Predictive data science is already in use in many fields, but its application in toxicology is new and sought after by non-animal alternative testing initiatives. Predictive Analytics for Toxicology: Applications in Discovery Science provides a comprehensive overview of the application of predictive analytics in the field of toxicology, highlighting its role and applications in discovery science. This book addresses the challenges of accurately predicting high-level endpoints of toxicity and explores the use of computational and artificial intelligence research to automate predictive toxicology. It underscores the importance of predictive toxicology in proposing and explaining adverse outcomes resulting from human exposures to specific toxicants, especially when experimental and observational data on the toxicant are incomplete or unavailable. Key features: Includes a plain language description of predictive analytics in toxicology adding an overview of the wide range of applications Examines the science of prediction, computational models as an automated science and comprehensive discussions on concepts of machine learning Opens the hood on AI and its applications in toxicology Features coverage on how in silico toxicity predictions are translational science tools The book integrates strategies and practices of predictive toxicology and offers practical information that students and professionals of the toxicology, chemical, and pharmaceutical industries will find essential. It fulfills the expectations of student researchers seeking to learn predictive analytics in toxicology. This book will energize scientists to conduct predictive toxicology modeling using artificial intelligence and machine learning, and inspire students and seasoned scientists interested in automated science to pick up new research using predictive in silico models to evaluate chemical-induced toxicity. With its focus on practical applications and real-world examples, this book serves as a guide for navigating the complex issues and practices of discovery toxicology. It is an essential resource for those interested in computer-based methods in toxicology, providing valuable insights into the use of predictive analytics.

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.

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

This book is a collection of machine learning and deep learning algorithms, methods, architectures, and software tools that have been developed and widely applied in predictive toxicology. It compiles a set of recent applications using state-of-the-art machine learning and deep learning techniques in analysis of a variety of toxicological endpoint data. The contents illustrate those machine learning and deep learning algorithms, methods, and software tools and summarise the applications of machine learning and deep learning in predictive toxicology with informative text, figures, and tables that are contributed by the first tier of experts. One of the major features is the case studies of applications of machine learning and deep learning in toxicological research that serve as examples for readers to learn how to apply machine learning and deep learning techniques in predictive toxicology. This book is expected to provide a reference for practical applications of machine learning and deep learning in toxicological research. It is a useful guide for toxicologists, chemists, drug discovery and development researchers, regulatory scientists, government reviewers, and graduate students. The main benefit for the readers is understanding the widely used machine learning and deep learning techniques and gaining practical procedures for applying machine learning and deep learning in predictive toxicology.

Toxicology is the scientific study of the adverse effects of chemical substances on living organisms. It encompasses a broad range of disciplines, including biology, chemistry, pharmacology, and environmental science, and is essential for understanding the impact of toxins on human health and the environment. The origins of toxicology can be traced back to ancient civilizations, where herbal remedies and poisons were used in medicine and warfare. Over the centuries, this field has evolved significantly, particularly with advancements in analytical techniques and a greater understanding of biological systems. The fundamental principle of toxicology is that the effect of a substance depends not only on its inherent toxicity but also on the dose, duration of exposure, and the route by which it enters the body. This is often summarized by the phrase "the dose makes the poison," attributed to the Swiss physician Paracelsus in the 16th century. Paracelsus emphasized that even substances considered beneficial can be harmful in excessive amounts, highlighting the importance of understanding dosage in toxicological assessments.

The History of Alternative Test Methods in Toxicology uses a chronological approach to demonstrate how the use of alternative methods has evolved from their conception as adjuncts to traditional animal toxicity tests to replacements for them. This volume in the History of Toxicology and Environmental Health series explores the history of alternative test development, validation, and use, with an emphasis on humanity and good science, in line with the Three Rs (Replacement,Reduction, Refinement) concept expounded by William Russell and Rex Burch in 1959 in their now classic volume, The Principles of Humane Experimental Technique. The book describes the historical development of technologies that have influenced the application of alternatives in toxicology and safety testing. These range from single cell monocultures to sophisticated, miniaturised and microfluidic organism-on-a-chip devices, and also include molecular modelling, chemoinformatics and QSAR analysis, and the use of stem cells, tissue engineering and hollow fibre bioreactors. This has been facilitated by the wider availability of human tissues, advances in tissue culture, analytical and diagnostic methods, increases in computational processing, capabilities, and a greater understanding of cell biology and molecular mechanisms of toxicity. These technological developments have enhanced the range and information content of the toxicity endpoints detected, and therefore the relevance of test systems and data interpretation, while new techniques for non-invasive diagnostic imaging and high resolution detection methods have permitted an increased role for human studies. Several key examples of how these technologies are being harnessed to meet 21st century safety assessment challenges are provided, including their deployment in integrated testing schemes in conjunction with kinetic modelling, and in specialized areas, such as inhalation toxicity studies. The History of Alternative Test Methods in Toxicology uses a chronological approach to demonstrate how the use of alternative methods has evolved from their conception as adjuncts to traditional animal toxicity tests to replacements for them. This volume in the History of Toxicology and Environmental Health series explores the history of alternative test development, validation, and use, with an emphasis on humanity and good science, in line with the Three Rs (Replacement, Reduction, Refinement) concept expounded by William Russell and Rex Burch in 1959 in their now-classic volume, The Principles of Humane Experimental Technique. The book describes the historical development of technologies that have influenced the application of alternatives in toxicology and safety testing. These range from single cell monocultures to sophisticated miniaturised and microfluidic organism-on-a-chip devices, and also include molecular modelling, chemoinformatics and QSAR analysis, and the use of stem cells, tissue engineering and hollow fibre bioreactors. This has been facilitated by the wider availability of human tissues, advances in tissue culture, analytical and diagnostic methods, increases in computational processing capabilities, and a greater understanding of cell biology and molecular mechanisms of toxicity. These technological developments have enhanced the range and information content of the toxicity endpoints detected, and therefore the relevance of test systems and data interpretation, while new techniques for non-invasive diagnostic imaging and high resolution detection methods have permitted an increased role for human studies. Several key examples of how these technologies are being harnessed to meet 21st century safety assessment challenges are provided, including their deployment in integrated testing schemes in conjunction with kinetic modelling, and in specialised areas, such as inhalation toxicity studies.

Toxicological Risk Assessment and Multisystem Health Impacts From Exposure highlights the emerging problems of human and environmental health attributable to cumulative and multiple sources of long-term exposure to environmental toxicants. The book describes the cellular, biological, immunological, endocrinologic, genetic, and epigenetic effects of long-term exposure. It examines how the combined exposure to nanomaterials, metals, pharmaceuticals, multifrequency radiation, dietary mycotoxins, and pesticides accelerates ecotoxicity in humans, animals, plants, and the larger environment. The book goes on to also offer insights into mixture risk assessments, protocols for evaluating the risks, and how this information can serve the regulatory agencies in setting safer exposure limits. The book is a go-to resource for scientists and professionals in the field tackling the current and emerging trends in modern toxicology and risk assessment. - Bridges basic research with clinical, epidemiological, regulatory, and translational research, conveying both an introductory understanding and the latest developments in the field - Evaluates real-life human health risk assessment for long-term exposures to xenobiotic mixtures and the role they play in contributing to chronic disease - Discusses advances in predictive (in silico) toxicology tools and the benefits of using omics technologies in toxicology research

Big Data Analytics in Chemoinformatics and Bioinformatics: With Applications to Computer-Aided Drug Design, Cancer Biology, Emerging Pathogens and Computational Toxicology provides an up-to-date presentation of big data analytics methods and their applications in diverse fields. The proper management of big data for decision-making in scientific and social issues is of paramount importance. This book gives researchers the tools they need to solve big data problems in these fields. It begins with a section on general topics that all readers will find useful and continues with specific sections covering a range of interdisciplinary applications. Here, an international team of leading experts review their respective fields and present their latest research findings, with case studies used throughout to analyze and present key information. - Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain - Covers many applications of big data analysis in diverse fields such as chemistry, chemoinformatics, bioinformatics, computer-assisted drug/vaccine design, characterization of emerging pathogens, and environmental protection - Highlights the considerable benefits offered by big data analytics to science, in biomedical fields and in industry

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

A complete handbook on toxicology covers basic principles, regulatory criteria, and sophisticated methods for understanding and assuring the safety of varied chemicals in the following pages. Introduction to toxicology, "Toxicology Fundamentals and Regulatory Guidelines," covers broad overviews, mechanistic toxicology, regulatory frameworks, and descriptive toxicology. Focus is on OECD, ICH, EPA, and Schedule Y regulatory criteria, as well as the history and importance of Good Laboratory Practise (GLP) in drug development. As the book explores "Types of Toxicity Studies and Test Item Characterization," it examines acute, sub-acute, chronic, and particular acute investigations, including oral, cutaneous, and inhalational toxicity studies. Test item characterisation procedures are carefully explained, emphasising their importance in regulatory compliance and toxicity evaluation. This leads to "Advanced Toxicology Studies," which covers reproductive toxicology, genotoxicity, and in vivo carcinogenicity. These investigations provide a thorough view of possible dangers and evaluate drug safety. The book then discusses "IND Enabling Studies and Safety Pharmacology," which covers the necessary research for IND applications. Exploring regulatory settings, corporate views, and safety pharmacology in drug development provides a complete knowledge of experimental substance safety. The third part, "Toxicokinetic and Alternatives to Animal Testing," emphasises toxicokinetic assessment and discusses new methods. Following the evolution of safety assessment practises, these options are investigated for ethical and regulatory consequences. Students, researchers, and professionals traversing toxicology's difficult landscape may find this book invaluable. Its extensive coverage, from basic concepts to sophisticated approaches, makes it an important tool for protecting humans and ecosystems in the dynamic pharmaceuticals and beyond industries.