Mark Nelms

Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources

The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity (HTT) testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledge base; however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of HTT testing, thereby reducing the use of animals in toxicity testing and greatly increasing the number of chemicals that can be tested.

Development of an in Silico Profiler for Mitochondrial Toxicity.

This study outlines the analysis of mitochondrial toxicity for a variety of pharmaceutical drugs extracted from Zhang et al. ((2009) Toxicol. In Vitro, 23, 134-140). These chemicals were grouped into categories based upon structural similarity. Subsequently, mechanistic analysis was undertaken for each category to identify the molecular initiating event driving mitochondrial toxicity. The mechanistic information elucidated during the analysis enabled mechanism-based structural alerts to be developed and combined together to form an in silico profiler. This profiler is envisaged to be used to develop chemical categories based upon similar mechanisms as part of the adverse outcome pathway paradigm. Additionally, the profiler could be utilized in screening large data sets in order to identify chemicals with the potential to induce mitochondrial toxicity.

Proposal of an in silico profiler for categorisation of repeat dose toxicity data of hair dyes

This study outlines the analysis of 94 chemicals with repeat dose toxicity data taken from Scientific Committee on Consumer Safety opinions for commonly used hair dyes in the European Union. Structural similarity was applied to group these chemicals into categories. Subsequent mechanistic analysis suggested that toxicity to mitochondria is potentially a key driver of repeat dose toxicity for chemicals within each of the categories. The mechanistic hypothesis allowed for an in silico profiler consisting of four mechanism-based structural alerts to be proposed. These structural alerts related to a number of important chemical classes such as quinones, anthraquinones, substituted nitrobenzenes and aromatic azos. This in silico profiler is intended for grouping chemicals into mechanism-based categories within the adverse outcome pathway paradigm.

Experimental verification, and domain definition, of structural alerts for protein binding: epoxides, lactones, nitroso, nitros, aldehydes and ketones.

This study outlines how a combination of in chemico and Tetrahymena pyriformis data can be used to define the applicability domain of selected structural alerts within the profilers of the OECD QSAR Toolbox. Thirty-three chemicals were profiled using the OECD and OASIS profilers, enabling the applicability domain of six structural alerts to be defined, the alerts being: epoxides, lactones, nitrosos, nitros, aldehydes and ketones. Analysis of the experimental data showed the applicability domains for the epoxide, nitroso, aldehyde and ketone structural alerts to be well defined. In contrast, the data showed the applicability domains for the lactone and nitro structural alerts needed modifying. The accurate definition of the applicability domain for structural alerts within in silico profilers is important due to their use in the chemical category in predictive and regulatory toxicology. This study highlights the importance of utilizing multiple profilers in category formation.

Adverse Outcome Pathways to Support the Assessment of Chemical Mixtures

Due to the ever-increasing number of chemicals coming to market, and the cost of performing traditional in vivo studies, there has been a shift toward the use of less costly alternative techniques. The adverse outcome pathway (AOP) concept has emerged as a scaffold for organizing mechanistic information from these methods. Two main elements – key events (KEs) and key event relationships (KERs) – are utilized to describe the underlying mechanism outlined by the AOP. Each KE depicts the measureable changes in the state of the biological system at each level of organization that are essential for the progression along the pathway. The KERs, meanwhile, contain the biological information that connects each of the KEs. This chapter covers some of the potential applications for AOPs when performing risk assessment of chemical mixtures. The structure of the AOP provides much more precision when considering mechanistic data in a mixtures assessment. The use of this concept provides a means to allow more specificity when deciding whether to use dose addition, independent action or integrated addition risk assessment methodologies. Furthermore, AOPs enable novel approaches for determining chemical groups and how they may be utilized within mixtures risk assessment.

CHAPTER 4:Linking Environmental Exposure to Toxicity

As the number of chemicals and environmental toxicants in commerce continue to increase, so does the need to understand the links between exposure to these stressors and any potential toxic reactions. Assessing the impact of these stressors on public health as well as our environment requires an understanding of the underlying mechanistic processes connecting their introduction into the environment to the associated adverse outcomes.Traditional in vivo methods of toxicity testing have become too costly and inefficient. In recent times, in vitro high-throughput toxicity screening methods have been introduced to reduce the burden of in vivo testing and keep pace with the ever increasing number of required tests. The adverse outcome pathway (AOP) concept has been adopted by many in the toxicology community as a framework for linking the biological events that occur from the point of contact with these stressors and the resulting adverse outcome. This provides a mechanistic framework for understanding the potential impacts of perturbations that are measured via in vitro testing strategies. The aggregate exposure pathway (AEP) has been proposed as a companion framework to the AOP. The goal of the AEP is to describe the path the introduction of the stressor into the environment at its source to a target site within an individual that is comparable with the concentrations in the in vitro toxicity tests. Together, these frameworks provide a comprehensive view of the source to adverse outcome continuum.Standardizing our representation of the mechanistic information in this way allows for increased interoperability for computational models describing different parts of the system. It also aids in translating new research in exposure science and toxicology for risk assessors and decision makers when assessing the impact of specific stressors on endpoints of regulatory significance.