Handbook of Integrated Weed Management for Major Field Crops provides a comprehensive guide to the identification, ecology, and management of weeds in key agricultural crops such as rice, wheat, maize, sugarcane, oilseeds, pulses, and more. The book highlights an integrated approach to weed control, combining cultural, mechanical, biological, and chemical methods. Each chapter focuses on specific crops, detailing tailored strategies for effective weed management in diverse agroecological zones. The text also explores weed biology, crop competition, and the role of environmental factors in weed proliferation. With an emphasis on sustainability and economic efficiency, this handbook is a crucial resource for students, researchers, farm managers, and agricultural professionals seeking practical and ecological weed management solutions. Key Features: - Comprehensive coverage of weed identification, biology, and ecology. - Focus on integrated weed management strategies across major field crops. - Detailed weed control approaches for specific crops. - Emphasis on sustainable and economically efficient practices. - Essential resource for students, researchers, and professionals in agriculture.

The Future of Agriculture: IoT, AI and Blockchain Technology for Sustainable Farming explores how cutting-edge technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and Blockchain are transforming farming for a sustainable future. Addressing challenges such as climate change, resource scarcity, and food supply chain inefficiencies, the book highlights how these technologies can improve decision-making, enhance crop yields, and increase transparency in agriculture. With a blend of theory and real-world applications, it covers everything from AI-driven pesticide prediction and disease identification to using Blockchain for efficient food supply chain management. This comprehensive guide is essential for researchers, professionals, and anyone interested in the intersection of technology and sustainable farming. Key Features: - Introduction to Digital Twin technology for sustainable farming - Practical applications of AI and IoT in agriculture - Blockchain's role in food supply chain management - Frameworks for precision agriculture and access to government schemes - Insights on integrating AI, IoT, and Blockchain into solid waste management systems

The book summarizes the role of multiple enzyme targets and strategies to design and develop novel drug candidates for Alzheimer's disease (AD). Insights from researchers across the globe from diverse fields are presented in a thematic volume. The chapters highlight current information scientists have unraveled about the origin, pathogenesis and prevention of AD. The contributions consider both established and emerging drug targets viz. Tau proteins, TREM, and microglia. Topics covered in the book include multi-target anti-Alzheimer's agents, epigenetic modifications, and the role of specific proteins like TMP21 and Tau in AD. A section dedicated to pharmacological treatments discusses the significance of tubulin-modifying enzymes, memantine, and glutamate antagonists. Enzymatic targets for drug discovery are thoroughly examined, focusing on cholinesterase, secretases, and other enzymes. Additionally, the book explores innovative nano-carrier-based drug delivery methods, emphasizing the crucial role of nanotechnology in effective Alzheimer's treatment. The book aims to inform students and researchers in the field of neuroscience, medicine and pharmacology about current research and biochemical nuances of AD pathogenesis and enzymatic drug targeting strategies.

Designing and developing new drugs is an expensive and time-consuming process, and there is a need to discover new tools or approaches that can optimize this process. Applied Computer-Aided Drug Design: Models and Methods compiles information about the main advances in computational tools for discovering new drugs in a simple and accessible language for academic students to early career researchers. The book aims to help readers understand how to discover molecules with therapeutic potential by bringing essential information about the subject into one volume. Key Features . Presents the concepts and evolution of classical techniques, up to the use of modern methods based on computational chemistry in accessible format. . Gives a primer on structure- and ligand-based drug design and their predictive capacity to discover new drugs. . Explains theoretical fundamentals and applications of computer-aided drug design. . Focuses on a range of applications of the computations tools, such as molecular docking; molecular dynamics simulations; homology modeling, pharmacophore modeling, quantitative structure-activity relationships (QSAR), density functional theory (DFT), fragment-based drug design (FBDD), and free energy perturbation (FEP). . Includes scientific reference for advanced readers

Computational Toxicology for Drug Safety and a Sustainable Environment is a primer on computational techniques in environmental toxicology for scholars. The book presents 9 in-depth chapters authored by expert academicians and scientists aimed to give readers an understanding of how computational models, software and algorithms are being used to predict toxicological profiles of chemical compounds. The book also aims to help academics view toxicological assessment from the lens of sustainability by providing an overview of the recent developments in environmentally-friendly practices. The chapters review the strengths and weaknesses of the existing methodologies, and cover new developments in computational tools to explain how researchers aim to get accurate results. Each chapter features a simple introduction and list of references to benefit a broad range of academic readers. List of topics: 1. Applications of computational toxicology in pharmaceuticals, environmental and industrial practices 2. Verification, validation and sensitivity studies of computational models used in toxicology assessment 3. Computational toxicological approaches for drug profiling and development of online clinical repositories 4. How to neutralize chemicals that kill environment and humans: an application of computational toxicology 5. Adverse environmental impact of pharmaceutical waste and its computational assessment 6. Computational aspects of organochlorine compounds: DFT study and molecular docking calculations 7. In-silico studies of anisole and glyoxylic acid derivatives 8. Computational toxicology studies of chemical compounds released from firecrackers 9. Computational nanotoxicology and its applications.

This book provides a compressive overview of nanotechnology in modern drug discovery for students and researchers. The book starts with the fundamentals of nanotechnology followed by nanomaterials in pharmaceutical drug design, drug delivery applications, regulatory aspects, formulation and nanoparticle biotransformation. It provides a step by step guide through the drug development process while conveying information about the benefits of nanomaterials for therapy. The book concludes with perspective on the future of nanotechnology-based drug discovery, summarizing current knowledge on nanotherapeutics and translational medicine. Key Features - Explains the fundamentals of nanotechnology in drug discovery - Includes up-to-date information on modern nanopharmaceutical manufacturing, nanomaterials, and nanoparticle-based drug therapy - Practice questions for learners and a list of references for advanced readers for each chapter

AI Innovations in Drug Delivery and Pharmaceutical Sciences: Advancing Therapy through Technology offers a comprehensive exploration of how artificial intelligence (AI) is revolutionizing the pharmaceutical and healthcare sectors. This book addresses the AI’s role in drug discovery, development, and delivery, highlighting applications in personalized medicine, nanotechnology, and clinical trials. It also covers AI’s impact on community and hospital pharmacy, herbal medicine, and drug product design. Each chapter examines the use of AI in optimizing drug processes, from designing innovative therapies to improving regulatory compliance and future trends in pharmaceutical technology. This insightful resource is invaluable for researchers, pharmaceutical professionals, and healthcare innovators aiming to advance therapeutic outcomes through AI. Key Features: - Comprehensive coverage of AI applications in drug discovery, delivery, and design. - Insights into AI-driven personalized medicine and nanotechnology. - Regulatory perspectives on AI in drug delivery and medical devices. - Future trends and innovations in AI for pharmaceutical technology.

This text book is a guide for pharmaceutical academics (students and teachers) as well as industry professionals learning about drug delivery and formulation. Chapters presents comprehensive information about self-emulsifying formulations by providing an in-depth understanding of the basic concepts and formulation mechanisms. This information is supplemented by details about current research and development in this field. Readers will learn about the types of self-emulsifying drug delivery systems, evaluation parameters and digestion models, among other topics. </p> Key Features: </p> - 9 chapters organized in a reader-friendly layout </p> - complete guide on self-emulsifying drug delivery formulations, including lipid based systems, SMEDOs, surfactants, and oral dosage forms </p> - includes basic concepts and current developments in research and industrial applications </p> - presents information on conventional and herbal formulations </p> - references for further reading

Angiogenesis plays rate limiting roles in tumor growth and invasion. Angiogenesis inhibition has been proposed as a general strategy to fight against cancers. This book covers different therapeutic targets for angiogenesis interventions with emphasis on clinical development of antiangiogenic drugs that target antiangiogenic cascade in different forms of cancers like breast cancer, multiple myeloma, renal carcinoma, gastrointestinal, prostate and lung cancer. Surrogate predictive markers of antiangiogenic therapy in novel preclinical models recapitulating tumor microenvironment together with genomic studies are special features of this book. Gene therapy approaches with emphasis on viral vectors have been explored in preclinical model with direct and indirect angiogenesis inhibitors. Recent advances in clinical application with antiangiogenic therapy resulted in encouraging clinical results are also detailed. It includes chapters that bridge the gap between basic science and clinical application of current knowledge of cancer. Different chapters are contributed by distinguished scientists and clinicians around the world making it an important addition to the bookshelves of clinicians, academics, researchers, students and institutions.