Pathway-Based Toxicity: History, Current Approaches and Liver Fibrosis and Steatosis as Prototypes

The Human Toxicology Project Consortium (HTPC) was created to accelerate implementation of the science and policies required to achieve a pathway-based foundation for toxicology as articulated in the 2007 National Research Council report, Toxicity Testing in the 21st Century: a Vision and a Strategy. The HTPC held a workshop, “Building Shared Experience to Advance Practical Application of Pathway-Based Toxicology: Liver Toxicity Mode-of-Action,” in January, 2013, in Baltimore, MD, to further the science of pathway-based approaches to liver toxicity. This review was initiated as a thought-starter for this workshop and has since been updated to include insights from the workshop and other activities occurring in 2013. The report of the workshop has been published elsewhere in this journal (Willett, 2014).JRC.I.5-Systems Toxicolog

Alternative methods for regulatory toxicology – a state-of-the-art review

This state-of-the art review is based on the final report of a project carried out by the European Commission’s Joint Research Centre (JRC) for the European Chemicals Agency (ECHA). The aim of the project was to review the state of the science of non-standard methods that are available for assessing the toxicological and ecotoxicological properties of chemicals. Non-standard methods refer to alternatives to animal experiments, such as in vitro tests and computational models, as well as animal methods that are not covered by current regulatory guidelines. This report therefore reviews the current scientific status of non-standard methods for a range of human health and ecotoxicological endpoints, and provides a commentary on the mechanistic basis and regulatory applicability of these methods. For completeness, and to provide context, currently accepted (standard) methods are also summarised. In particular, the following human health endpoints are covered: a) skin irritation and corrosion; b) serious eye damage and eye irritation; c) skin sensitisation; d) acute systemic toxicity; e) repeat dose toxicity; f) genotoxicity and mutagenicity; g) carcinogenicity; h) reproductive toxicity (including effects on development and fertility); i) endocrine disruption relevant to human health; and j) toxicokinetics. In relation to ecotoxicological endpoints, the report focuses on non-standard methods for acute and chronic fish toxicity. While specific reference is made to the information needs of REACH, the Biocidal Products Regulation and the Classification, Labelling and Packaging Regulation, this review is also expected to be informative in relation to the possible use of alternative and non-standard methods in other sectors, such as cosmetics and plant protection products.JRC.I.5-Systems Toxicolog

Advanced in vitro models for studying drug induced toxicity

Bringing safe medicines to the market has remained a major challenge to the pharmaceutical industry. Recent years have seen increased drug attrition rates due to toxicity - even after rigorous testing in both in vitro and in vivo test models. This is partly due to poor prediction of human-specific responses in these models. This thesis aims to address the issue by developing advanced in vitro models and methods that can complement and improve the predictive power of in vitro assays at preclinical level. Liver and kidneys are often susceptible to drug insult due to their respective roles in drug metabolism and reabsorption. We have developed a robust 3D in vitro model for liver toxicity studies, this model shows many hallmarks of in vivo hepatocytes, is applied in a 384-micro-well format and is compatible with standard medium- and high-throughput lab infrastructure for routine drug screening. This thesis also discusses the role of immune mediators in aggravating kidney toxicity and use of sophisticated high-content screening approach to measure apoptosis and necrosis in real time. These models are promising new tools for preclinical drug safety testingNetherlands Toxicogenomics centre (NTC) via Netherlands Genomics InitiativeUBL - phd migration 201

Novel in vitro and mathematical models for the prediction of chemical toxicity

The focus of much scientific and medical research is directed towards understanding the disease process and defining therapeutic intervention strategies. Whilst the scientific basis of drug safety has received relatively little attention, despite the fact that adverse drug reactions (ADRs) are a major health concern and a serious impediment to development of new medicines. Toxicity issues account for ~21% drug attrition during drug development and safety testing strategies require considerable animal use. Mechanistic relationships between drug plasma levels and molecular/cellular events that culminate in whole organ toxicity underpins development of novel safety assessment strategies. Current in vitro test systems are poorly predictive of toxicity of chemicals entering the systemic circulation, particularly to the liver. Such systems fall short because of 1) the physiological gap between cells currently used & human hepatocytes existing in their native state, 2) the lack of physiological integration with other cells/systems within organs, required to amplify the initial toxicological lesion into overt toxicity, 3) the inability to assess how low level cell damage induced by chemicals may develop into overt organ toxicity in a minority of patients, 4) lack of consideration of systemic effects. Reproduction of centrilobular & periportal hepatocyte phenotypes in in vitro culture is crucial for sensitive detection of cellular stress. Hepatocyte metabolism/phenotype is dependent on cell position along the liver lobule, with corresponding differences in exposure to substrate, oxygen & hormone gradients. Application of bioartificial liver (BAL) technology can encompass in vitro predictive toxicity testing with enhanced sensitivity and improved mechanistic understanding. Combining this technology with mechanistic mathematical models describing intracellular metabolism, fluid-­‐flow, substrate, hormone and nutrient distribution provides the opportunity to design the BAL specifically to mimic the in vivo scenario. Such mathematical models enable theoretical hypothesis testing, will inform the design of in vitro experiments, and will enable both refinement and reduction of in vivo animal trials. In this way, development of novel mathematical modelling tools will help to focus and direct in vitro and in vivo research, and can be used as a framework for other areas of drug safety science

Annotating Adverse Outcome Pathways to Organize Toxicological Information for Risk Assessment

The Adverse Outcome Pathway (AOP) framework connects molecular perturbations with organism and population level endpoints used for regulatory decision-making by providing a conceptual construct of the mechanistic basis for toxicity. Development of an AOP typically begins with the adverse outcome, and intermediate effects connect the outcome with a molecular initiating event amenable to high-throughput toxicity testing (HTT). Publicly available controlled vocabularies were used to provide terminology supporting AOP’s at all levels of biological organization. The resulting data model contains terms from 22 ontologies and controlled vocabularies annotating currently existing AOP’s. The model provides the ability to attach evidence in support of the AOP, supports data aggregation, and promotes the development of AOP networks. Long term, this structured description of the AOP will enable logical reasoning for hazard identification and for dose-response assessment. Case studies showcase how the model informs AOP development in the context of chemical risk assessment.Master of Scienc

Toxicity prediction using multi-disciplinary data integration and novel computational approaches

Current predictive tools used for human health assessment of potential chemical hazards rely primarily on either chemical structural information (i.e., cheminformatics) or bioassay data (i.e., bioinformatics). Emerging data sources such as chemical libraries, high throughput assays and health databases offer new possibilities for evaluating chemical toxicity as an integrated system and overcome the limited predictivity of current fragmented efforts; yet, few studies have combined the new data streams. This dissertation tested the hypothesis that integrative computational toxicology approaches drawing upon diverse data sources would improve the prediction and interpretation of chemically induced diseases. First, chemical structures and toxicogenomics data were used to predict hepatotoxicity. Compared with conventional cheminformatics or toxicogenomics models, interpretation was enriched by the chemical and biological insights even though prediction accuracy did not improve. This motivated the second project that developed a novel integrative method, chemical-biological read-across (CBRA), that led to predictive and interpretable models amenable to visualization. CBRA was consistently among the most accurate models on four chemical-biological data sets. It highlighted chemical and biological features for interpretation and the visualizations aided transparency. Third, we developed an integrative workflow that interfaced cheminformatics prediction with pharmacoepidemiology validation using a case study of Stevens Johnson Syndrome (SJS), an adverse drug reaction (ADR) of major public health concern. Cheminformatics models first predicted potential SJS inducers and non-inducers, prioritizing them for subsequent pharmacoepidemiology evaluation, which then confirmed that predicted non-inducers were statistically associated with fewer SJS occurrences. By combining cheminformatics' ability to predict SJS as soon as drug structures are known, and pharmacoepidemiology's statistical rigor, we have provided a universal scheme for more effective study of SJS and other ADRs. Overall, this work demonstrated that integrative approaches could deliver more predictive and interpretable models. These models can then reliably prioritize high risk chemicals for further testing, allowing optimization of testing resources. A broader implication of this research is the growing role we envision for integrative methods that will take advantage of the various emerging data sources.Doctor of Philosoph

Pluripotent Stem Cell Biology

Pluripotent stem cells have the potential to revolutionize treatment options for a range of diseases and conditions. This book presents recent advances in our understanding of the biological mechanisms of stem cell self-renewal, reprograming and regeneration. Also covered are novel methodological advances in the culture, purification and use of stem cells, as well as the ethical and moral dilemmas of embryo donation and adoption. These advances will shape the utilization of stem cells for future basic and applied applications