Computational Tools for Chemical Toxicity Testing and Risk Assessment Under the Framework of Adverse Outcome Pathways
M. MUMTAZ*a, P. RUIZa AND Q. ZHANGb
We are exposed to hundreds of chemicals routinely, whether intentionally or unintentionally. That number increases each year as more chemicals are introduced in commerce and the world we live in. Chemical risk assessments estimate public health consequences from exposure to chemicals in the environment, workplace, and medicine. Traditional experimental determination of toxicity profiles using laboratory animals takes a great deal of time, money, and other resources. Classically, toxicity testing gathers data on set exposures
Issues in Toxicology No. 31
Computational Systems Pharmacology and Toxicology Edited by Dale E. Johnson and Rudy J. Richardson © The Royal Society of Chemistry 2017 Published by the Royal Society of Chemistry, www.rsc.org of 14 days, 90 days, and 2 years in animal bioassays. Increased access to and thorough analyses of these data during the past decade has brought a realization that the results have not significantly advanced quantitative assessment of chemical toxicity. These classical approaches were based on a coarse and rudimentary understanding of the mechanism of action(s) leading to toxicity; the amount of modern knowledge of biology and physiology used for risk assessment, particularly at the cellular and molecular levels, has been minimal.
In response to such concerns about classical toxicity testing approaches, efforts have been made on multiple fronts to develop alternatives. these alternative approaches would make best use of modern science. They also would be economical, efficient, humane, and informative to real-world human exposures. the National Academy of Sciences (NAS) proposed a revolutionary new approach, TT21C, published in 2007.1 NAS recommended rigorous investigations of perturbation of generally accepted toxicity pathways at the molecular and cellular levels. the interagency Coordination Committee on the Validation of alternative Methods authorization act, passed by the united States Congress in 2000, has authorized the adoption of tests that will also achieve the goal of humane treatment of animals by reducing, refining, and replacing animal toxicity testing.2 through these activities, toxicology is taking a more aggressive approach to overcome the paucity of data. toxicology now accesses a broad panel of in vitro assays that the drug discovery industry has been using for years.3 Several uS government agencies and organizations around the world are integrating these methods for high-throughput screening (HTS) of chemicals. noteworthy government-funded programs include the uS Environmental protection agency (EpA) toxicity ForeCaster (ToxCast) and toxicology in the 21st Century (Tox21). Registration, evaluation, authorisation, and restriction of Chemical substances (reach) is a European initiative that will generate experimental data at a pace never witnessed in the history of the toxicology. The advent of numerous in vitro methods, rapid increase in associated databases, and the advancement in data analysis tools of large data sets has allowed us to holistically view the toxicity assessment process in light of systems biology and toxicity pathway analysis. Through these means, we might then overcome the shortcomings of the animal toxicity testing protocols.4,s
Such thinking has led to the development of a new “adverse outcome pathway” (AOp) framework that covers the gamut of biological processes involved in risk assessment, from the exposure source to population and community impacts.6,y Through these strategy and approach developments, we see that computational tools based on biological mechanisms would play an increasingly large role in chemical risk assessment, hand-in-hand with novel ways of experimental interrogations of the underlying biological systems. Some of these computational tools needed to implement the AOp framework have been in use and improved over many years. Examples include quantitative structure-activity relationship and physiologically based pharmacokinetic (PBPK) modeling. Others, such as systems biology pathways modeling, are still emerging and being developed. AOPs piece together these various approaches under a single umbrella for a common cause. In this chapter, we give a brief introduction of the traditional quantitative approaches in risk assessment and how some of them can be adapted to the new AOp framework. We then focus on the computational tools for systems biology-based toxicity pathway modeling. These computational tools will be used to understand and predict cellular and tissue responses. they will be developed in conjunction with the animal-free movement of toxicity testing and risk assessment.