Toxicogenomics Based Cellular Models

Toxicogenomics-Based Cellular Models is a unique and valuable reference for all academic and professional researchers employing toxicogenomic methods with respect to animal testing for chemical safety. This resource offers cutting-edge information on the application of toxicogenomics to developing alternatives to current animal toxicity tests. By illustrating the development of toxicogenomics-based cellular models for critical endpoints of toxicity and providing real-world examples for validation and data analysis, this book provides an assessment of the current state of the field, as well as opportunities and challenges for the future. Written by renowned international toxicological experts, this book explores ‘omics technology for developing new assays for toxicity testing and safety assessment and provides the reader with a focused examination of alternative means to animal testing. Describes the state-of-the-art in developing toxicogenomics-based cellular models for chemical-induced carcinogenicity, immunotoxicity, developmental toxicity, neurotoxicity and reproduction toxicity Illustrates how to validate toxicogenomics-based alternative test models and provides an outlook to societal and economic implementation of these novel assays Includes an overview of current testing methods and risk assessment frameworks Provides a real-world assessment by articulating the current development and challenges in toxicogenomics while suggesting ways to move this field forward

The new field of toxicogenomics presents a potentially powerful set of tools to better understand the health effects of exposures to toxicants in the environment. At the request of the National Institute of Environmental Health Sciences, the National Research Council assembled a committee to identify the benefits of toxicogenomics, the challenges to achieving them, and potential approaches to overcoming such challenges. The report concludes that realizing the potential of toxicogenomics to improve public health decisions will require a concerted effort to generate data, make use of existing data, and study data in new waysâ€"an effort requiring funding, interagency coordination, and data management strategies.

Describes toxicogenomics methods in predictive carcinogenicity testing and cancer risk assessment. Addresses the use of stem cells and bioinformatics in toxicogenomics. For postgraduates, academics and industrialists.

The meteoric rate at which the human genome is being sequenced has presented to the research community a vast array of newly discovered genes, which in tum has catalyzed an even more dramatic effort to decipher this voluminous data set into understanding how genes function both individually and in complex pathways that regulate the biochemistry of life. A compendium of gene expression data, enhanced by complete proteomic analysis, will enable investigators to probe into the complexities of the mechanisms of normal genetic and metabolic pathways and, subsequently, how disease occurs when they malfunction. The new science of toxicogenomics combines genomic, proteomic, and informatics technologies, and biological research can now foresee a time when there will be a full comprehension of the complex dynamic mechanisms of genetics, biochemistry, and physiology. The inherent power of toxicogenomics derives from an amalgamation of multiple scientific disciplines that were originally drawn together to facilitate sequencing the three billion bases that comprise the human genome. Traditionally, the science of toxicology has been founded upon empirical codification of dose-related effects. It has evolved to studies that are directed towards understanding the mechanisms by which individual agents cause their effects in humans. Due to technical limitations, this process has been relatively slow, since it has accomplished one chemical or one effect at a time.

Toxicogenomics was established as a merger of toxicology with genomics approaches and methodologies more than 15 years ago, and considered of major value for studying toxic mechanisms-of-action in greater depth and for classification of toxic agents for predicting adverse human health risks. While the original focus was on technological validation of in particular microarray-based whole genome expression analysis (transcriptomics), mainly through cross-comparing different platforms for data generation (MAQC-I), it was soon appreciated that actually the wide variety of data analysis approaches represents the major source of inter-study variation. This led to early attempts towards harmonizing data analysis protocols focusing on microarray-based models for predicting toxicological and clinical end-points and on different methods for GWAS data (MAQC-II). Simultaneously, further technological developments, geared by increasing insights into the complexity of cellular regulation, enabled analyzing molecular perturbations across multiple genomics scales (epigenomics and microRNAs, metabolomics). While these were initially still based on microarray technology, this is currently being phased out and replaced by a variety of next generation sequencing-based methods enabling exploration of genomic responses to toxicants at even greater depth (SEQC-I). This raises the demand for reliable and robust data analysis approaches, ranging from harmonized bioinformatics concepts for preprocessing raw data to non-supervised and supervised methods for capturing and integrating the dynamic perturbations of cell function across dose and time, and thus retrieving mechanistic insights across multiple regulation scales. Traditional toxicology focused on dose-dependently determining apical endpoints of toxicity. With the advent of toxicogenomics, efforts towards better understanding underlying molecular mechanisms has led to the development of the concept of Adverse Outcome Pathways, which are basically presented as a structural network of linearly related gene-gene interactions regulating key events for inducing apical toxic endpoints of interest. Impulse challenges from exposure of biological systems to toxic agents will however induce a cascade-type of events, presenting both adverse and adaptive processes, thus requiring bioinformatics approaches and methods for complex dynamic data, generated not only across dose, but clearly also across time. Currently, time-resolved toxicogenomics data sets are increasingly being assembled in the course of large-scaled research projects, for instance devoted towards developing toxicogenomics-based predictive assays for evaluating chemical safety which are no longer animal-based.

This new fifth edition of Information Resources in Toxicology offers a consolidated entry portal for the study, research, and practice of toxicology. Both volumes represents a unique, wide-ranging, curated, international, annotated bibliography, and directory of major resources in toxicology and allied fields such as environmental and occupational health, chemical safety, and risk assessment. The editors and authors are among the leaders of the profession sharing their cumulative wisdom in toxicology’s subdisciplines. This edition keeps pace with the digital world in directing and linking readers to relevant websites and other online tools. Due to the increasing size of the hardcopy publication, the current edition has been divided into two volumes to make it easier to handle and consult. Volume 1: Background, Resources, and Tools, arranged in 5 parts, begins with chapters on the science of toxicology, its history, and informatics framework in Part 1. Part 2 continues with chapters organized by more specific subject such as cancer, clinical toxicology, genetic toxicology, etc. The categorization of chapters by resource format, for example, journals and newsletters, technical reports, organizations constitutes Part 3. Part 4 further considers toxicology’s presence via the Internet, databases, and software tools. Among the miscellaneous topics in the concluding Part 5 are laws and regulations, professional education, grants and funding, and patents. Volume 2: The Global Arena offers contributed chapters focusing on the toxicology contributions of over 40 countries, followed by a glossary of toxicological terms and an appendix of popular quotations related to the field. The book, offered in both print and electronic formats, is carefully structured, indexed, and cross-referenced to enable users to easily find answers to their questions or serendipitously locate useful knowledge they were not originally aware they needed. Among the many timely topics receiving increased emphasis are disaster preparedness, nanotechnology, -omics, risk assessment, societal implications such as ethics and the precautionary principle, climate change, and children’s environmental health. Introductory chapters provide a backdrop to the science of toxicology, its history, the origin and status of toxicoinformatics, and starting points for identifying resources Offers an extensive array of chapters organized by subject, each highlighting resources such as journals, databases,organizations, and review articles Includes chapters with an emphasis on format such as government reports, general interest publications, blogs, and audiovisuals Explores recent internet trends, web-based databases, and software tools in a section on the online environment Concludes with a miscellany of special topics such as laws and regulations, chemical hazard communication resources, careers and professional education, K-12 resources, funding, poison control centers, and patents Paired with Volume Two, which focuses on global resources, this set offers the most comprehensive compendium of print, digital, and organizational resources in the toxicological sciences with over 120 chapters contributions by experts and leaders in the field

The rate at which toxicological data is generated is continually becoming more rapid and the volume of data generated is growing dramatically. This is due in part to advances in software solutions and cheminformatics approaches which increase the availability of open data from chemical, biological and toxicological and high throughput screening resources. However, the amplified pace and capacity of data generation achieved by these novel techniques presents challenges for organising and analysing data output. Big Data in Predictive Toxicology discusses these challenges as well as the opportunities of new techniques encountered in data science. It addresses the nature of toxicological big data, their storage, analysis and interpretation. It also details how these data can be applied in toxicity prediction, modelling and risk assessment. This title is of particular relevance to researchers and postgraduates working and studying in the fields of computational methods, applied and physical chemistry, cheminformatics, biological sciences, predictive toxicology and safety and hazard assessment.