(Q)SAR modeling and safety assessment in regulatory review

Clinical Pharmacology and Therapeutics

Volumn 91, Issue 3, 2012, Pages 529-534

  Kruhlak, N L ^a   Benz, R D ^a   Zhou, H ^a   Colatsky, T J ^a  

^a CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DRUG INDUSTRY; DRUG STRUCTURE; FOOD AND DRUG ADMINISTRATION; PHYSICAL CHEMISTRY; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; RISK ASSESSMENT;

DECISION MAKING; DRUG AND NARCOTIC CONTROL; DRUG INDUSTRY; DRUG TOXICITY; HUMANS; MODELS, THEORETICAL; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RISK ASSESSMENT;

EID: 84862777215     PISSN: 00099236     EISSN: 15326535     Source Type: Journal    
DOI: 10.1038/clpt.2011.300     Document Type: Review

References (36)

1. Myint, K.Z. & Xie, X.Q. Recent advances in fragment-based QSAR and multidimensional QSAR methods. Int. J. Mol. Sci. 11, 3846-3866 (2010).
2. Johnson, M.A. & Maggiora, G.M. Concepts and Applications of Molecular Similarity (Wiley, New York, 1990).
3. C ronin, M.T. The current status and future applicability of quantitative structure-activity relationships (QSARs) in predicting toxicity. Altern. Lab. Anim. 30 (suppl. 2), 81-84 (2002). (Pubitemid 36168717)
4. Selassie, C.D. History of quantitative structure-activity relationships. In Burger's Medicinal Chemistry and Drug Discovery 6th edn., Vol. 1: Drug Discovery (ed. Abraham, D.J.) 1-48 (Hoboken, NJ: Wiley, 2003).
5. 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. Adv. Drug Deliv. Rev. 59, 43-55 (2007). (Pubitemid 46204935)
6. Mahadevan, B. et al. Genetic toxicology in the 21st century: reflections and future directions. Environ. Mol. Mutagen. 52, 339-354 (2011).
7. Perkins, R., Fang, H., Tong, W. & Welsh, W.J. Quantitative structure-activity relationship methods: perspectives on drug discovery and toxicology. Environ. Toxicol. Chem. 22, 1666-1679 (2003). (Pubitemid 37337298)
8. Ashby, J. & Tennant, R.W. Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP. Mutat. Res. 257, 229-306 (1991). (Pubitemid 121007619)
9. Cooper, J.A. 2nd, Saracci, R. & Cole, P. Describing the validity of carcinogen screening tests. Br. J. Cancer 39, 87-89 (1979). (Pubitemid 9094302)
10. Organisation for Economic Co-operation and Development. Guidance document on the validation of (quantitative) structure-activity relationships [(Q)SAR] models. ENV/JM/MONO(2007)2 (2007).
11. Muster, W., Breidenbach, A., Fischer, H., Kirchner, S., Müller, L. & Pähler, A. Computational toxicology in drug development. Drug Discov. Today 13, 303-310 (2008).
12. Muller, L., Breidenbach, A., Funk, C., Muster, W. & Pahler, A. Strategies for using computational toxicology methods in pharmaceutical R&D. In Computational Toxicology-Risk Assessment for Pharmaceutical and Environmental Chemicals (ed. Ekins, S.) 545-579 (Hoboken, NJ: Wiley, 2007).
13. Leeson, P.D. & Springthorpe, B. The influence of drug-like concepts on decisionmaking in medicinal chemistry. Nat. Rev. Drug Discov. 6, 881-890 (2007). (Pubitemid 350042396)
14. US Food and Drug Administration. Center for Drug Evaluation and Research. Guidance for Industry-Genotoxic and Carcinogenic Impurities in Drug Substances and Products: Recommended Approaches (Draft Guidance) (2008).
15. European Medicines Agency. Questions and answers on the "Guideline on the limits of genotoxic impurities." In EMA/CHMP/SWP/431994/2007 Rev. 3. EMA 〈http://www.ema.europa.eu/docs/en-GB/document-library/Scientific- guideline/2009/09/WC500002907.pdf〉 (2010).
16. Benz, R.D. Toxicological and clinical computational analysis and the US FDA/CDER. Expert Opin. Drug Metab. Toxicol. 3, 109-124 (2007). (Pubitemid 47307458)
17. Matthews, E.J. & Contrera, J.F. A new highly specific method for predicting the carcinogenic potential of pharmaceuticals in rodents using enhanced MCA SE QSAR-ES software. Regul. Toxicol. Pharmacol. 28, 242-264 (1998). (Pubitemid 29096166)
18. Contrera, J.F., Matthews, E.J. & Daniel Benz, R. Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices. Regul. Toxicol. Pharmacol. 38, 243-259 (2003). (Pubitemid 37414815)
19. Matthews, E.J., Kruhlak, N.L., Cimino, M.C., Benz, R.D. & Contrera, J.F. An analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: I. Identification of carcinogens using surrogate endpoints. Regul. Toxicol. Pharmacol. 44, 83-96 (2006). (Pubitemid 43234284)
20. Matthews, E.J., Kruhlak, N.L., Cimino, M.C., Benz, R.D. & Contrera, J.F. An analysis of genetic toxicity, reproductive and developmental toxicity, and carcinogenicity data: II. Identification of genotoxicants, reprotoxicants, and carcinogens using in silico methods. Regul. Toxicol. Pharmacol. 44, 97-110 (2006). (Pubitemid 43234285)
21. 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, 313-323 (2005). (Pubitemid 41616397)
22. Contrera, J.F., Matthews, E.J., Kruhlak, N.L. & Benz, R.D. In Silico Screening of Chemicals for Genetic Toxicity Using MDL-QSAR, Nonparametric Discriminant Analysis, E-State, Connectivity, and Molecular Property Descriptors. Toxicol. Mech. Methods 18, 207-216 (2008). (Pubitemid 351414972)
23. Matthews, E.J., Kruhlak, N.L., Daniel Benz, R. & Contrera, J.F. A comprehensive model for reproductive and developmental toxicity hazard identification: I. Development of a weight of evidence QSAR database. Regul. Toxicol. Pharmacol. 47, 115-135 (2007). (Pubitemid 46217819)
24. Matthews, E.J., Kruhlak, N.L., Daniel Benz, R., Ivanov, J., Klopman, G. & Contrera, J.F. A comprehensive model for reproductive and developmental toxicity hazard identification: II. Construction of QSAR models to predict activities of untested chemicals. Regul. Toxicol. Pharmacol. 47, 136-155 (2007). (Pubitemid 46217818)
25. Kruhlak, N.L. et al. Development of a phospholipidosis database and predictive quantitative structure-activity relationship (QSAR) models. Toxicol. Mech. Methods 18, 217-227 (2008). (Pubitemid 351414975)
26. Ursem, C.J., Kruhlak, N.L., Contrera, J.F., MacLaughlin, P.M., Benz, R.D. & Matthews, E.J. Identification of structure-activity relationships for adverse effects of pharmaceuticals in humans. Part A: use of FDA post-market reports to create a database of hepatobiliary and urinary tract toxicities. Regul. Toxicol. Pharmacol. 54, 1-22 (2009).
27. Matthews, E.J. et al. Identification of structure-activity relationships for adverse effects of pharmaceuticals in humans. Part B: use of (Q)SAR systems for early detection of drug-induced hepatobiliary and urinary tract toxicities. Regul. Toxicol. Pharmacol. 54, 23-42 (2009).
28. Matthews, E.J., Kruhlak, N.L., Benz, R.D., Aragonés Sabaté, D., Marchant, C.A. & Contrera, J.F. Identification of structure-activity relationships for adverse effects of pharmaceuticals in humans. Part C: use of QSAR and an expert system for the estimation of the mechanism of action of drug-induced hepatobiliary and urinary tract toxicities. Regul. Toxicol. Pharmacol. 54, 43-65 (2009).
29. Matthews, E.J. & Frid, A.A. Prediction of drug-related cardiac adverse effects in humans-A: creation of a database of effects and identification of factors affecting their occurrence. Regul. Toxicol. Pharmacol. 56, 247-275 (2010).
30. Frid, A.A. & Matthews, E.J. Prediction of drug-related cardiac adverse effects in humans-B: use of QSAR programs for early detection of drug-induced cardiac toxicities. Regul. Toxicol. Pharmacol. 56, 276-289 (2010).
31. Matthews, E.J., Kruhlak, N.L., Benz, R.D. & Contrera, J.F. Assessment of the health effects of chemicals in humans: I. QSAR estimation of the maximum recommended therapeutic dose (MRTD) and no effect level (NOEL) of organic chemicals based on clinical trial data. Curr. Drug Discov. Technol. 1, 61-76 (2004).
32. Contrera, J.F., Matthews, E.J., Kruhlak, N.L. & Benz, R.D. Estimating the safe starting dose in phase I clinical trials and no observed effect level based on QSAR modeling of the human maximum recommended daily dose. Regul. Toxicol. Pharmacol. 40, 185-206 (2004). (Pubitemid 39531301)
33. 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, 16-20 (2007). (Pubitemid 46323204)
34. Matthews, E.J. & Contrera, J.F. In silico approaches to explore toxicity endpoints: issues and concerns for estimating human health effects. Expert Opin. Drug Metabol. Toxicol. 3, 125-134 (2007). (Pubitemid 47307459)
35. 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, 172-182 (2007). (Pubitemid 350103627)
36. Matthews, E.J., Kruhlak, N.L., Benz, R.D., Contrera, J.F., Marchant, C.A. & Yang, C . Combined use of MC4PC, MDL-QSAR, Leadscope PDM, and Derek for Windows software to achieve high-performance, high-confidence, mode of action-based predictions of chemical carcinogenesis in rodents. Toxicol. Mech. Meth. 18, 189-206 (2008). (Pubitemid 351414971)