. Pharmacol. 38 (2003) 243-259.

6. Contrera, J.F., Hall, L.H., Kier, L.B., MacLaughlin, P. QSAR modeling of carcinogenic risk using discriminant analysis and topological molecular descriptors. Curr. Drug Discov. Technol., 2 (2005) 55-57.

7. Contrera, J.F., Kruhlak, N.L., Matthews, E. J., Benz, R.D.  Comparison of MC4PC and MDL-QSAR rodent carcinogenicity predictions and the enhancement of predictive performance by combining QSAR models. Regul. Toxicol. Pharmacol. 49 (2007) 172-182.

8. Matthews, E. J., Kruhlak, N.L., Benz, R.D., Contrera, J.F. C.A. Marchant, C. Yang. Combined use of MC4PC, MDL-QSAR, BioEpisteme, Leadscope PDM, and Derek for Windows software to achieve high performance, high confidence, mode of action-based predictions of chemical carcinogenesis in rodents. Toxicology Mech. Methods, 18: (2008) 189 - 206.

9. Contrera, J.F., Matthews, E.J., Kruhlak, N.L., Benz R.D. In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL® QSAR software. Regul. Toxicol. Pharmacol. 43 (2005) 313-323.

10. Contrera, J.F., Matthews, E.J., Kruhlak, N.L., Benz R.D. In silico screening of chemicals for genetic toxicity using MDL-QSAR, non-parametricric discriminant analysis, E-state, connectivity and molecular property descriptors. Toxicology Mech. Methods, 18 (2008) 207- 216.

11. Muller et al., A rationale for determining, testing, and controlling specific impurities in pharmaceuticals that possess potential for genotoxicity. Regul. Toxicol. Pharmacol. 44 (2006) 198-211.

12. Dobo, K.L., Greene, N., Cyr, M.O., Caron, S., Ku, W.W., 2006. The application of structure-based assessment to support safety and chemistry diligence to manage genotoxic impurities in active pharmaceutical ingredients during drug development. Regul. Toxicol. Pharmacol.(2006) 44(3), 282-93.

13. Contrera, J. F. Validation of Toxtree and SciQSAR in silico predictive software using a publicly available benchmark mutagenicity database and their applicability for the qualification of impurities in pharmaceuticals. Regul. Toxicol. Pharmacol. 67 (2013) 285-293.

14. Valerio, L. G. and Cross, K.P. Characterization and validation of an in silico toxicology model to predict the mutagenic potential of drug impurities. Toxicol. Applied Pharmacol. 260 (2012), 209-221.

15. Benchmarking assessment of open source and newly released Salmonella mutagenicity (Q)SAR models for potential use under ICH M7. Stavitskaya, L., et al., Poster abstract # 2273b, Society of Toxicology Annual Meeting, Phoenix, AZ. (2014). (FDA presentation)