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Pharmaceutical Industry Practices on Genotoxic Impurities
A great deal of confusion and uncertainty over genotoxic impurity (GTI) identification, assessment, and control exists in the pharmaceutical industry today. Pharmaceutical Industry Practices on Genotoxic Impurities strives to facilitate scientific and systematic consensus on GTI management by presenting rationales, strategies, methods, interpretati
Drug Discovery and Evaluation
This book is a landmark in the continuously changing world of drugs. It is essential reading for scientists and managers in the pharmaceutical industry who are involved in drug finding, drug development and decision making in the development process.
Artificial Intelligence in Drug Design
This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.
Genetic Toxicology
Genetic Toxicology is a comprehensive book covering the historical perspective of genetic toxicology; basic mechanisms of mutations and chromosomal effects; health consequences of genetic damage, including cancer and inheritable mutations; properties of physical, chemical, and biological mutagens; risk assessment of human exposure to genotoxicants; and the current position of some government regulatory agencies in the United States on the issues of genetic toxicology. The book will be a useful reference for students and researchers in toxicology, genetics, cancer biology, and medicine who are interested in the basic and applied principles of genetic toxicology. It will also benefit industrial toxicologists, products registration specialists, and government regulatory specialists with responsibility for the safety evaluation of industrial and environmental agents.
Drug-Induced Liver Toxicity
This book provides a comprehensive view of the methodologies used for the study of liver toxicity encountered throughout the whole life cycle of a drug, from drug discovery, to clinical trial, post-marketing, and even clinical practice. Organized into six sections, the first section introduces the mechanisms contributing to drug-induced liver toxicity. The second and third section explore in silico and in vitro approaches used to help mitigate hepatotoxicity liability at the early stages of drug development. The fourth section describes methodologies applied in regulatory processes, including preclinical studies, clinical trials, and post-marketing surveillance. The fifth section discusses clinical hepatotoxicity. Emerging technologies are examined in the final section. As a volume in the Methods in Pharmacology and Toxicology series, chapters include the kind of expert advice that will lead to optimal results. Authoritative and practical, Drug-Induced Liver Toxicity serves all those who aim to improve assessment and understanding of hepatotoxic potentials of new medications and marketed drugs. Chapter 30 is open access under a CC BY 4.0 license via link.springer.com.
Advances in Computational Toxicology
This book provides a comprehensive review of both traditional and cutting-edge methodologies that are currently used in computational toxicology and specifically features its application in regulatory decision making. The authors from various government agencies such as FDA, NCATS and NIEHS industry, and academic institutes share their real-world experience and discuss most current practices in computational toxicology and potential applications in regulatory science. Among the topics covered are molecular modeling and molecular dynamics simulations, machine learning methods for toxicity analysis, network-based approaches for the assessment of drug toxicity and toxicogenomic analyses. Offering a valuable reference guide to computational toxicology and potential applications in regulatory science, this book will appeal to chemists, toxicologists, drug discovery and development researchers as well as to regulatory scientists, government reviewers and graduate students interested in this field.
