In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR

A plethora of databases exist online that can assist in in silico chemical or drug safety assessment. However, a systematic review and grouping of databases, based on purpose and information content, consolidated in a single source has been lacking. To resolve this issue, this review provides a comprehensive listing of the key in silico data resources relevant to: chemical identity and properties, drug action, toxicology (including nano-material toxicity), exposure, omics, pathways, Absorption, Distribution, Metabolism and Elimination (ADME) properties, clinical trials, pharmacovigilance, patents-related databases, biological (genes, enzymes, proteins, other macromolecules etc.) databases, protein-protein interactions (PPIs), environmental exposure related, and finally databases relating to animal alternatives in support of 3Rs policies. More than nine hundred databases were identified and reviewed against criteria relating to accessibility, data coverage, interoperability or application programming interface (API), appropriate identifiers, types of in vitro-in vivo -clinical data recorded and suitability for modelling, read-across or similarity searching. This review also specifically addresses the need for solutions for mapping and integration of databases into a common platform for better translatability of preclinical data to clinical data

Computational hypothesis generation with genome-side metabolic reconstructions: in-silico prediction of metabolic changes in the freshwater model organism Daphnia to environmental stressors

Computational toxicology is an emerging, multidisciplinary field that uses in-silico modelling techniques to predict and understand how biological organisms interact with pollutants and environmental stressors. Genome-wide metabolic reconstruction (GWMR) is an in-silico modelling technique that aims to represent the metabolic capabilities of an organism. Daphnia is an emerging model species for environmental omics whose underlying biology is still being uncovered. Creating a metabolic reconstruction of Daphnia and applying it in an environmental computational toxicology setting has the potential to aid in understanding its interaction with environmental stressors. Here, the fist GWMR of D. magna is presented, which is built using METRONOME, a newly developed tool for automated GWMR of new genome sequences. Active module identification allows for omics data sets to be integrated into in-silico models and uses optimisation algorithms to find hot-spots within networks that represent areas that are significantly impacted based on a toxicogenomic transcriptomics dataset. Here, a method that uses the active modules approach in a predictive capacity for computational hypothesis generation is introduced to predict unknown metabolic responses to environmentally relevant human-induced stressors. A computational workflow is presented that takes a new genome sequence, builds a GWMR and integrates gene expression data to make predictions of metabolic effects. The aim is to introduce an element of hypothesis generation into the untargeted metabolomics experimental workflow. A study to validate this approach using D. magna as the target organism is presented, which uses untargeted Liquid-Chromatography Mass Spectrometry (LC-MS) to make metabolomics measurements. A software tool MUSCLE is presented that uses multi-objective closed-loop evolutionary optimisation to automatically develop LC-MS instrument methods and is used here to develop the analytical method

Vaccine semantics : Automatic methods for recognizing, representing, and reasoning about vaccine-related information

Post-marketing management and decision-making about vaccines builds on the early detection of safety concerns and changes in public sentiment, the accurate access to established evidence, and the ability to promptly quantify effects and verify hypotheses about the vaccine benefits and risks. A variety of resources provide relevant information but they use different representations, which makes rapid evidence generation and extraction challenging. This thesis presents automatic methods for interpreting heterogeneously represented vaccine information. Part I evaluates social media messages for monitoring vaccine adverse events and public sentiment in social media messages, using automatic methods for information recognition. Parts II and III develop and evaluate automatic methods and res

Systems Toxicology: Beyond Animal Models

Toxicology – much like the rest of biology – is undergoing a profound change as new technologies begin to offer a more systems oriented view of cellular physiology. For toxicology in particular, this means moving away from black-box animal models that provide limited information about mechanisms of toxicity towards the use of in vitro approaches which can both expedite hazard assessment while at the same time providing a more data –rich insight into toxic effects at the molecular level. One motivator of this shift is Green Toxciology, which seeks to support the Green Chemistry movement. In order for this approach to succeed, it will require two separate but parallel efforts. The first is an Integrated Testing Strategy which seeks to use machine learning and data mining techniques to combine QSARs and in vitro tests in the most efficient way possible to accurately estimate hazard, which is discussed both theoretically and demonstrated practically with the example of skin sensitization. Secondly, toxicology will require new approaches that exploit the insights of network biology to look at toxic mechanisms from a systems perspective. The theoretical concept of a Pathway of Toxicity is outlined, and an example of how to extract a suggested Pathway of Toxicity is given, using a Weighted Gene Correlation Network Analysis of a small microarray study of MPTP toxicity combined with text-mining and other high-throughput data to suggest novel candidate transcription factors and proteins. In conclusion, it discusses some of the current limitations of another promising –omics technology, metabolomics

Inside the sequence universe: the amazing life of data and the people who look after them

This thesis provides an ethnographic exploration of two large nucleotide sequence databases, the European Molecular Biology Laboratory Bank, UK and GenBank, US. It describes and analyses their complex bioinformatic environments as well as their material-discursive environments – the objects, narratives and practices that recursively constitute these databases. In doing so, it unravels a rich bioinformational ecology – the “sequence universe”. Here, mosquitoes have mumps, the louse is “huge” and self-styled information plumbers patch-up high-throughput data pipelines while data curators battle the indiscriminate coming-to-life caused by metagenomics. Given the intensification of data production, the biosciences have reached a point where concerns have squarely turned to fundamental questions about how to know within and between all that data. This thesis assembles a database imaginary, recovering inventive terms of scholarly engagement with bioinformational databases and data, terms that remain critical without necessarily reverting to a database logic. Science studies and related disciplines, investigating illustrious projects like the UK Biobank, have developed a sustained critique of the perceived conflation of bodies and data. This thesis argues that these accounts forego an engagement with the database sui generis, as a situated arrangement of people, things, routines and spaces. It shows that databases have histories and continue established practices of collecting and curating. At the same time, it maps entanglements of the databases with experiments and discovery thereby demonstrates the vibrancy of data. Focusing on the question of what happens at these databases, the thesis follows data curators and programmers but also database records and the entities documented by them, such as uncultured bacteria. It contextualises ethnographic findings within the literature on the sociology and philosophy of science and technology while also making references to works of art and literature in order to bring into relief the boundary-defying scope of the issues raised