Making better use of toxicity studies for human health by extrapolating across endpoints
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Abstract
To develop and evaluate scientifically robust and innovative approaches for the safety assessment of chemicals across multiple regulatory sectors, the EU Reference Laboratory for alternatives to animal testing (EURL ECVAM) has started a project to explore how to better use the available information, including that from existing animal studies. The aim is to minimize reliance on in vivo testing to avoid redundancy and to facilitate the integration of novel non-animal methods in the regulatory setting with the ultimate goal of designing sustainable testing strategies. In this thought-starter paper, we present a number of examples to illustrate and trigger further discussions within the scientific and regulatory communities on ways to extrapolate useful information for predicting toxicity from one toxicity endpoint to another or across endpoints based on mechanistic information.
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Arzuaga, X., T., Smith, M., F., Gibbons, C. et al. (2019). Proposed key characteristics of male reproductive toxicants as an approach for organizing and evaluating mechanistic evidence in human health hazard assessments. Environ Health Perspect 127, 65001. doi:10.1289/EHP5045
Asturiol, D., Casati, S. and Worth, A. (2016). Consensus of classification trees for skin sensitisation hazard prediction. Toxicol In Vitro 36, 197-209. doi:10.1016/J.TIV.2016.07.014
Bal-Price, A., Pistollato, F., Sachana, M. et al. (2018). Strategies to improve the regulatory assessment of developmental neurotoxicity (DNT) using in vitro methods. Toxicol Appl Pharmacol 354, 7-18. doi:10.1016/J.TAAP.2018.02.008
Basketter, D. A., Alépée, N., Ashikaga, T. et al. (2014). Categorization of chemicals according to their relative human skin sensitizing potency. Dermatitis 25, 11-21. doi:10.1097/DER.0000000000000003
Batke, M., Escher, S., Hoffmann-Doerr, S. et al. (2011). Evaluation of time extrapolation factors based on the database RepDose. Toxicol Lett 205, 112-129. doi:10.1016/j.toxlet.2011.05.1030
Bennett, J. M., Reeves, G., Billman, G. E. et al. (2018). Inflammation – Nature’s way to efficiently respond to all types of challenges: Implications for understanding and managing “the epidemic” of chronic diseases. Front Med 5, 316. doi:10.3389/fmed.2018.00316
Bessems, J., Coecke, S., Goliarmou, V. et al. (2015). JRC Science and Policy Report. EURL ECVAM Strategy for Achieving 3Rs Impact in the Assessment of Toxicokinetics and Systemic Toxicity. Luxembourg: Publications Office of the EU. doi:10.2788/197633
Bloom, J. (1993). Principles of hematotoxicology: Laboratory assessment and interpretation of data. Toxicol Pathol 21, 30-34. doi:10.1177/019262339302100203
Bloom, J. and Brandt, J. (2001). Toxic responses of the blood. In C. D. Klaassen (ed.), Casarett and Doull’s Toxicology the Basic Science of Poisons (389-417). New York, USA: McGraw-Hill.
Bokkers, B. G. H. and Slob, W. (2005). A comparison of ratio distributions based on the NOAEL and the benchmark approach for subchronic-to-chronic extrapolation. Toxicol Sci 85, 1033-1040. doi:10.1093/toxsci/kfi144
Boobis, A. R., Doe, J. E., Heinrich-Hirsch, B. et al. (2008). IPCS framework for analyzing the relevance of a noncancer mode of action for humans. Crit Rev Toxicol 38, 87-96. doi:10.1080/10408440701749421
Bos, P. M. J., Geraets, L., de Wit-Bos et al. (2020). Towards an animal-free human health assessment: Starting from the current regulatory needs. ALTEX 37, 395-408. doi:10.14573/altex.1912041
Braakhuis, H. M., Slob, W., Olthof, E. D. et al. (2018). Is current risk assessment of non-genotoxic carcinogens protective? Crit Rev Toxicol 48, 500-511. doi:10.1080/10408444.2018.1458818
Budinsky, R. A. (2003). Hematotoxicity: Chemically induced toxicity of the blood. In P. L. Williams, R. C. James and S. M. Roberts, Principals of Toxicology: Environmental and Industrial Applications (Chapter 4, 87-109). 2nd edition. John Wiley & Sons. doi:10.1002/0471231800.ch4
Bulgheroni, A., Kinsner-Ovaskainen, A., Hoffmann, S. et al. (2009). Estimation of acute oral toxicity using the no observed adverse effect level (NOAEL) from the 28 day repeated dose toxicity studies in rats. Regul Toxicol Pharmacol 53, 16-19. doi:10.1016/J.YRTPH.2008.10.001
Burgdorf, T., Piersma, A. H., Landsiedel, R. et al. (2019). Workshop on the validation and regulatory acceptance of innovative 3R approaches in regulatory toxicology – Evolution versus revolution. Toxicol In Vitro 59, 1-11. doi:10.1016/j.tiv.2019.03.039
Carvajal, F. J., Mattison, H. A. and Cerpa, W. (2016). Role of NMDA receptor-mediated glutamatergic signaling in chronic and acute neuropathologies. Neural Plast 2016, 2701526. doi:10.1155/2016/2701526
Cohen, S. M., Boobis, A. R., Dellarco, V. L. et al. (2019). Chemical carcinogenicity revisited 3: Risk assessment of carcinogenic potential based on the current state of knowledge of carcinogenesis in humans. Regul Toxicol Pharmacol 103, 100-105. doi:10.1016/J.YRTPH.2019.01.017
Corvi, R., Madia, F., Guyton, K. Z. et al. (2017). Moving forward in carcinogenicity assessment: Report of an EURL ECVAM/ ESTIV workshop. Toxicol In Vitro 45, 278-286. doi:10.1016/j.tiv.2017.09.010
EC (2006). 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 1999/4. OJ L 396, 1-849. http://data.europa.eu/eli/reg/2006/1907/oj
EC (2008). Regulation (EC) No 1272/2008 of the European Parliament and of the Council of 16 December 2008 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. OJ L 353, 1-1355. http://data.europa.eu/eli/reg/2008/1272/oj
EC (2009). Regulation (EC) No 1223/2009 of the European Parliament and of the Council of 30 November 2009 on cosmetic products. OJ L 342, 59-209. http://data.europa.eu/eli/reg/2009/1223/oj
ECETOC (2010). Guidance on Assessment Factors to Derive a DNEL, Technical Report No 110. Tech Rep 110. http://members.ecetoc.org/Documents/Document/20110131112906-ECETOC_Technical_Report_110.pdf
ECHA (2012). Guidance on information requirements and chemical safety assessment. Chapter R.8: Characterisation of dose [concentration]-response for human health. Eur Chem Agency, 1-186. http://echa.europa.eu/documents/10162/13632/information_requirements_r8_en.pdf
ECHA (2016). New Approach Methodologies in Regulatory Science. Proceedings of a scientific workshop, Helsinki 19-20 April 2016. Publications Office of the European Union, 1-65. doi:10.2823/543644
ECHA (2017). Guidance on information requirements and chemical safety assessment. Chapter R.7a: Endpoint specific guidance. Eur Chem Agency, 1-610. https://echa.europa.eu/documents/10162/13632/information_requirements_r7a_en.pdf/e4a2a18f-a2bd-4a04-ac6d-0ea425b2567f
EFSA (2012). Guidance on selected default values to be used by the EFSA Scientific Committee, Scientific Panels and Units in the absence of actual measured data. EFSA J 10, 2579. doi:10.2903/j.efsa.2012.2579
EU (2010). Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes. OJ L 276, 33-79. http://data.europa.eu/eli/dir/2010/63/oj
Fielden, M. R., Ward, L. D., Minocherhomji, S. et al. (2018). Modernizing human cancer risk assessment of therapeutics. Trends Pharmacol Sci 39, 232-247. doi:10.1016/j.tips.2017.11.005
Foran, C. M., Rycroft, T., Keisler, J. et al. (2020). A modular approach for assembly of quantitative adverse outcome pathways. ALTEX 36, 353-362. doi:10.14573/altex.1810181
Furman, D., Campisi, J., Verdin, E. et al. (2019). Chronic inflammation in the etiology of disease across the life span. Nat Med 25, 1822-1832. doi:10.1038/s41591-019-0675-0
Gissi, A., Louekari, K., Hoffstadt, L. et al. (2017). Alternative acute oral toxicity assessment under REACH based on sub-acute toxicity values. ALTEX 34, 353-361. doi:10.14573/altex.1609121
Graepel, R., Asturiol, D., Prieto, P. et al. (2016). Exploring waiving opportunities for mammalian acute systemic toxicity tests. Altern Lab Anim 44, 271-279. doi:10.1177/026119291604400306
Guyton, K. Z., Kyle, A. D., Aubrecht, J. et al. (2009). Improving prediction of chemical carcinogenicity by considering multiple mechanisms and applying toxicogenomic approaches. Mutat Res 681, 230-240. doi:10.1016/j.mrrev.2008.10.001
Hunter, P. (2012). The inflammation theory of disease. The growing realization that chronic inflammation is crucial in many diseases opens new avenues for treatment. EMBO Rep 13, 968-970. doi:10.1038/embor.2012.142
ICH (2016). Regulatory Notice Document, Proposed Change to Rodent Carcinogenicity Testing of Pharmaceuticals. http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Safety/S1/S1_RND_Revisions_22Dec2015_Final.pdf
Jacobs, M. N., Colacci, A., Louekari, K. et al. (2016). International regulatory needs for development of an IATA for non-genotoxic carcinogenic chemical substances. ALTEX 33, 359-392. doi:10.14573/altex.1601201
Jacobs, M. N., Colacci, A., Corvi, R. et al. (2020). Chemical carcinogen safety testing: OECD expert group international consensus on the development of an integrated approach for the testing and assessment of chemical non-genotoxic carcinogens. Arch Toxicol 94, 2899-2923. doi:10.1007/s00204-020-02784-5
JRC (2016). Screening methodology to identify potential endocrine disruptors according to different options in the context of an impact assessment. EUR 27955 EN. doi:10.2788/73203
Kalberlah, F. and Schneider, K. (1998). Quantification of extrapolation factors: Final report of the research project No. 116 06 113 of the Federal Environmental Agency. Wirtschaftsverlag NW.
Kalberlah, F., Fost, U. and Schneider, K. (2002). Time extrapolation and interspecies extrapolation for locally acting substances in case of limited toxicological data. Ann Occup Hyg 46, 175-185. doi:10.1093/annhyg/mef014
Kienzler, A., Barron, M. G., Belanger, S. E. et al. (2017). Mode of action (MOA) assignment classifications for ecotoxicology: An evaluation of approaches. Environ Sci Technol 51, 10203-10211. doi:10.1021/acs.est.7b02337
Krewski, D., Andersen, M. E., Tyshenko, M. G. et al. (2020). Toxicity testing in the 21st century: Progress in the past decade and future perspectives. Arch Toxicol 94, 1-58. doi:10.1007/s00204-019-02613-4
La Merrill, M. A., Vandenberg, L. N., Smith, M. T. et al. (2019). Consensus on the key characteristics of endocrine-disrupting chemicals as a basis for hazard identification. Nat Rev Endocrinol 16, 45-57. doi:10.1038/s41574-019-0273-8
Laroche, C., Annys, E., Bender, H. et al. (2019). Finding synergies for the 3Rs – Repeated dose toxicity testing: Report from an EPAA partners’ forum. Regul Toxicol Pharmacol 108, 104470. doi:10.1016/J.YRTPH.2019.104470
Luderer, U., Eskenazi, B., Hauser, R. et al. (2019). Proposed key characteristics of female reproductive toxicants as an approach for organizing and evaluating mechanistic data in hazard assessment. Environ Health Perspect 127, 75001. doi:10.1289/EHP4971
Luechtefeld, T., Marsh, D., Rowlands, C. et al. (2018). Machine learning of toxicological big data enables read-across structure activity relationships (RASAR) outperforming animal test reproducibility. Toxicol Sci 165, 198-212. doi:10.1093/toxsci/kfy152
Madia, F., Worth, A., Whelan, M. et al. (2019). Carcinogenicity assessment: Addressing the challenges of cancer and chemicals in the environment. Environ Int 128, 417-429. doi:10.1016/j.envint.2019.04.067
Madia, F., Kirkland, D., Morita, T. et al. (2020). EURL ECVAM genotoxicity and carcinogenicity database of substances eliciting negative results in the Ames test: Construction of the database. Mutat Res 854-855, 503199. doi:10.1016/j.mrgentox.2020.503199
Mahony, C., Ashton, R. S., Birk, B. et al. (2020). New ideas for non-animal approaches to predict repeated-dose systemic toxicity: Report from an EPAA blue sky workshop. Regul Toxicol Pharmacol 114, 104668. doi:10.1016/J.YRTPH.2020.104668
Mantovani, A., Allavena, P., Sica, A. et al. (2008). Cancer-related inflammation. Nature 454, 436-444. doi:10.1038/nature07205
May, M., Drost, W., Germer, S. et al. (2016). Evaluation of acute-to-chronic ratios of fish and Daphnia to predict acceptable no-effect levels. Environ Sci Eur 28, 16. doi:10.1186/s12302-016-0084-7
Meek, M. E., Boobis, A., Cote, I. et al. (2014). New developments in the evolution and application of the WHO/IPCS framework on mode of action/species concordance analysis. J Appl Toxicol 34, 1-18. doi:10.1002/jat.2949
Miklossy, J. and McGeer, P. L. (2016). Common mechanisms involved in Alzheimer’s disease and type 2 diabetes: A key role of chronic bacterial infection and inflammation. Aging (Albany NY) 8, 575-588. doi:10.18632/aging.100921
Nordlander, K., Simon, C.-M. and Pearson, H. (2010). Hazard v. risk in EU chemicals regulation. Eur J Risk Regul 1, 239-250. doi:10.1017/S1867299X00000416
NRC (2017). Using 21st Century Science to Improve Risk-Related Evaluations. Washington, DC, USA: National Academic Press. doi:10.17226/24635
OECD (2014a). Guidance Document 116 on the Conduct and Design of Chronic Toxicity and Carcinogenicity Studies, Supporting Test Guidelines 451, 452 and 453. Second edition. OECD Series on Testing and Assessment, No. 116, OECD Publishing, Paris. doi:10.1787/9789264221475-en
OECD (2014b). Guidance Document for Describing Non-Guideline In Vitro Methods. OECD Series on Testing and Assessment, No. 211. https://bit.ly/30fwAnk
OECD (2017a). Guidance Document for the Use of Adverse Outcome Pathways in Developing Integrated Approaches to Testing and Assessment (IATA). OECD Series on Testing and Assessment, No. 260, OECD Publishing, Paris. doi:10.1787/44bb06c1-en
OECD (2017b). Guidance Document on the Reporting of Defined Approaches and Individual Information Sources to be Used within Integrated Approaches to Testing and Assessment (IATA) for Skin Sensitisation. OECD Series on Testing and Assessment, No. 256. OECD Publishing, Paris. doi:10.1787/9789264279285-en
OECD (2019). Guiding Principles and Key Elements for Establishing a Weight of Evidence for Chemical Assessment. Series on Testing and Assessment, No 311. Environment, Health and Safety Division, Environment Directorate. https://bit.ly/3j9ThAZ
Patlewicz, G., Kuseva, C., Kesova, A. et al. (2014). Towards AOP application – Implementation of an integrated approach to testing and assessment (IATA) into a pipeline tool for skin sensitization. Regul Toxicol Pharmacol 69, 529-545. doi:10.1016/J.YRTPH.2014.06.001
Piersma, A. H., Burgdorf, T., Louekari, K. et al. (2018). Workshop on acceleration of the validation and regulatory acceptance of alternative methods and implementation of testing strategies. Toxicol In Vitro 50, 62-74. doi:10.1016/j.tiv.2018.02.018
Pieters, M. N., Kramer, H. J. and Slob, W. (1998). Evaluation of the uncertainty factor for subchronic-to-chronic extrapolation: Statistical analysis of toxicity data. Regul Toxicol Pharmacol 27, 108-111. doi:10.1006/RTPH.1997.1196
Pohl, H. R., Chou, C.-H. S. J., Ruiz, P. et al. (2010). Chemical risk assessment and uncertainty associated with extrapolation across exposure duration. Regul Toxicol Pharmacol 57, 18-23. doi:10.1016/J.YRTPH.2009.11.007
Prieto, P., Graepel, R., Gerloff, K. et al. (2019). Investigating cell type specific mechanisms contributing to acute oral toxicity. ALTEX 36, 39-64. doi:10.14573/altex.1805181
Schilter, B., Benigni, R., Boobis, A. et al. (2014). Establishing the level of safety concern for chemicals in food without the need for toxicity testing. Regul Toxicol Pharmacol 68, 275-296. doi:10.1016/J.YRTPH.2013.08.018
Schneider, K., Hassauer, M., Oltmanns, J. et al. (2005). Uncertainty analysis in workplace effect assessment. Proj Rep F1824/F1825/F1826 Fed Inst Occup Saf Heal Dortmund.
Schwarzman, M. R., Ackerman, J. M., Dairkee, S. H. et al. (2015). Screening for chemical contributions to breast cancer risk: A case study for chemical safety evaluation. Environ Health Perspect 123, 1255-1264. doi:10.1289/ehp.1408337
Sistare, F. D., Morton, D., Alden, C. et al. (2011). An analysis of pharmaceutical experience with decades of rat carcinogenicity testing: Support for a proposal to modify current regulatory guidelines. Toxicol Pathol 39, 716-744. doi:10.1177/0192623311406935
Smith, M. T., Guyton, K. Z., Gibbons, C. F. et al. (2016). Key characteristics of carcinogens as a basis for organizing data on mechanisms of carcinogenesis. Environ Health Perspect 124, 713-721. doi:10.1289/ehp.1509912
Sonich-Mullin, C., Fielder, R., Wiltse, J. et al. (2001). IPCS conceptual framework for evaluating a mode of action for chemical carcinogenesis. Regul Toxicol Pharmacol 34, 146-152. doi:10.1006/RTPH.2001.1493
Spinu, N., Bal-Price, A., Cronin, M. T. D. et al. (2019). Development and analysis of an adverse outcome pathway network for human neurotoxicity. Arch Toxicol 93, 2759-2772. doi:10.1007/s00204-019-02551-1
Spinu, N., Cronin, M. T. D., Enoch, S. J. et al. (2020). Quantitative adverse outcome pathway (qAOP) models for toxicity prediction. Arch Toxicol 94, 1497-1510. doi:10.1007/s00204-020-02774-7
Suzuki, T. and Yamamoto, M. (2015). Molecular basis of the Keap1-Nrf2 system. Free Radic Biol Med 88, 93-100. doi:10.1016/j.freeradbiomed.2015.06.006
Todoric, J., Antonucci, L. and Karin, M. (2016). Targeting inflammation in cancer prevention and therapy. Cancer Prev Res 9, 895-905. doi:10.1158/1940-6207.CAPR-16-0209
van der Laan, J. W., Kasper, P., Silva Lima, B. et al. (2016). Critical analysis of carcinogenicity study outcomes. Relationship with pharmacological properties. Crit Rev Toxicol 46, 587-614. doi:10.3109/10408444.2016.1163664
Villeneuve, D. L., Angrish, M. M., Fortin, M. C. et al. (2018a). Adverse outcome pathway networks II: Network analytics. Environ Toxicol Chem 37, 1734-1748. doi:10.1002/etc.4124
Villeneuve, D. L., Landesmann, B., Allavena, P. et al. (2018b). Representing the process of inflammation as key events in adverse outcome pathways. Toxicol Sci 163, 346-352. doi:10.1093/toxsci/kfy047
Wolf, D. C., Cohen, S. M., Boobis, A. R. et al. (2019). Chemical carcinogenicity revisited 1: A unified theory of carcinogenicity based on contemporary knowledge. Regul Toxicol Pharmacol 103, 86-92. doi:10.1016/J.YRTPH.2019.01.021
Zuang, V., Dura, A. et al. (2020). EURL ECVAM status report on the development, validation and regulatory acceptance of alternative methods and approaches (2019). Publ Off Eur Union EUR 30100 EN. doi:10.2760/25602