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This book introduces “network pharmacology” as an emerging frontier subject of systematic drug research in the era of artificial intelligence and big data. Network Pharmacology is an original subject of fusion system biology, bioinformatics, network science and other related disciplines. It emphasizes on starting from the overall perspective of the system level and biological networks, the analysis of the laws of molecular association between drugs and their treatment objects, reveals the systematic pharmacological mechanisms of drugs, and guides the research and development of new drugs and clinical diagnosis and treatment. After it was proposed, network pharmacology has been paid attention by researchers, and it has been rapidly developed and widely used. In order to systematically reveal the biological basis of diagnosis and treatment in traditional Chinese medicine and modern medicine, we proposed a new concept of "network target" for the first time, which has become the core theory of "network pharmacology". The core principle of a network target is to construct a biological network that can be used to decipher complex diseases. The network is then used as the therapeutic target, to which multicomponent remedies are applied. This book mainly includes four parts: 1) The concept and theory of network pharmacology; 2) Common analysis methods, databases and software in network pharmacological research; 3) Typical cases of traditional Chinese medicine modernization and modern drug research based on network pharmacology; 4) Network pharmacology practice process based on drugs and diseases.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Fully updated and rewritten by a basic scientist who is also a practicing physician, the third edition of this popular textbook remains comprehensive, authoritative and readable. Taking a receptor-based, target-centered approach, it presents the concepts central to the study of drug action in a logical, mechanistic way grounded on molecular and principles. Students of pharmacy, chemistry and pharmacology, as well as researchers interested in a better understanding of drug design, will find this book an invaluable resource. Starting with an overview of basic principles, Medicinal Chemistry examines the properties of drug molecules, the characteristics of drug receptors, and the nature of drug-receptor interactions. Then it systematically examines the various families of receptors involved in human disease and drug design. The first three classes of receptors are related to endogenous molecules: neurotransmitters, hormones and immunomodulators. Next, receptors associated with cellular organelles (mitochondria, cell nucleus), endogenous macromolecules (membrane proteins, cytoplasmic enzymes) and pathogens (viruses, bacteria) are examined. Through this evaluation of receptors, all the main types of human disease and all major categories of drugs are considered. There have been many changes in the third edition, including a new chapter on the immune system. Because of their increasingly prominent role in drug discovery, molecular modeling techniques, high throughput screening, neuropharmacology and genetics/genomics are given much more attention. The chapter on hormonal therapies has been thoroughly updated and re-organized. Emerging enzyme targets in drug design (e.g. kinases, caspases) are discussed, and recent information on voltage-gated and ligand-gated ion channels has been incorporated. The sections on antihypertensive, antiviral, antibacterial, anti-inflammatory, antiarrhythmic, and anticancer drugs, as well as treatments for hyperlipidemia and peptic ulcer, have been substantially expanded. One new feature will enhance the book's appeal to all readers: clinical-molecular interface sections that facilitate understanding of the treatment of human disease at a molecular level.
Despite considerable technological advances, the pharmaceutical industry is experiencing a severe innovation deficit, especially in the discovery of new drugs. Innovative Approaches in Drug Discovery: Ethnopharmacology, Systems Biology and Holistic Targeting provides a critical review and analysis of health, disease and medicine, and explores possible reasons behind the present crisis in drug discovery. The authors illustrate the benefits of systems biology and pharmacogenomics approaches, and advocate the expansion from disease-centric discovery to person-centric therapeutics involving holistic, multi-target, whole systems approaches. This book lays a path for reigniting pharmaceutical innovation through a disciplined reemergence of pharmacognosy, embracing open innovation models and collaborative, trusted public-private partnerships. With unprecedented advances made in the development of biomedically-relevant tools and technologies, the need is great and the time is now for a renewed commitment towards expanding the repertoire of medicines. By incorporating real-life examples and state-of-the-art reviews, this book provides valuable insights into the discovery and development strategies for professionals, academicians, and students in the pharmaceutical sciences. - Analyzes the reasons behind historical drug failures to provide valuable insights on lessons learned - Uses current scientific research to promote learning from traditional knowledge systems and through the integration of traditional and western medicines - Discusses advances in technologies and systems biology to support the transition from formulation discovery to therapeutic discovery
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Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.
A fresh examination of the past successes of natural products as medicines and their new future from both conventional and new technologies. High-performance liquid chromatography profiling, combinatorial synthesis, genomics, proteomics, DNA shuffling, bioinformatics, and genetic manipulation all now make it possible to rapidly evaluate the activities of extracts as well as purified components derived from microbes, plants, and marine organisms. The authors apply these methods to new natural product drug discoveries, to microbial diversity, to specific groups of products (Chinese herbal drugs, antitumor drugs from microbes and plants, terpenoids, and arsenic compounds), and to specific sources (the sea, rainforest, and endophytes). These new opportunities show how research and development trends in the pharmaceutical industry can advance to include both synthetic compounds and natural products, and how this paradigm shift can be more productive and efficacious.
Animal Experimentation: Working Towards a Paradigm Change critically appraises current animal use in science and discusses ways in which we can contribute to a paradigm change towards human-biology based approaches.