In silico toxicology models and databases as FDA Critical Path Initiative toolkits

Human Genomics

Volumn 5, Issue 3, 2011, Pages 200-207

  Valerio, Luis G ^a  

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

Author keywords

Cardiac safety; Computational toxicology; Drug safety; Genotoxicity; In silico methods; In silico toxicology; QSAR; SAR

Indexed keywords

BIOLOGY; CHEMICAL MODEL; DRUG INDUSTRY; FACTUAL DATABASE; FOOD AND DRUG ADMINISTRATION; HUMAN; METHODOLOGY; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; RISK MANAGEMENT; TOXICOLOGY; UNITED STATES;

COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; DRUG INDUSTRY; HUMANS; MODELS, CHEMICAL; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; RISK MANAGEMENT; TOXICOLOGY; UNITED STATES; UNITED STATES FOOD AND DRUG ADMINISTRATION;

EID: 79961119877     PISSN: 14739542     EISSN: 14797364     Source Type: Journal    
DOI: 10.1186/1479-7364-5-3-200     Document Type: Review

References (37)

1. EU (2006), 'Regulation (EC) No 1907/2006 of The European Parliament and of the Council concerning the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), establishing a European Chemicals Agency, amending Directive 1999/45/EC and repealing Council Regulation (EEC) No 793/93 and Commission Regulation (EC) No 1488/94, as well as Council Directive 76/769/EEC and Commission Directives 91/155/EEC, 93/67/EEC, 93/105/EC and 2000/21/EC', OJEU Vol. L396 (EC 1907/2006), pp. 1-843.
2. NRC (2007), Toxicity Testing in the 21st Century: A Vision and a Strategy, National Academy Press, Washington, DC.
3. FDA (2010), 'Critical Path Initiative', http://www.fda.gov/ ScienceResearch/SpecialTopics/CriticalPathInitiative/default.htm. US Department of Health and Human Services, Rockville, MD (accessed 15th June, 2010).
4. FDA (2004), 'Challenge and opportunity on the critical path to new medical products', http://www.fda.gov/ScienceResearch/SpecialTopics/ CriticalPathInitiative/CriticalPathOpportunitiesReports/ucm()77262.htm. US Department of Health and Human Services, US Food and Drug Administration, Rockville, MD.
5. Yang, C., Valerio, L.G., Jr. and Arvidson, K.B. (2009), 'Computational toxicology approaches at the US Food and Drug Administration', Altern. Lab. Anim. Vol. 37, pp. 523-531.
6. Valerio, L.G., Jr. (2009), 'In silico toxicology for the pharmaceutical sciences', Toxicol. Appl. Pharmacol. Vol. 241, pp. 356-370.
7. Valerio, L.G., Jr., Arvidson, K.B., Busta, E., Minnier, B.L. et al. (2010), 'Testing computational toxicology models with phytochemicals', Mol. Nutr. Food Res. Vol. 54, pp. 186-194.
8. Valerio, L.G., Jr. (2008), 'Tools for evidence-based toxicology: Computational-based strategies as a viable modality for decision support in chemical safety evaluation and risk assessment', Hum. Exp. Toxicol. Vol. 27, pp. 757-760.
9. Valerio, L.G., Jr., Yang, C., Arvidson, K.B. and Kruhlak, N.L. (2010), 'A structural feature-based computational approach for toxicology predictions', Expert Opin. Drug Metab. Toxicol. Vol. 6, pp. 505-518.
10. Valerio, L.G., Jr., Arvidson, K.B., Busta, E., Minnier, B.L. et al. (2010), 'Testing computational toxicology models with phytochemicals', Mol. Nutr. Food Res. Vol. 54, pp. 186-194.
11. Valerio, L.G., Jr. (2010), 'Computational science in drug metabolism and toxicology' [Editorial], Expert Opin. Drug Metab. Toxicol. Vol. 6, pp. 781-784.
12. Evers, A. and Klebe, G. (2004), 'Successful virtual screening for a submicromolar antagonist of the neurokinin-1 receptor based on a ligand-supported homology model', J. Med. Chem. Vol. 47, pp. 5381-5392. (Pubitemid 39382788)
13. Combes, R.D. (2010), 'Is computational toxicology withering on the vine?', Arch. Toxicol. Vol. 84, pp. 333-336.
14. Johnson, S.R. (2007), 'The trouble with QSAR (or how I learned to stop worrying and embrace fallacy)', J. Chem. Inf. Model. Vol. 48, pp. 25-26. (Pubitemid 351271047)
15. Greene, N. and Naven, R. (2009), 'Early toxicity screening strategies', Curr. Opin. Drug Discov. Devel. Vol. 12, pp. 90-97.
16. Merlot, C. (2010), 'Computational toxicology - A tool for early safety evaluation', Drug Discov. Today Vol. 15, pp. 16-22.
17. Boyer, S. (2010), 'The use of computer models in pharmaceutical safety evaluation', Altern. Lab. Anim. Vol. 37, pp. 467-475.
18. FDA (2008), Draft guidance for industry: Genotoxic and carcinogenic impurities in drug substances and products: Recommended approaches, US FDA/CDER, US Department of Health and Human Services, Silver Spring, MD.
19. Naven, R.T., Louise-May, S. and Greene, N. (2010), 'The computational prediction of genotoxicity', Expert Opin. Drug Metab. Toxicol. Vol. 6, pp. 797-807.
20. Benigni, R., Bossa, C., Tcheremenskaia, O. and Giuliani, A. (2010), 'Alternatives to the carcinogenicity bioassay: In silico methods, and the in vitro and in vivo mutagenicity assays', Expert Opin. Drug Metab. Toxicol. Vol. 6, pp. 809-819.
21. Benigni, R. and Bossa, C. (2008), 'Predictivity and reliability of QSAR models: The case of mutagens and carcinogens', Toxicol. Mech. Methods Vol. 18, pp. 137-147. (Pubitemid 351414963)
22. Lee, N., Authier, S., Pugsley, M.K. and Curtis, M.J. (2010), 'The continuing evolution of torsades de pointes liability testing methods: Is there an end in sight?', Toxicol. Appl. Pharmacol. Vol. 243, pp. 146-153.
23. Roden, D.M. (2004), 'Drug-induced prolongation of the QT interval', N. Engl. J. Med. Vol. 350, pp. 1013-1022. (Pubitemid 38269278)
24. Piccini, J.P., Whellan, D.J., Berridge, B.R., Finkle, J.K. et al. (2009), 'Current challenges in the evaluation of cardiac safety during drug development: Translational medicine meets the Critical Path Initiative', Am. Heart J. Vol. 158, pp. 317-326.
25. FDA (2005), International Conference on Harmonisation: Guidance on E14 clinical evaluation of QT/QTc interval prolongation and proarrhythmic potential for non-antiarrhythmic drugs; availability. Notice. Department of Health and Human Services Vol. 70, pp. 61134-61135.
26. Cavero, I. and Crumb, W. (2005), 'ICH S7B draft guideline on the non-clinical strategy for testing delayed cardiac repolarisation risk of drugs: A critical analysis', Expert Opin. Drug Saf. Vol. 4, pp. 509-530. (Pubitemid 40723724)
27. Cartwright, M.E., Petruska, J., Arezzo, J., Frank, D. et al. (2009), 'Phospholipidosis in neurons caused by posaconazole, without evidence for functional neurologic effects', Toxicol. Pathol. Vol. 37, pp. 902-910.
28. Kruhlak, N.L., Choi, S.S., Contrera, J.F., Weaver, J.L. et al. (2008), 'Development of a phospholipidosis database and predictive quantitative structure-activity relationship (QSAR) models', Toxicol. Mech. Methods Vol. 18, pp. 217-227. (Pubitemid 351414975)
29. FDA (2010), 'The regulatory challenges of drug-induced phospholipidosis', http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/ Drugs/AdvisoryCommitteeforPharmaceuticalScienceandClinicalPharmacology/ UCM210798.pdf. Department of Health and Human Services, Bethesda, MD (accessed 14th June, 2010).
30. NAMS. The North American Menopause Society web page (2010), 'Hormone therapy statistics', http://www.menopause.org/hormone-therapystats.aspx. NAMS, Mayfield Heights, OH (accessed 15th May, 2010).
31. Kurzer, M.S. and Xu, X. (1997), 'Dietary phytoestrogens', Ann. Rev. Nutr. Vol. 17, pp. 353-381. (Pubitemid 27328805)
32. Liu, J., Burdette, J.E., Xu, H., Gu, C. et al. (2001), 'Evaluation of estrogenic activity of plant extracts for the potential treatment of menopausal symptoms', J. Agric. Food Chem. Vol. 49, pp. 2472-2479. (Pubitemid 32843277)
33. Lieberman, S. (1998), 'A review of the effectiveness of Cimicifuga racemosa (black cohosh) for the symptoms of menopause', J. Women's Health Vol. 7, pp. 525-529.
34. Mahady, G.B., Dog, T.L., Barrett, M.L., Chavez, M.L. et al. (2008), 'United States Pharmacopeia review of the black cohosh case reports of hepatotoxicity', Menopause Vol. 15, pp. 628-638.
35. Betz, J., Anderson, L., Avigan, M.I., Barnes, J. et al. (2009), 'Black cohosh. Considerations of safety and benefit', Nutr. Today Vol. 44, pp. 155-162.
36. Wang, W.J., Dou, J., Cross, K.P. and Valerio, L.G., Jr. (2011), 'Computational analysis for hepatic safety signals of constituents present in botanical extracts widely used by women in the United States for treatment of menopausal symptoms', Reg. Toxicol. Pharmacol. Vol. 59, pp. 111-124.
37. Valerio, L.G., Jr. (2010), 'The in silico prediction of human-specific metabolites from hepatotoxic drugs', Curr. Drug Discov. Technol. Vol. 7, pp. 170-187.