A 10-step framework for use of read-across (RAX) in next generation risk assessment (NGRA) for cosmetics safety assessment

Ankley, 2018, The adverse outcome pathway: a multifaceted framework supporting 21st century toxicology, Curr. Opin. Toxicol., 9, 1, 10.1016/j.cotox.2018.03.004 Bajusz, 2015, Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?, J. Chemoinf., 7, 20, 10.1186/s13321-015-0069-3 Ball, 2014, The challenge of using read-across within the EU REACH regulatory framework; how much uncertainty is too much? Dipropylene glycol methyl ether acetate, an exemplary case study, Regul. Toxicol. Pharmacol., 68, 212, 10.1016/j.yrtph.2013.12.007 Ball, 2016, Toward good read-across practice (GRAP) guidance, Altex-Altern. Anim. Exp., 33, 149 Benfenati, 2019, Integrating in silico models and read-across methods for predicting toxicity of chemicals: a step-wise strategy, Environ. Int., 131, 10.1016/j.envint.2019.105060 Berggren, 2015, Chemical safety assessment using read-across: assessing the use of novel testing methods to strengthen the evidence base for decision making, Environ. Health Perspect., 123, 1232, 10.1289/ehp.1409342 Berggren, 2017, Ab initio chemical safety assessment: a workflow based on exposureconsiderations and non-animal methods, Comput. Toxicol., 4, 31, 10.1016/j.comtox.2017.10.001 Bessems, 2017, The margin of internal exposure (MOIE) concept for dermal risk assessment based on oral toxicity data – a case study with caffeine, Toxicology, 392, 119, 10.1016/j.tox.2017.03.012 Blackburn, 2014, A framework to facilitate consistent characterization of read across uncertainty, Regul. Toxicol. Pharmacol., 68, 353, 10.1016/j.yrtph.2014.01.004 Blackburn, 2020, An interim internal Threshold of Toxicologic Concern (iTTC) for chemicals in consumer products, with support from an automated assessment of ToxCast™ dose response data, Regul. Toxicol. Pharmacol., 114, 104656, 10.1016/j.yrtph.2020.104656 Bury, 2021, New framework for a non-animal approach adequately assures the safety of cosmetic ingredients – a case study on caffeine, Regul Toxicol Pharmacol, 24 Campbell, 2015, A case study on quantitative in vitro to in vivo extrapolation for environmental esters: methyl-, propyl- and butylparaben, Toxicology, 332, 67, 10.1016/j.tox.2015.03.010 Cereto-Massagué, 2015, Molecular fingerprint similarity search in virtual screening, Methods, 71, 58, 10.1016/j.ymeth.2014.08.005 Chen, 2020, Retinoids and developmental neurotoxicity: utilizing toxicogenomics to enhance adverse outcome pathways and testing strategies, Reprod. Toxicol., 96, 102, 10.1016/j.reprotox.2020.06.007 Clewell, 2008, On the incorporation of chemical-specific information in risk assessment, Toxicol. Lett., 180, 100, 10.1016/j.toxlet.2008.06.002 Coulet, 2019, Use of in vitro bioassays to facilitate read-across assessment of nitrogen substituted heterocycle analogues of polycyclic aromatic hydrocarbons, Toxicol. Vitro, 59, 281, 10.1016/j.tiv.2019.04.030 Cronin, 2019, Unlocking the potential of in silico chemical safety assessment - a report on a cross-sector symposium on current opportunities and future challenges, Comput Toxicol, 10, 38, 10.1016/j.comtox.2018.12.006 Cronin, 2017, In silico prediction of organ level toxicity: linking chemistry to adverse effects, Toxicol. Res., 33, 173, 10.5487/TR.2017.33.3.173 Cronin, 2017, Relationship between Adverse Outcome Pathways and chemistry-cased in silico models to predict toxicity, Appl. in vitro Toxicol., 3, 286, 10.1089/aivt.2017.0021 De Abrew, 2015, A novel transcriptomics based in vitro method to compare and predict hepatotoxicity based on mode of action, Toxicology, 328, 29, 10.1016/j.tox.2014.11.008 De Abrew, 2019, Use of connectivity mapping to support read across: a deeper dive using data from 186 chemicals, 19 cell lines and 2 case studies, Toxicology, 423, 84, 10.1016/j.tox.2019.05.008 Delmaar, 2006 Dent, 2018, Principles underpinning the use of new methodologies in the risk assessment of cosmetic ingredients, Comput. Toxicol., 7, 20, 10.1016/j.comtox.2018.06.001 2016 2017 2019, Guidance on the use of the Threshold of Toxicological Concern approach in food safety assessment, EFSA J., 17 Ellison, 2020, Application of structural and functional pharmacokinetic analogs for physiologically based pharmacokinetic model development and evaluation, Regul. Toxicol. Pharmacol., 114, 104667, 10.1016/j.yrtph.2020.104667 2016 Embry, 2014, Risk assessment in the 21st century: roadmap and matrix, Crit. Rev. Toxicol., 44, 6, 10.3109/10408444.2014.931924 Escher, 2019, Towards grouping concepts based on new approach methodologies in chemical hazard assessment: the read-across approach of the EU-ToxRisk project, Arch. Toxicol., 93, 3643, 10.1007/s00204-019-02591-7 Firman, 2018, Read-across of 90-day rodent repeated-dose toxicity: a case study for selected simple aryl alcohol alkyl carboxylic acid esters, Comput. Toxicol., 7, 1, 10.1016/j.comtox.2018.05.001 Fisher, 2011, Pharmacokinetic modeling: prediction and evaluation of route dependent dosimetry of bisphenol A in monkeys with extrapolation to humans, Toxicol. Appl. Pharmacol., 257, 122, 10.1016/j.taap.2011.08.026 Gelbke, 2018, Toxicological assessment of lower alkyl methacrylate esters by a category approach, Regul. Toxicol. Pharmacol., 92, 104, 10.1016/j.yrtph.2017.11.013 Groothuis, 2015, Dose metric considerations in in vitro assays to improve quantitative in vitro-in vivo dose extrapolations, Toxicology, 332, 30, 10.1016/j.tox.2013.08.012 Hanway, 2000, Read-across of toxicological data in the notification of new chemicals, Toxicol. Lett., 116, 61 Helman, 2018, Extending the Generalised Read-Across approach (GenRA): a systematic analysis of the impact of physicochemical property information on read-across performance, Comput Toxicol, 8, 34, 10.1016/j.comtox.2018.07.001 Helman, 2019, Generalized read-across (GenRA): a workflow implemented into the EPA CompTox chemicals dashboard ALTEX-ALTERNATIVES to animal, Exp., 36, 462 Hewitt, 2020, Measurement of the penetration of 56 cosmetic relevant chemicals into and through human skin using a standardised protocol, J. Appl. Toxicol., 40, 403, 10.1002/jat.3913 House, 2021, Grouping of UVCB substances with new approach methodologies (NAMs) data, ALTEX - Altern. Anim. Exp., 38, 123 2017 2018 Jiang, 2019, The application of omics-based human liver platforms for investigating the mechanism of drug-induced hepatotoxicity in vitro, Arch. Toxicol., 93, 3067, 10.1007/s00204-019-02585-5 Klimisch, 1997, A systematic approach for evaluating the quality of experimental toxicological and ecotoxicological data, Regul. Toxicol. Pharmacol., 25, 1, 10.1006/rtph.1996.1076 Kovarich, 2019, Filling data gaps by read-across: a mini review on its application, Dev. Chall. Mol. Inf., 38 Krewski, 2020, Toxicity testing in the 21st century: progress in the past decade and future perspectives, Arch. Toxicol., 94, 1, 10.1007/s00204-019-02613-4 Laroche, 2018, Finding synergies for 3Rs-Toxicokinetics and read-across: report from an EPAA partners' Forum, Regul. Toxicol. Pharmacol., 99, 5, 10.1016/j.yrtph.2018.08.006 Lester, 2018, Structure activity relationship (SAR) toxicological assessments: the role of expert judgment, Regul. Toxicol. Pharmacol., 92, 390, 10.1016/j.yrtph.2017.12.026 Lipinski, 2001, Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings, Adv. Drug Deliv. Rev., 46, 3, 10.1016/S0169-409X(00)00129-0 Little, 2017, In silico approach to safety of botanical dietary supplement ingredients utilizing constituent-level characterization, Food Chem. Toxicol., 107, 418, 10.1016/j.fct.2017.07.017 Liu, 2019, Toxicogenomics: a 2020 vision, Trends Pharmacol. Sci., 40, 92, 10.1016/j.tips.2018.12.001 Low, 2013, Integrative Chemical–Biological Read-Across approach for chemical hazard classification, Chem. Res. Toxicol., 26, 1199, 10.1021/tx400110f Luijten, 2020, Utility of a next generation framework for assessment of genomic damage: a case study using the industrial chemical benzene, Environ. Mol. Mutagen., 61, 94, 10.1002/em.22346 Madden, 2019, In silico resources to assist in the development and evaluation of physiologically-based kinetic models, Comput. Toxicol., 11, 33, 10.1016/j.comtox.2019.03.001 McMullin, 2016, Development of an integrated multi-species and multi-dose route PBPK model for volatile methyl siloxanes - D4 and D5, Regul. Toxicol. Pharmacol., 74, S1, 10.1016/j.yrtph.2015.12.010 Meek, 2011, Risk Assessmet of combined exposure to multiple chemicals: a WHO/IPCS framework, Regul. Toxicol. Pharmacol., 60, S1, 10.1016/j.yrtph.2011.03.010 Mellor, 2016, The identification of nuclear receptors associated with hepatic steatosis to develop and extend adverse outcome pathways, Crit. Rev. Toxicol., 46, 138, 10.3109/10408444.2015.1089471 Mellor, 2016, Using molecular initiating events to develop a structural alert based screening workflow for nuclear receptor ligands associated with hepatic steatosis, Chem. Res. Toxicol., 29, 203, 10.1021/acs.chemrestox.5b00480 Mellor, 2017, Read-across for rat oral gavage repeated-dose toxicity for short-chain mono-alkylphenols: a case study, Comp Toxicol, 2, 1, 10.1016/j.comtox.2017.03.003 Mellor, 2019, Molecular fingerprint-derived similarity measures for toxicological read-across: recommendations for optimal use, Regul. Toxicol. Pharmacol., 101, 121, 10.1016/j.yrtph.2018.11.002 Moroni, 2020, SCREENED: a multistage model of thyroid gland function for screening endocrine-disrupting chemicals in a biologically sex-specific manner, Int. J. Mol. Sci., 21, 3648, 10.3390/ijms21103648 2017 2021, 1 Ouedraogo, 2020 Patlewicz, 2015, Building scientific confidence in the development and evaluation of read-across, Regul. Toxicol. Pharmacol., 72, 117, 10.1016/j.yrtph.2015.03.015 Patlewicz, 2017, Navigating through the minefield of read-across tools: a review of in silico tools for grouping, Comput Toxicol, 3, 1, 10.1016/j.comtox.2017.05.003 Pawar, 2019, In silico toxicology data resources to support read-across and (Q)SAR, Front. Pharmacol., 10, 561, 10.3389/fphar.2019.00561 Przybylak, 2017, Read-across of 90-day rat oral repeated-dose toxicity: a case study for selected β-olefinic alcohols, Comp Toxicology, 1, 22, 10.1016/j.comtox.2016.11.001 Punt, 2020, New approach methodologies (NAMs) for human-relevant biokinetics predictions: meeting the paradigm shift in toxicology towards an animal-free chemical risk assessment, ALTEX - Altern. Anim. Exp., 37, 607 Ryan, 2019, Evaluating sufficient similarity of botanical dietary supplements: combining chemical and in vitro biological data, Toxicol. Sci., 172, 316, 10.1093/toxsci/kfz189 Sauer, 2020, 21st century approaches for evaluating exposures, biological activity, and risks of complex substances: workshop highlights, Regul. Toxicol. Pharmacol., 111, 104583, 10.1016/j.yrtph.2020.104583 2018, 24 Schultz, 2017, Read-across of 90-day rat oral repeated-dose toxicity: a case study for selected n-alkanols, Comp Toxicology, 2, 12, 10.1016/j.comtox.2017.02.002 Schultz, 2017, Read-across of 90-day rat oral repeated-dose toxicity: a case study for selected 2-alkyl-1-alkanols, Comput.Toxicol., 2, 28, 10.1016/j.comtox.2017.02.005 Schultz, 2019, Assessing uncertainty in read-across: questions to evaluate toxicity predictions based on knowledge gained from case studies, Comput.Toxicol., 9, 1, 10.1016/j.comtox.2018.10.003 Shah, 2016, Systematically evaluating read-across prediction and performance using a local validity approach characterised by chemical structure and bioactivity information, Regul. Toxicol. Pharmacol., 79, 12, 10.1016/j.yrtph.2016.05.008 Shen, 2014, An in silico skin absorption model for fragrance materials, Food Chem. Toxicol., 74, 164, 10.1016/j.fct.2014.09.015 Solomon, 2008, Extrapolation in the context of criteria setting and risk assessment, 1 Sperber, 2019, Metabolomics as read-across tool: an example with 3-aminopropanol and 2-aminoethanol, Regul. Toxicol. Pharmacol., 108, 104442, 10.1016/j.yrtph.2019.104442 Tan, 2020, PBPK model reporting template for chemical risk assessment applications, Regul. Toxicol. Pharmacol., 115, 104691, 10.1016/j.yrtph.2020.104691 Thomas, 2019, The next generation blueprint of computational toxicology at the U.S. Environmental protection agency, Toxicol. Sci., 169, 317, 10.1093/toxsci/kfz058 Troutman, 2015, Development of a physiologically-based pharmacokinetic model of 2-phenoxyethanol and its metabolite phenoxyacetic acid in rats and humans to address toxicokinetic uncertainty in risk assessment, Regul. Toxicol. Pharmacol., 10.1016/j.yrtph.2015.07.012 1994 2006 US Environmental Protection Agency (USEPA), 2011, Recommended use of body weight3/4 as the default method in derivation of the oral reference dose, Risk Assessment Forum VanderMolen, 2020, Incorporation of In vitro techniques for botanicals dietary supplement safety assessment - towards evaluation of developmental and reproductive toxicity (DART), Food Chem. Toxicol., 6, 111539, 10.1016/j.fct.2020.111539 Van der Stel, 2021, New approach methods supporting read-across: two neurotoxicity AOP-based IATA case studies, ALTEX, 10.14573/altex.2103051 van Ravenzwaay, 2016, Metabolomics as read-across tool: a case study with phenoxy herbicides, Regul. Toxicol. Pharmacol., 81, 288, 10.1016/j.yrtph.2016.09.013 WHO, 2010, 9 Willett, 1998, Chemical similarity searching, J. Chem. Inf. Comput. Sci., 38, 983, 10.1021/ci9800211 Wu, 2010, A framework for using structural, reactivity, metabolic and physicochemical similarity to evaluate the suitability of analogs for SAR-based toxicological assessments, Regul. Toxicol. Pharmacol., 56, 67, 10.1016/j.yrtph.2009.09.006 Yang, 2017, Thresholds of Toxicological Concern for cosmetics-related substances: new database, thresholds, and enrichment of chemical space, Food Chem. Toxicol., 109, 170, 10.1016/j.fct.2017.08.043