Computational Tools for Regulatory Needs

Computational Toxicology: Risk Assessment for Pharmaceutical and Environmental Chemicals

Volumn , Issue , 2006, Pages 751-775

  Bassan, Arianna ^a   Worth, Andrew P ^a  

^a JOINT RESEARCH CENTRE   (Italy)

Author keywords

Computational tools for regulatory needs; Decision support system (DSS) for nontesting strategies; Toxicity prediction in regulatory assessment

Indexed keywords

EID: 38849104363     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470145890.ch27     Document Type: Chapter

References (46)

1. Schultz TW, Cronin MTD, Walker JD, Aptula AO. Quantitative structure-activity relationships (QSARs) in toxicology: A historical perspective. J Mol Struct (Theo-chem) 2003;622:1-22.
2. Worth AP. The tiered approach to toxicity assessment based on the integrated use of alternative (non-animal) tests. In: Cronin MTD, Livingstone DJ, editors, Predicting chemical toxicity and fate. Boca Raton, FL: CRC Press, 2004. p. 391-412.
3. Dearden J. In silico prediction of drug toxicity. J Comput Aided Mol De 2003;17: 119-27.
4. Dearden JC, Barratt MD, Benigni R, Bristol DW, Combes RD, Cronin MTD, Judson PM, Payne MP, Richard AM, Tichy M, Worth AP, Yourick JJ. The development and validation of expert systems for predicting toxicity. The report and recommendations of an ECVAM/ECB workshop (ECVAM workshop 24). ATLA 1997;25:223-52.
5. Rosenkranz HS, Cunningham AR. Chemical categories for health hazard identification: A feasibility study. Regul Toxicol Pharm 2001;33:313-18.
6. OECD. Section 3.2 of the OECD Manual for Investigation of HPV Chemicals: Chapter of guidance document on the formation and use of chemical categories. 2005. Available at: .
7. Cronin MTD. Predicting chemical toxicity and fate in human and the environment-an introduction. In: Cronin MTD, Livingstone DJ, editors, Predicting chemical toxicity and fate. Boca Raton, FL: CRC Press, 2004. p. 3-13.
8. European Commission. Council Directive 86/609/EEC of 24 November 1986 on the approximation of laws, regulations and administrative provisions of the member states regarding the protection of animals used for experimental and other scientific purposes. Off J Eur Commun 1986;L358:1-29, 18 Nov 1986.
9. Cronin MTD. The use by governmental regulatory agencies of quantitative structure-activity relationships and expert systems to predict toxicity. In: Cronin MTD, Livingstone DJ, editors, Predicting chemical toxicity and fate. Boca Raton, FL: CRC Press, 2004. p. 414-27.
10. Worth AP, Bassan A, de Bruijn J, Gallegos Saliner A, Netzeva TI, Patlewicz G, Pavan M, Tsakovska I, Eisenreich S. The role of the European Chemicals Bureau in promoting the regulatory use of (Q)SAR methods. SAR QSAR Environ Res 2007;18:111-25.
11. Walker JD, Carlsen L, Hulzebos E, Simon-Hettich B. Global government applications of analogues, SARs, and QSARs to predict aquatic toxicity, chemicals or physical properties, environmental fate parameters and health effects of organic chemicals. SAR QSAR Environ Res 2002;13:607-16.
12. Cronin MTD, Walker JD, Jaworska JS, Comber MHI, Watts CD, Worth AP. Use of QSARs in international decision-making frameworks to predict ecologic effects and environmental fate of chemical substances. Environ Health Perspect 2003;111:1376-90.
13. Cronin MTD, Walker JD, Jaworska JS, Comber MHI, Watts CD, Worth AP. Use of QSARs in international decision-making frameworks to predict health effects of chemical substances. Environ Health Perspect 2003;111:1391-401.
14. Walker JD. Applications of QSAR in toxicology: A US government perspective. J Mol Struct (Theochem) 2003;622:167-84.
15. OECD. Report on the regulatory uses and applications in OECD member countries of (quantitative) structure-activity relationship [(Q)SAR] models in the assessment of new and existing chemicals. Paris: Organisation of Economic Cooperation and Development, 2006. Available at: .
16. European Commission. Proposal for a Regulation of the European Parliament and of the Council concerning the registration, evaluation, authorisation and restriction of chemicals (REACH), establishing a European Chemicals Agency and amending Directive 1999/45/EC and regulation (EC) {on persistent organic pollutants}. Proposal for a Directive of the European Parliament and of the Council amending Council Directive 67/548/EEC in order to adapt it to Regulation (EC) of the European Parliament and of the Council concerning the registration, evaluation, authorisation and restriction of chemicals. Brussels, Belgium. 29 Oct 2003. Available at: .
17. Worth AP, Cronin MTD, Van Leeuwen, CJ. A framework for promoting the acceptance and regulatory use of (Quantitative) structure activity relationships. In: Cronin MTD, Livingstone DJ, editors, Predicting chemical toxicity and fate. Boca Raton, FL: CRC Press, 2004. p. 429-40.
18. Turban E, Aronson RH. Decision support systems and intelligent systems, 5th edition. Upper Saddle River, NJ: Prentice Hall, 1997.
19. Alter S. Decision support systems: Current practice and continuing challenges. Reading, MA: Addison-Wesley, 1980.
20. Holsapple CW, Whinston AB. Decision support systems: A knowledge based approach. Minneapolis: West, 1996.
21. Elsevier MDL CTFile Formats (MDL mol and SD file format) downloadable documentation on .
22. Weininger D. SMILES, a chemical language and information system: 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci 1988;28:31-6.
23. IUPAC Web site describing the IUPAC Chemical Identifier (InChI): .
24. Richard AM, Swirsky GL, Nicklaus MC. Chemical structure indexing of toxicity data on the Internet: Moving toward a flat world. Curr Opin Drug Discov Devel 2006;9:314-25.
25. Weininger D, Weininger A, Weininger JL. SMILES: 2. Algorithm for generation of unique SMI LES notation. J Chem Inf Comput Sci 1989;29:97-101.
26. Gallegos Saliner A. Mini-review on chemical similarity and prediction of toxicity. Curr Comput Aided Drug Des 2006;2:105-22.
27. Flower DR. On the properties of bit string-based measures of chemical similarity. J Chem Inf Comput Sci 1998;38:379-86.
28. Kaiser KLE. Toxicity data sources. In: Cronin MTD, Livingstone DJ, editors, Predicting chemical toxicity and fate. Boca Raton, FL: CRC Press, 2004. p. 17429.
29. The QSAR and Modelling Society maintains an extensive list of databases that can be accessed through their Web site: .
30. The European Chemicals Bureau publishes a list of databases on the Web dedicated to computational toxicology: .
31. Yang C, Benz RD, Cheeseman MA. Landscape of current toxicity databases and database standards, Curr Opin Drug Discov Devel 2006;9:124-33.
32. Worth AP, Bassan A, Gallegos A, Netzeva TI, Patlewicz G, Pavan M, Tsakovska I, Vracko M. The characterisation of (quantitative) structure-activity relationships: Preliminary guidance. 2005; JRC report EUR 21866 EN. European Chemicals Bureau, Ispra (Italy). Available at: .
33. QSAR Model Reporting Formats can be downloaded from European Chemicals Bureau Web site: .
34. Klimisch HJ, Andreae M, Tillmann U. Systematic approach for evaluating the quality of experimental toxicological and ecotoxicological data. Regul Toxicol Pharm 1997;25:1-5.
35. Johnson M, Maggiora GM. Concepts and applications of molecular similarity. New York: Wiley, 1990. "
36. Walters WP, Stahl MT, Murcko MA. Virtual screening-An overview. Drug Discov Today 1998;3:160-78.
37. Todeschini R, Consonni V. Handbook of molecular descriptors. Weinheim: Wiley-VCH, 2000.
38. Jaccard P. Étude comparative de la distribution florale dans une portion des Alpes et des Jura. Bull. Soc Vaudoise Sci Nat 1901;37:547-79.
39. Hodgkin EE, Richards GW. Molecular similarity based on electrostatic potential and electric field. Int J Quant Chem Quant Biol Symp 1987;14:105-10.
40. Good AC, Hodgkin EE, Richards GW. Utilization of Gaussian functions for the rapid evaluation of molecular similarity. J Chem Inf Comput Sci 1992;32:188-91.
41. Jaworska J, Nikolova-Jeliazkova N, Aldenberg T. QSAR applicability domain estimation by projection of the training set in descriptor space: a review. ATLA 2005;33:445-59.
42. Verhaar HJM, van Leeuwen CJ, Hermens JLM. Classifying environmental pollutants: Structure-activity relationships for prediction of aquatic toxicity. Chemo-sphere 1992;25:471-91.
43. Toxtree. Software developed by Dr Nina Jeliazkova (Ideaconsult Ltd; contact nina@acad.bg) on behalf of the European Chemicals Bureau (ECB). Copyright European Communities (2005). Available at: .
44. Cramer GM, Ford RA, Hall RL. Estimation of toxic hazard-A decision tree approach. J Cosmet Toxicol 1978;16:255-76.
45. Russom CL, Anderson EB, Greenwood BE, Pilli A. ASTER: An integration of AQUIRE data base and the QSAR system for use in ecological risk assessments. Sci Total Environ 1991;109-10:667-70.
46. Worth AP, Netzeva T, Patlewicz GY. Predicting toxicological and ecotoxicological endpoints. In: Van Leeuwen VJ, Vermeire T, editors, Risk assessment of chemicals: An introduction, 2nd edition. Berlin: Springer-Verlag, 2007.