Search

Risk assessment methodologies in toxicology have remained largely unchanged for decades. The default approach uses high dose animal studies, together with human exposure estimates, and conservative assessment (uncertainty) factors or linear extrapolations to determine whether a specific chemical exposure is 'safe' or 'unsafe'. Although some incremental changes have appeared over the years, results from all new approaches are still judged against this process of extrapolating high-dose effects in animals to low-dose exposures in humans. The US National Research Council blueprint for change, entitled Toxicity Testing in the 21st Century: A Vision and Strategy called for a transformation of toxicity testing from a system based on high-dose studies in laboratory animals to one founded primarily on in vitro methods that evaluate changes in normal cellular signalling pathways using human-relevant cells or tissues. More recently, this concept of pathways-based approaches to risk assessment has been expanded by the description of 'Adverse Outcome Pathways' (AOPs). The question, however, has been how to translate this AOP/TT21C vision into the practical tools that will be useful to those expected to make safety decisions. We have sought to provide a practical example of how the TT21C vision can be implemented to facilitate a safety assessment for a commercial chemical without the use of animal testing. To this end, the key elements of the TT21C vision have been broken down to a set of actions that can be brought together to achieve such a safety assessment. Such components of a pathways-based risk assessment have been widely discussed, however to-date, no worked examples of the entire risk assessment process exist. In order to begin to test the process, we have taken the approach of examining a prototype toxicity pathway (DNA damage responses mediated by the p53 network) and constructing a strategy for the development of a pathway based risk assessment for a specific chemical in a case study mode. This contribution represents a 'work-in-progress' and is meant to both highlight concepts that are well-developed and identify aspects of the overall process which require additional development. To guide our understanding of what a pathways-based risk assessment could look like in practice, we chose to work on a case study chemical (quercetin) with a defined human exposure and to bring a multidisciplinary team of chemists, biologists, modellers and risk assessors to work together towards a safety assessment. Our goal was to see if the in vitro dose response for quercetin could be sufficiently understood to construct a TT21C risk assessment without recourse to rodent carcinogenicity study data. The data presented include high throughput pathway biomarkers (p-H2AX, p-ATM, p-ATR, p-Chk2, p53, p-p53, MDM2 and Wip1) and markers of cell-cycle, apoptosis and micronuclei formation, plus gene transcription in HT1080 cells. Eighteen point dose response curves were generated using flow cytometry and imaging to determine the concentrations that resulted in significant perturbation. NOELs and BMDs were compared to the output from biokinetic modelling and the potential for in vitro to in vivo extrapolation explored. A first tier risk assessment was performed comparing the total quercetin concentration in the in vitro systems with the predicted total quercetin concentration in plasma and tissues. The shortcomings of this approach and recommendations for improvement are described. This paper therefore describes the current progress in an ongoing research effort aimed at providing a pathways-based, proof-of-concept in vitro-only safety assessment for a consumer use product., (Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.)

The 2007 National Research Council Report "Toxicity Testing in the 21st Century: A Vision and A Strategy" recommended an integrated, toxicity pathway-oriented approach for chemical testing. As an integral component of the recommendation, computational dose-response modeling of toxicity pathways promises to provide mechanistic interpretation and prediction of adverse cellular outcomes. Among the many toxicity pathways, the DNA damage response is better characterized and thus more suited for computational modeling. In the present study, we formulated a minimal mathematical model of this pathway to examine the dose response for etoposide (ETP), an anticancer drug that causes DNA double strand breaks (DSBs). In the model, DSB results from inhibition of topoisomerase by ETP and p53 is activated by a bistable switch composed of a positive feedback loop between ATM and γH2AX. Our stochastic model recapitulated the dose response for several molecular biomarkers measured with flow cytometry in HT1080 cells, including phosphorylated p53, ATM, γH2AX, and micronuclei. Model simulations were consistent with a bimodal pattern of p53 activation and a graded population-averaged response at high ETP concentrations. The graded response was a result of heterogeneous activation of individual cells due to molecular stochasticity. This work shows the value of combining data collection on single cell responses and mechanistic, stochastic modeling to develop and test hypothesis for the circuitry of important toxicity pathways. Future studies will determine how well this initial modeling effort agrees with a broader set of experimental studies on pathway responses by examining a more diverse group of DNA-damaging compounds.