In recent years, the application of self-associating block copolymer based drug delivery systems has attracted increasing attention as nano-sized carriers for the encapsulation and the controlled delivery of water insoluble drugs. Most of the drug formulations are based on the "trial and error" method with no specific library of polymer and drug combination. This is simply because in the context of drug formulation and drug delivery from polymeric micelles, many factors are necessary to study such as drug-polymer intermolecular interactions, release kinetics, polymer compatibility with human cells, etc. Computer simulation that can help design such polymeric drug delivery systems will enable researchers to make educated decisions on choosing a particular polymeric carrier for a given drug, avoiding time consuming and expensive trial and error based formulation experiments. In the present thesis, we reported the use of molecular dynamics (MD) simulation to calculate the self-diffusion coefficients of a hydrophobic drug molecule in a series of micelle-forming PEO-b-PCL block copolymers with different structures and PCL block lengths in the presence of water molecules. MD analysis techniques like velocity auto-correlation functions, and squared displacement values along x, y and z axis provided useful atomistic details to understand the molecular origin of the diffusivity observed for drug molecules. Based on the evidence of reported work, intermolecular specific interactions between drug and different blocks of block copolymers all play important roles in the self-diffusion of drug molecule (CuB) in block copolymers. Additionally, water concentration, polymer swelling and wriggling motion of polymer chains affect the diffusivity of water molecules. The computed radius of gyration (Rg) of the PCL block confirmed that the PCL block tends to exhibit a higher degree of swelling than the PEO block. The understanding of relative contributions of the inter molecular interactions between drug and polymer can help us to customize the performance of drug carriers by engineering the structure of block copolymers to achieve a desired drug self-diffusion.

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 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.

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.

This book documents the latest research into the theory and application of force-fields, semi-empirical molecular orbital, density functional and ab initio calculations, Quantum Mechanical (QM) based modelling, Atoms in Molecules (AIM) approach, and biomolecular dynamics. It also covers theory and application of 2D cheminformatics, QSAR/QSPR, ADME properties of drugs, drug docking/scoring protocols and approaches, topological methodology, and modelling accurate inhibition constants of enzymes. Finally, the book gives the theory and applications of multiscale modelling of proteins and biomolecular systems. The information need for a book in this area is due to the continuing rapid advance of firstly theoretical approaches, secondly software/hardware and lastly the successful application of the technology and this book fills a gap in the literature. The co-editors have extensive experience of teaching and researching in the field and the book includes contributions from cutting-edge academic and industrial researchers in their respective fields. It is essential reading for medicinal chemists, computational chemists and those in the pharmaceutical industry.

Molecular dynamics simulation is a very powerful tool to understand biomolecular processes. In this chapter, we go over different applications of this methodology to drug delivery systems (DDS) carried out in the group. DDS-a formulation or a device that enables the introduction of a therapeutic substance in the body and improves its efficacy and safety by controlling the rate, time, and place of release of drugs-are an important component of drug development and therapeutics. Biocompatible nanoparticles are materials in the nanoscale that emerged as important players, improving efficacy of approved drugs, for example. The molecular understanding of the encapsulation process could be very helpful to guide the nanocarrier for a specific system. Here we discuss different applications of drug delivery carriers, such as liposomes, polymeric micelles, and polymersomes using atomistic and coarse grain (CG) molecular dynamics simulations.