Are Non-animal Systemic Safety Assessments Protective? A Toolbox and Workflow

• Published in: Toxicological sciences 2022-08, Vol.189 (1), p.124-147
• Main Authors: Middleton, Alistair M, Reynolds, Joe, Cable, Sophie, Baltazar, Maria Teresa, Li, Hequn, Bevan, Samantha, Carmichael, Paul L, Dent, Matthew Philip, Hatherell, Sarah, Houghton, Jade, Kukic, Predrag, Liddell, Mark, Malcomber, Sophie, Nicol, Beate, Park, Benjamin, Patel, Hiral, Scott, Sharon, Sparham, Chris, Walker, Paul, White, Andrew
• Format: Article
• Language: English
• Subjects: Adult; Bayes Theorem; Benchmarking; Cosmetics; Humans; Regulatory Science, Risk Assessment, and Decision Making; Risk Assessment; Workflow
• ISSN: 1096-6080; 1096-0929; 1096-0929
• DOI: 10.1093/toxsci/kfac068

Abstract An important question in toxicological risk assessment is whether non-animal new approach methodologies (NAMs) can be used to make safety decisions that are protective of human health, without being overly conservative. In this work, we propose a core NAM toolbox and workflow for conducting systemic safety assessments for adult consumers. We also present an approach for evaluating how protective and useful the toolbox and workflow are by benchmarking against historical safety decisions. The toolbox includes physiologically based kinetic (PBK) models to estimate systemic Cmax levels in humans, and 3 bioactivity platforms, comprising high-throughput transcriptomics, a cell stress panel, and in vitro pharmacological profiling, from which points of departure are estimated. A Bayesian model was developed to quantify the uncertainty in the Cmax estimates depending on how the PBK models were parameterized. The feasibility of the evaluation approach was tested using 24 exposure scenarios from 10 chemicals, some of which would be considered high risk from a consumer goods perspective (eg, drugs that are systemically bioactive) and some low risk (eg, existing food or cosmetic ingredients). Using novel protectiveness and utility metrics, it was shown that up to 69% (9/13) of the low risk scenarios could be identified as such using the toolbox, whilst being protective against all (5/5) the high-risk ones. The results demonstrated how robust safety decisions could be made without using animal data. This work will enable a full evaluation to assess how protective and useful the toolbox and workflow are across a broader range of chemical-exposure scenarios.