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 book bridges the gap between pharmaceutics and molecular modelling at the micro, meso and macro scale. It covers Lipinski's rule of five, nanoparticulate drug delivery, computational prediction of drug solubility and ability to cross blood brain barrier, computer-based simulation of pharmacokinetic parameters, virtual screening of mucoadhesive polymers, QSPR modelling, designing of 2D nanomaterials and role of principal component analysis.

The first book of its kind to show the potential of quantum computing in drug delivery. Drug delivery systems (DDS) are defined as methods by which drugs are delivered to desired tissues, organs, cells, and subcellular organs for drug release and absorption through a variety of drug carriers. By controlling the precise level and/or location of a given drug in the body, side effects are reduced, doses are lowered, and new therapies are possible. Nevertheless, there are still significant obstacles to delivering certain medications to particular cells. Drug delivery methods change pharmacokinetic, pharmacodynamic, and drug release patterns to enhance product efficacy and safety, as well as patient convenience and compliance. Computational approaches in drug development enable quick screening of a vast chemical library and identification of possible binders by using modeling, simulation, and visualization tools. Quantum computing (QC) is a fundamentally new computing paradigm based on quantum mechanics rules that enables certain computations to be conducted significantly more rapidly and effectively than regular computing, and hence this has huge promise for the pharmaceutical sector. Significant advances in computational simulation are making it easier to comprehend the process of drug delivery. This book explores an important biophysical component of DDSs, and how computer modeling may help with the logical design of DDSs with enhanced and optimized characteristics. The book concentrates on computational research for various important types of nanocarriers, including dendrimers and dendrons, polymers, peptides, nucleic acids, lipids, carbon-based DDSs, and gold nanoparticles. Audience Researchers and industry scientists working in clinical research and disease management; pharmacists, formulation and pharmaceutical scientists working in R&D; computer science engineers applying deep learning and quantum computing in healthcare.

This book, aimed at academics, industrialists and post-graduates, documents the latest research into computer aided drug design.

This book examines the role of computer-assisted techniques for discovering, designing, optimizing and manufacturing new, effective, and safe pharmaceutical formulations and drug delivery systems. The book discusses computational approaches, statistical modeling and molecular modeling for the development and safe delivery of drugs in humans. The application of concepts of QbD (Quality by Design), DoE (Design of Experiments), artificial intelligence and in silico pharmacokinetic assessment/simulation have been made a lot easier with the help of commercial software and expert systems. This title provides in-depth knowledge of such useful software with illustrations from the latest researches. The book also fills in the gap between pharmaceutics and molecular modeling at micro, meso and maro scale by covering topics such as advancements in computer-aided Drug Design (CADD), drug-polymer interactions in drug delivery systems, molecular modeling of nanoparticles and pharmaceutics/bioinformatics. This book provides abundant applications of computers in formulation designing and characterization are provided as examples, case studies and illustrations. Short reviews of software, databases and expert systems have also been added to culminate the interest of readers for novel applications in formulation development and drug delivery. Computer-aided pharmaceutics and drug delivery is an authoritative reference source for all the latest scholarly update on emerging developments in computed assisted techniques for drug designing and development. The book is ideally designed for pharmacists, medical practitioners, students and researchers.

Computational methods and understanding computational models are important in modern drug discovery. The books focus on computational approaches that can improve the development of in silico methodologies. They include lead hit methods, docking algorithms, computational chiral compounds, structure-based drug design, GROMACS and NAMD, structural genomics, toxicity prediction, enzyme inhibitors and peptidomimetic therapeutics.

A Handbook of Artificial Intelligence in Drug Delivery explores the use of Artificial Intelligence (AI) in drug delivery strategies. The book covers pharmaceutical AI and drug discovery challenges, Artificial Intelligence tools for drug research, AI enabled intelligent drug delivery systems and next generation novel therapeutics, broad utility of AI for designing novel micro/nanosystems for drug delivery, AI driven personalized medicine and Gene therapy, 3D Organ printing and tissue engineering, Advanced nanosystems based on AI principles (nanorobots, nanomachines), opportunities and challenges using artificial intelligence in ADME/Tox in drug development, commercialization and regulatory perspectives, ethics in AI, and more. This book will be useful to academic and industrial researchers interested in drug delivery, chemical biology, computational chemistry, medicinal chemistry and bioinformatics. The massive time and costs investments in drug research and development necessitate application of more innovative techniques and smart strategies. - Focuses on the use of Artificial Intelligence in drug delivery strategies and future impacts - Provides insights into how artificial intelligence can be effectively used for the development of advanced drug delivery systems - Written by experts in the field of advanced drug delivery systems and digital health

"This cutting-edge volume reviews the latest breakthroughs in CADD (Computer-Aided Drug Design), drug delivery systems, and enabling technologies"--Provided by publisher.

Artificial Neural Network for Drug Design, Delivery and Disposition provides an in-depth look at the use of artificial neural networks (ANN) in pharmaceutical research. With its ability to learn and self-correct in a highly complex environment, this predictive tool has tremendous potential to help researchers more effectively design, develop, and deliver successful drugs. This book illustrates how to use ANN methodologies and models with the intent to treat diseases like breast cancer, cardiac disease, and more. It contains the latest cutting-edge research, an analysis of the benefits of ANN, and relevant industry examples. As such, this book is an essential resource for academic and industry researchers across the pharmaceutical and biomedical sciences. - Written by leading academic and industry scientists who have contributed significantly to the field and are at the forefront of artificial neural network (ANN) research - Focuses on ANN in drug design, discovery and delivery, as well as adopted methodologies and their applications to the treatment of various diseases and disorders - Chapters cover important topics across the pharmaceutical process, such as ANN in structure-based drug design and the application of ANN in modern drug discovery - Presents the future potential of ANN-based strategies in biomedical image analysis and much more