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The Advisory list for self-classification of dangerous substances

4 References

  1. Regulation (EC) No 1907/2006 of the European Parliament and of the Council of 18 December 2006 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.
     
  2. Council Directive 67/548/EEC on the approximation of the laws, regulations and administrative provisions relating to the classification, packaging and labelling of dangerous substances.
     
  3. EINECS (European Inventory of Existing Commercial Chemical Substances). Official Journal of the European Union (1990). 146A, 15.6.1990
     
  4. Addendum to EINECS (European Inventory of Existing Commercial Chemical Substances). Official Journal of the European Union (2002). C 54/13 01.03.2002, 2002/C54/08
     
  5. The Danish Environmental Protection Agency (2001). Report on the Advisory list for self-classification of dangerous substances. Environmental Project No. 636
     
  6. Council Directive 1999/45/EEC concerning the approximation of the laws, regulations and administrative provisions of the Member States relating to the classification, packaging and labelling of dangerous preparations
     
  7. Regulation (EC) no 1272/2008 of the European Parliament and of the Council on classification, labelling and packaging of substances and mixtures, amending and repealing Directives 67/548/EEC and 1999/45/EC, and amending Regulation (EC) No 1907/2006
     
  8. M-CASE, Users Guide, Version 3.30 (Rev. 1.0), Multicase inc., 25825 Science Drive Park, suite 100, Cleveland, OH, 44122.
     
  9. Guidance for the implementation of REACH - Guidance on information requirements and chemical safety assessment Chapter R.6: (Q)SARs and grouping of chemicals. European Chemicals Agency, 2008
     
  10. Oxford Molecular, Chem-X version July 1998, SMILES to 3D (three dimensional) conversion module
     
  11. J.A. Cooper, R. Saracci and P. Cole, Describing the validity of carcinogen screening tests, British Journal of Cancer, 39 (1979), pp. 87-89.
     
  12. Dimitrov, S., Dimitrova, G., Pavlov, T., Dimitrova, N., Patlewicz, G., Niemelâ, J., and Mekenyan, O. A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models. J. Chem. Inf. Model., Vol. 45 (4), 839 -849, 2005.
     
  13. J.J. Kraker, D.M. Hawkins, S.C. Basak, R. Natarajan, and D. Mills, Quantitative Structure-Activity Relationship ((Q)SAR) modeling of juvenile hormone activity: Comparison of validation procedures, Chemometr. Intell. Lab. Syst. 87 (2007), pp. 33–42.
     
  14. A. Golbraikh, and A. Tropsha, Beware of q2!, J. Mol. Graph. Model. 20 (2002), pp.269-276.
     
  15. R.Benigni, and C.Bossa, Predictivity of (Q)SAR, J. Chem. Inf. Model. 48 (2008), pp.971-980.
     
  16. W.R. Lee, S. Abrahamson, R. Valencia, E.S. von Halle, F.E. Würgler, and S. Zimmering, The sex-linked recessive lethal test for mutagenesis in Drosophila melanogaster. A report of the U.S. Environmental Protection Agency Gene-Tox Program. Mut. Res. 123 (1983), pp.183-279.
     
  17. Hayashi et al. Micronuleus tests in mice on 39 food additives and eight miscellanneous chemicals”, Food Chem. Toxicol. 26 (1988) pp 487-500
     
  18. Mavournin et al. The in vivo micronucleus assay in mammalian bone marrow and peripheral blood”, Report of the US EPA Gene-Tox Program, Mut. Res. 239 (1990) pp. 29-80.
     
  19. Waters et al. The performance of short-term test in identifying potential germ cell mutagens: A quantitative and qualitative analysis”, Mut. Res. 341 (1994) pp. 109-131.
     
  20. Morita et al., ”Evaluation of the rodent micronucleus assay in the screening of IARC carcinogens (Groups 1, 2A and 2B)”, The summary report of the 6th collaborative study by CSGMT/JEMS-MMS, Mut. Res. 389 (1997) pp. 3-122.
     
  21. Green et al., Current status of bioassays in genetic toxicology--the dominant lethal assay. A report of the U.S. Environmental Protection Agency Gene-Tox Program. Mut. Res. 154, 1 (1985) pp. 49-67. Review.
     
  22. J.D. Tucker, A. Auletta, M.C. Cimino, K.L. Dearfield, D. Jacobson-Kram, R.R. Tice, and A.V. Carrano, Sister-chromatid exchange: Second report of the Gene-Tox program. Mut. Res. 297 (1993) pp. 101-180
     
  23. Sasaki et al., Crit. Rev. in Toxicol. 30, 6 (2000) pp. 629-799.
     
  24. J. Matthews and J.F. Contrera. A new highly specific method for predicting the carcinogenic potential of pharmaceuticals in rodent using enhanced MCASE (Q)SAR-ES software. Reg. Toxicol. and Pharmacol. 28 (1998) pp. 242-264.
     
  25. J. Kazius, R. McGuire, and R. Bursi. Derivation and validation of toxicophores for mutagenicity prediction. J. Med. Chem. (2005) 48, pp. 312-320.
     
  26. Rosenkranz,H.S.; Ennever,F.K.; Klopman,G. Relationship between carcinogenicity in rodents and the induction of sister chromatid exchanges and chromosomal aberrations in Chinese hamster ovary cells. Mutagenesis (1990) 5, pp. 559-571.
     
  27. Evaluation of the Setubal Principles for establishing the status of development and validation of (Q)SARs, OECD, Paris. OECD Environment, Health and Safety Publication. Annex 4 pp. 91-110, J.
     
  28. J. Niemela, E. Wedebye (2004), “A ‘global’ Multi-Case model for in vitro chromosomal aberrations in mammalian cells”. OECD Environment Health and Safety Publications, Series on Testing and Assessment, No. 49, OECD, Paris, 113-133in vitro”.
  1. Motoi Ishidata, Jr., "Data book of Chromosomal Aberration Test In Vitro", Biological Research Centre, National Institute of Hygienic Sciences, Japan, Elsevier Life-Science Information Center, New York 1988
     
  2. Ishidata M., Jr. Taken from Sofoni, T. (Ed), "Data Book of Chromosomal Aberration Test In Vitro", LIC. Tokyo, 1998.
     
  3. Grant et al., Mut. Res. 465 (2001), pp. 201-229
     
  4. Ghanooni, M.; Mattison, D. R.; Zhang, , Y. P.; Macina, O. T.; Rosenkranz, H. S., and Klopman, G. Structural determinants associated with risk of human developmental toxicity. Am.J.Obstet.Gynecol. 176, 4 (1997) pp. 799-805.
     
  5. Lee, W.R.; Abrahamson, S.; R. Valencia, E.S. von Halle, F.E. Würgler, and S. Zimmering, The sex-linked recessive lethal test for mutagenesis in Drosophila melanogaster. A report of the U.S. Environmental Protection Agency Gene-Tox Program. Mut. Res. 123 (1983), pp.183-279.
     
  6. Green, S.; A. Auletta, J. Fabricant, R. Kapp, M. Manandhar, C-j. Sheu, J. Springer, and B. Whitfield, Current status of bioassays in genetic toxicology – the dominant lethal assay. Part of the U.S. Environmental Protection Agency Gene-Tox Program. Mut. Res. 154 (1985), pp. 49-67.
     
  7. G. E. Jensen; J. R. Niemelä; E. B. Wedebye; N. G. Nikolov (2008) QSAR models for reproductive toxicity and endocrine disruption in regulatory use - a preliminary investigation. SAR and QSAR in Environmental Research, 19 (7&8) 631-641.
     
  8. (Q)SAR Model Reporting Format Inventory, European Commission, Joint Research Centre (JRC), http://qsardb.jrc.it/qmrf/
     
  9. Allanou, R., Hansen, Bjørn G., Bilt, Yvonne van der (1999), “Public availability of Data on EU High Production Volume Chemicals”, European Commission, JRC, EUR 18996 EN.
     
  10. OECD (Q)SAR Application Toolbox v. 1.1. OECD Quantitative Structure-Activity Relationships [(Q)SARs] Project, http://www.oecd.org/. Search for OECD (Q)SAR Application Toolbox download.
     
  11. OECD document ENV/JM/TG(2004)26/REV1: ”COMPARISON OF SIDS TEST DATA WITH (Q)SAR PREDICTIONS FOR ACUTE AQUATIC TOXICITY, BIODEGRADABILITY AND MUTAGENICITY ON ORGANIC CHEMICALS DISCUSSED AT SIAM 11-18”
     
  12. Loonen, H., Lindgren, F, Hansen, B., Karcher, W., Niemelä, J., Hiromatsu, K.\ Takatsuki, M.\ Peijnenburg, W., Rorije, E., and Struijs, J. PREDICTION OF BIODEGRADABILITY FROM CHEMICAL STRUCTURE: MODELING OF READY BIODEGRADATION TEST DATA. Env. Toxicol. Chem., Vol. 18(8), 1763–1768, 1999.
     
  13. Klopman, G. Meihua, T. STRUCTURE–BIODEGRADABILITY STUDY AND COMPUTER-AUTOMATED PREDICTION OF AEROBIC BIODEGRADATION OF CHEMICALS. Env. Toxicol. Chem., Vol. 16(9), 1829-1835, 1997.
     
  14. Tunkel, J., Howard, P.H., Boethling, R.S., Stiteler, W., Loonen, H. Predicting Ready Biodegradability in the Japanese Ministry of International Trade and Industry Test. Env. Toxicol. Chem. 19(10); 2478-2485, 2000.
     
  15. Meylan, W.M., Howard, P.H., Boethling, R.S., Aronson,D., Printup,H., Gouchie, S. Improved method for estimating bioconcentration/
    bioaccumulation factor from octanol/water partition coefficient. Environ. Toxicol. Chem, 18(4); 644-672, 1999.
     
  16. BIOWIN Biodegradation Probability Program for Microsoft Windows, Syracuse Research Corporation, Syracuse, NY, U.S.A.
     
  17. Pedersen, H. Tyle, J.R. Niemelä, B. Guttman, L. Lander, and A. Wedebrand, Environmental Hazard Classification – data collection and interpretation guide for substances to be evaluated for classification as dangerous to the environment. Appendix 9; Validation of the BIODEG Probability Program, TemaNord Report 589, 1995, pp. 153-156.
     
  18. Howard, P.H., Boethling, R.S., Stiteler, W.M., Meylan, W.M., Hueber, A.E., Beauman, J.A., Larosche, M.E. Predictive Model for aerobic biodegradability developed from a file of evaluated biodegradation data. Environ. Toxicol. Chem, 11; 593-603, 1992.
     
  19. European Commission, Technical Guidance Document in Support of commission directive 93/67EEC on Risk Assessment for New Notified Substances and Commission Regulation (EC) No. 1488/94 on Risk Assessment for Existing Substances, Part III, ISBN 92-827-8013-9, 1996, p. 554.
     
  20. Improved Method for Estimating Bioconcentration Factor (BCF) from Octanol-Water Partition Coefficient, SRC TR-97-006 (3rd Update), August 13, 1997; prepared for: Robert S. Boethling, EPA-OPPT, Washington, DC; Contract No. 68-D5-0012; prepared by: W.M. Meylan, P.H. Howard, D. Aronson, H. Printup and S. Gouchie; Syracuse Research Corp., Environmental Science Center, 6225 Running Ridge Road, North Syracuse, NY 13212.
     
  21. Data from Brooke, L.T. et al. Acute Toxicities of Organic Chemicals to Fathead Minnows (Pimephales promelas), Center for Lake Superior Environm. Studies, University of Wisconsin, Superior 1988. G. Klopman, R. Saiakov, and S. Rozenkranz, Multiple Computer-Automated Structure Evaluation Study of Aquatic Toxicity II. Fathead minnow, Env. Toxicol. and Chem., Vol. 19, No 2, pp. 441-447 and data from G. Klopman, R. Saiakov, H.S. Rosenkranz, J.L.M. Hermans, Multiple Computer-Automated Structure Evaluation program study of aquatic toxicity 1: Guppy, Env. Toxicol. Chem. 18, 1999, pp. 2497-2505.
     
  22. Data from The Aquire Database (US EPA Ecotox Database), and R. Kühn, et. al. Results of the harmful effects of selected water pollutants (anilines, phenols, aliphatic compounds) to Daphnia magna, Water Res. 23; 495-499 (1989), and E. Urrestarazu Ramos, Aquatic Toxicity of Polar Narcotic Pollutants, Thesis - University of Utrecht (1998) ISBN 90-393-1638-4, p. 82-85, and O.C.Hansen, DTI Environment, Quantitative Structure-Activity Relationships ((Q)SAR) and Pesticides, April 1999, and Danish EPA report from VKI (Finn Pedersen) 1998, Immobilization Test of Aniline Compounds with the Crustacean Daphnia magna, and Danish EPA report from VKI (Finn Pedersen) 2002. Immobilization Test of Selected Organic Amines with the Crustacean Daphnia magna, and Danish EPA report from VKI (Finn Pedersen) 2003 Immobilization Test of Three Trialkylamine Compounds with the Crustacean Daphnia magna.
     
  23. Included were 396 tests made at the Danish Technical University for the Danish EPA, 85 physiological substances which theoretically are non-toxic to Algae, 17 Aquire tests (US EPA Ecotox Database), 27 tests from C.D.S Tomlin, The Pesticide manual , ISBN 1 901396 11 8, British Crop Protection Council, Surrey UK, 1997. 5 tests from Environmental Project no. 615 2001, Environmental and Health Assessment of Substances in Household Detergents and Cosmetic Detergent Products, Danish EPA. 1 test from D.R. Orvos, D.J. Versteeg, J. Inauen, M. Capdevielle, A. Rothenstein, V. Cunningham, Aquatic Toxicity of Triclosan, Env. Toxicol. and Chem. 21, 7, 2002,
     
  24. Guidance for the implementation of REACH - Guidance on information requirements and chemical safety assessment. European Chemicals Agency, 2008
     
  25. Hermens, J.L., et. al., Aquatic Toxicity of Polar Narcotic Pollutants, University of Utrecht, Utrecht, Netherlands, 1998.
     
  26. ECETOC Technical Report No. 67, The Role of Bioaccumulation in Environmental Risk Assessment: The Aquatic Environment and Related Food Webs, 1995.
     
  27. Pedersen, F., Tyle, H., Niemela, J., Guttman, B., Lander, L., and Wedebrand, A., 1995, Environmental Hazard Classification – data collection and interpretation guide for substances to be evaluated for classification as dangerous to the environment. Appendix 9; Validation of the BIODEG Probability Program, TemaNord Report 589, 153-156.
     
  28. Veith, G.D., D.L. Defoe and B.V. Bergstedt. 1979. Measuring and estimating the bioconcentration factor of chemicals on fish. J. Fish. Res. Board Can. 36:1040-1048.
     
  29. Danish Environmental Protection Agency (2004). List of Undesirable Substances. Environmental Review, 15/2004. ISBN 87-7614-477-1. Danish Environmental Protection Agency.
     
  30. Danish Environmental Protection Agency (1996). Criteria for selection of undesirable substances. Environmental Review, 71/1996. Danish Environmental Protection Agency.
     
  31. Danish Environmental Protection Agency (2000). List of Effects 2000. Environmental Review, 6/2000. Danish Environmental Protection Agency.
     
  32. The European lists of High Production Volume Chemicals (HPVs) and the Low Production Volume Chemicals (LPVCs) are listed in ESIS (European chemical Substances Information System). http://ecb.jrc.ec.europa.eu/esis/
     
  33. Globally Harmonized system of Classification and Labelling of Chemicals (GHS). United Nations, New York, Geneva. 2007. http://www.unece.org/trans/danger/publi/ghs/ghs_welcome_e.html
     
  34. 61. OECD (2004). OECD Principles for the Validation, for Regulatory Purposes, of (Quantitative) Structure-Activity Relationship Models. http://www.oecd.org/document/23/
    0,2340,en_2649_34379_33957015_1_1_1_1,00.html
     
  35. The Danish Environmental Protection Agency (2009). The Advisory list for self-classification of dangerous substances. Environmental Project No. 1303.
     
  36. Niemela, J., “Non-Structural Activity Coefficients for Acute Oral Toxicity in the Mouse and Rat”, Danish EPA, working document, 1992 (available on request)
     
  37. Niemela, J., “Acute Toxicity versus rout of Administration in Mice”, Danish EPA, working document, 1995 (available on request)
     
  38. http://pharma-algorithms.com/
     
  39. Hunter, W.J., et. al., “Intercomparison Study on the Determination of Single administration Toxicity in Rats,” J. ASSOC. AFF. ANAL. CHEM., Vol. 62, no. 4, 1979.
     
  40. Japertas, J., Didziapetris, R., Sazonovas, A, “Acute toxicity (LD50) prediction involving fragmental QSAR model, similarity analysis and reliability of predictions”, Abstracts / Toxicology Letters 172S (2007) S1-S240.
     
  41. Health Designs, Inc., “New Skin Sensitization Model,” Computational Toxicology News, no. 21, 1998
     
  42. MultiCASE; Model A33 Allergic contact dermatitis, July, 1998
     
  43. Niemela, J., “QSAR’s for the Estimation of Sensitization Potential,” Danish EPA, working document, 1999 (available on request).
     
  44. RTECS (Registry of Toxic Effects of Chemical Substances), US National Institute for Occupational Safety and Health (NIOSH), version of November 2000 from CHEMBANK.
     
  45. HSDB (Hazardous Substances Data Bank), US National Library of Medicine’s (NLM) Toxicology Data Network (TOXNET®), version of November 2000 from CHEMBANK
     
  46. Arnot J.A., W.M.Meylan, J. Tunkel, P.H Howard, D. Mackay, M. Bonnell, R.S. Boethling: “A Quantitative Structure-Activity relationship for Predicting Metabolic Biotransformation rates for Organic Chemicals in Fish”, Env. Toxicol. Chem 28 (6), 1168-77

 

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