1 3 Proposing a scientific confidence framework to help support the 4 application of adverse outcome pathways for regulatory purposes 5 6 7 Grace Patlewicz a,⇑ , Ted Simon b , J. Craig Rowlands c , Robert A. Budinsky c , Richard A. Becker d 8 a DuPont Haskell Global Centers for Health and Environmental Sciences, 1090 Elkton Road, Newark, DE 19711, USA 9 b Ted Simon LLC, 4184 Johnston Road, Winston, GA 30187, USA 10 c The Dow Chemical Company, Toxicology & Environmental Research & Consulting, 1803 Building Washington Street, Midland, MI 48674, USA 11 d Regulatory and Technical Affairs Department, American Chemistry Council (ACC), Washington, DC 20002, USA 12 13 15 article info 16 Article history: 17 Received 29 August 2014 18 Available online xxxx 19 Keywords: 20 Scientific confidence framework (SCF) 21 Adverse outcome pathway (AOP) 22 Mode of action (MoA) 23 Integrated approaches to testing and 24 assessment (IATA) 25 (Q)SAR 26 Read-across 27 Exposure:activity ratio (EAR) 28 29 abstract 30 An adverse outcome pathway (AOP) describes the causal linkage between initial molecular events and an 31 adverse outcome at individual or population levels. Whilst there has been considerable momentum in 32 AOP development, far less attention has been paid to how AOPs might be practically applied for different 33 regulatory purposes. This paper proposes a scientific confidence framework (SCF) for evaluating and 34 applying a given AOP for different regulatory purposes ranging from prioritizing chemicals for further 35 evaluation, to hazard prediction, and ultimately, risk assessment. The framework is illustrated using three 36 different AOPs for several typical regulatory applications. The AOPs chosen are ones that have been 37 recently developed and/or published, namely those for estrogenic effects, skin sensitisation, and rodent 38 liver tumor promotion. The examples confirm how critical the data-richness of an AOP is for driving 39 its practical application. In terms of performing risk assessment, human dosimetry methods are neces- 40 sary to inform meaningful comparisons with human exposures; dosimetry is applied to effect levels 41 based on non-testing approaches and in vitro data. Such a comparison is presented in the form of an expo- 42 sure:activity ratio (EAR) to interpret biological activity in the context of exposure and to provide a basis 43 for product stewardship and regulatory decision making. 44 Ó 2015 Published by Elsevier Inc. 45 46 47 48 1. Introduction 49 Societal demands for safer and more sustainable chemical prod- 50 ucts are stimulating changes in toxicity testing and assessment 51 frameworks. Chemical safety assessments are expected to be 52 conducted faster and with fewer animals, and at the same time, 53 the number of chemicals that require assessment is also rising with 54 the number of different regulatory programmes increasing world- 55 wide. These considerations have stimulated a shift in thinking 56 about how toxicity testing and their evaluations need be conduct- 57 ed in the future-moving away from extensive toxicity testing based 58 on phenotypic responses in animals towards pathway approaches 59 based on (quantitative) structure–activity relationships ((Q)SAR), 60 toxicokinetics, physiological mechanisms and dose-dependent 61 biological changes underlying toxicity in exposed organisms. Since 62 ‘‘safety,’’ by definition, includes both the inherent hazards of the 63 substances that make up a product and exposures that occur as a 64 result of use of the product, improvements are needed in both 65 approaches for evaluating intrinsic hazards and approaches for 66 determining exposures. These visions were articulated to a large 67 extent in the 2007 NRC report ‘‘Toxicity Testing in the 21st Centu- 68 ry: A Vision and a Strategy’’ (NRC, 2007) and the 2012 NRC report 69 ‘‘Exposure Science in the 21st Century: A Vision and A Strategy’’ 70 (NRC, 2012; Cohen Hubal et al., 2010). 71 A move towards more mechanistically based risk assessments 72 implies with it the use of in vitro tests, including high throughput 73 and high content (HT/HC) screening methods, coupled with the 74 application of a range of computational methods for data analysis 75 and predictive modeling. Thus achieving the visions of Tox21 and 76 EXPO21 relies on 4 key components: 77  The generation of in vitro data. 78  The derivation of models from these biological activity assays 79 that predict downstream biological responses of toxicological 80 relevance. http://dx.doi.org/10.1016/j.yrtph.2015.02.011 0273-2300/Ó 2015 Published by Elsevier Inc. ⇑ Corresponding author at: EPA, Office of Research and Development, National Center for Computational Toxicology, 109 T W Alexander Dr, Durham, NC 27711, USA. E-mail address: patlewig@hotmail.com (G. Patlewicz). Regulatory Toxicology and Pharmacology xxx (2015) xxx–xxx Contents lists available at ScienceDirect Regulatory Toxicology and Pharmacology journal homepage: www.elsevier.com/locate/yrtph YRTPH 3239 No. of Pages 16, Model 5G 20 February 2015 Please cite this article in press as: Patlewicz, G., et al. Proposing a scientific confidence framework to help support the application of adverse outcome path- ways for regulatory purposes. Regul. Toxicol. Pharmacol. (2015), http://dx.doi.org/10.1016/j.yrtph.2015.02.011