Provides an extensive and up-to-date overview of the theory and application of computational pharmaceutics in the drug development process Exploring Computational Pharmaceutics - AI and Modeling in Pharma 4.0 introduces a variety of current and emerging computational techniques for pharmaceutical research. Bringing together experts from academia, industry, and regulatory agencies, this edited volume also explores the current state, key challenges, and future outlook of computational pharmaceutics while encouraging development across all sectors of the field. Throughout the text, the authors discuss a wide range of essential topics, from molecular modeling and process simulation to intelligent manufacturing and quantitative pharmacology. Building upon Exploring Computational Pharmaceutics - AI and Modeling in Pharma 4.0, this new edition provides a multi-scale perspective that reveals the physical, chemical, mathematical, and data-driven details of pre-formulation, formulation, process, and clinical studies, in addition to in vivo prediction in the human body and precision medicine in clinical settings. Detailed chapters address both conventional dosage forms and the application of computational technologies in advanced pharmaceutical research, such as dendrimer-based delivery systems, liposome and lipid membrane research, and inorganic nanoparticles. A major contribution to the development and promotion of computational pharmaceutics, this important resource: Discusses the development track, achievements, and prospects of computational pharmaceutics Presents multidisciplinary research to help physicists, chemists, mathematicians, and computer scientists locate problems in the field of drug delivery Covers a wide range of technologies, including complex formulations for water-insoluble drugs, protein/peptide formulations, nanomedicine, and gene delivery systems Focuses on the application of cutting-edge computational technologies and intelligent manufacturing of emerging pharmaceutical technologies Includes a systematic overview of computational pharmaceutics and Pharma 4.0 to assist non-specialist readers Covering introductory, advanced, and specialist topics, Exploring Computational Pharmaceutics - AI and Modeling in Pharma 4.0 is an invaluable resource for computational chemists, computational analysts, pharmaceutical chemists, process engineers, process managers, and pharmacologists, as well as computer scientists, medicinal chemists, clinical pharmacists, material scientists, and nanotechnology specialists working in the field.

Molecular modeling techniques have been widely used in drug discovery fields for rational drug design and compound screening. Now these techniques are used to model or mimic the behavior of molecules, and help us study formulation at the molecular level. Computational pharmaceutics enables us to understand the mechanism of drug delivery, and to develop new drug delivery systems. The book discusses the modeling of different drug delivery systems, including cyclodextrins, solid dispersions, polymorphism prediction, dendrimer-based delivery systems, surfactant-based micelle, polymeric drug delivery systems, liposome, protein/peptide formulations, non-viral gene delivery systems, drug-protein binding, silica nanoparticles, carbon nanotube-based drug delivery systems, diamond nanoparticles and layered double hydroxides (LDHs) drug delivery systems. Although there are a number of existing books about rational drug design with molecular modeling techniques, these techniques still look mysterious and daunting for pharmaceutical scientists. This book fills the gap between pharmaceutics and molecular modeling, and presents a systematic and overall introduction to computational pharmaceutics. It covers all introductory, advanced and specialist levels. It provides a totally different perspective to pharmaceutical scientists, and will greatly facilitate the development of pharmaceutics. It also helps computational chemists to look for the important questions in the drug delivery field. This book is included in the Advances in Pharmaceutical Technology book series.

The network approaches of systems pharmacology and toxicology serve as early predictors of the most relevant screening approach to pursue both in drug discovery and development and ecotoxicological assessments. Computational approaches have the potential to improve toxicological experimental design, enable more rapid drug efficacy and safety testing and also reduce the number of animals used in experimentation. Rapid advances in availability of computing technology hold tremendous promise for advancing applied and basic science and increasing the efficiency of risk assessment. This book provides an understanding of the basic principles of computational toxicology and the current methods of predictive toxicology using chemical structures, toxicity-related databases, in silico chemical-protein docking, and biological pathway tools. The book begins with an introduction to systems pharmacology and toxicology and computational tools followed by a section exploring modelling adverse outcomes and events. The second part of the book covers the discovery of protein targets and the characterisation of toxicant-protein interactions. Final chapters include case studies and additionally discuss interactions between phytochemicals and Western therapeutics. This book will be useful for scientists involved in environmental research and risk assessment. It will be a valuable resource for postgraduate students and researchers wishing to learn about key methods used in studying biological targets both from a toxicity and pharmacological activity standpoint.

The world of pharmaceutical research is moving at lightning speed, and the age-old approach to drug discovery faces many challenges. It's a fascinating time to be on the cutting edge of medical innovation, but it's certainly not without its obstacles. The process of developing new drugs is often time-consuming, expensive, and fraught with uncertainty. Researchers are constantly seeking ways to streamline this process, reduce costs, and increase the success rate of bringing new drugs to market. One promising solution lies in the convergence of pharmacy science and engineering, particularly in computational drug discovery. Converging Pharmacy Science and Engineering in Computational Drug Discovery presents a comprehensive solution to these challenges by exploring the transformative synergy between pharmacy science and engineering. This book demonstrates how researchers can expedite the identification and development of novel therapeutic compounds by harnessing the power of computational approaches, such as sophisticated algorithms and modeling techniques. Through interdisciplinary collaboration, pharmacy scientists and engineers can revolutionize drug discovery, paving the way for more efficient and effective treatments. This book is an invaluable resource for pharmaceutical scientists, researchers, and engineers seeking to enhance their understanding of computational drug discovery. This book inspires future innovations by showcasing cutting-edge methodologies and innovative research at the intersection of pharmacy science and engineering. It contributes to the ongoing evolution of pharmaceutical research. It offers practical insights and solutions that will shape the future of drug discovery, making it essential reading for anyone involved in the pharmaceutical industry.

This book is the first to combine computational material science and modeling of molecular solid states for pharmaceutical industry applications. • Provides descriptive and applied state-of-the-art computational approaches and workflows to guide pharmaceutical solid state chemistry experiments and to support/troubleshoot API solid state selection • Includes real industrial case examples related to application of modeling methods in problem solving • Useful as a supplementary reference/text for undergraduate, graduate and postgraduate students in computational chemistry, pharmaceutical and biotech sciences, and materials science

Helps you choose the right computational tools and techniques to meet your drug design goals Computational Drug Design covers all of the major computational drug design techniques in use today, focusing on the process that pharmaceutical chemists employ to design a new drug molecule. The discussions of which computational tools to use and when and how to use them are all based on typical pharmaceutical industry drug design processes. Following an introduction, the book is divided into three parts: Part One, The Drug Design Process, sets forth a variety of design processes suitable for a number of different drug development scenarios and drug targets. The author demonstrates how computational techniques are typically used during the design process, helping readers choose the best computational tools to meet their goals. Part Two, Computational Tools and Techniques, offers a series of chapters, each one dedicated to a single computational technique. Readers discover the strengths and weaknesses of each technique. Moreover, the book tabulates comparative accuracy studies, giving readers an unbiased comparison of all the available techniques. Part Three, Related Topics, addresses new, emerging, and complementary technologies, including bioinformatics, simulations at the cellular and organ level, synthesis route prediction, proteomics, and prodrug approaches. The book's accompanying CD-ROM, a special feature, offers graphics of the molecular structures and dynamic reactions discussed in the book as well as demos from computational drug design software companies. Computational Drug Design is ideal for both students and professionals in drug design, helping them choose and take full advantage of the best computational tools available. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

The proposed volume provides both fundamental and detailed information about the computational and computational-experimental studies which improve our knowledge of how leaving matter functions, the different properties of drugs (including the calculation and the design of new ones), and the creation of completely new ways of treating numerical diseases. Whenever it is possible, the interplay between theory and experiment is provided. The book features computational techniques such as quantum-chemical and molecular dynamic approaches and quantitative structure–activity relationships. The initial chapters describe the state-of-the art research on the computational investigations in molecular biology, molecular pharmacy, and molecular medicine performed with the use of pure quantum-chemical techniques. The central part of the book illustrates the status of computational techniques that utilize hybrid, so called QM/MM approximations as well as the results of the QSAR studies which now are the most popular in predicting drugs’ efficiency. The last chapters describe combined computational and experimental investigations.