This book describes the state-of-the-art of chemoinformatics, bioinformatics, materials informatics and measurement/metrology informatics to improve the correlation with the functionality, efficacy, safety and quality of compounds for drugs with good physical properties and activity values. Recently, "AI drug discovery", drug discovery research utilizing artificial intelligence technology such as machine learning has attracted much attention. This book provides an overview of the four applied informatics fields and their applications in drug development for a wide spectrum of readers from learners to professional scientists in academica and industry. It focuses on the basic research stage of drug development with contributions from experts at the forefront of these fields. The authors hope that this book will be of assistance to explore new opportunities for collaboration between pharmaceutical science and informatics.

Within the context of integrated health management domains, pharmacoinformatics aims at maximizing the benefits from the use of information systems and technologies for the provision of decision support tools necessary for improved drug management, use, and administration practices. Pharmacoinformatics and Drug Discovery Technologies: Theories and Applications offers the latest the field has to offer to practitioners and academics alike, presented through theoretical frameworks, case studies, and future directions. This vital resource gathers an integrated pattern of high quality publications from around the world providing current, cutting-edge, and provocative scientific work in the three domains of pharmacoinformatics: decision making domains, knowledge utilization and representation environment, and the technological and infrastructural context.

Integrating various technologies with informational systems provides vast improvements to the overall research and development that occur in the biopharmaceutical industry. One of the first books to explore this area, Functional Informatics in Drug Discovery examines all aspects of technology integration and information flow in a biopharmaceutical

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.

This book updates knowledge on recent advances in computational, biophysical and bioinformatics tools/techniques and their practical applications in modern drug design and discovery paradigm. It also encompasses fundamental principles, advanced methodologies and applications of various CADD approaches including several cutting-edge areas; presenting recent developments covering ongoing trends in the field of computer-aided drug discovery. Having contributions by a global team of experts, the book is expected to be an ideal resource for drug discovery scientists, medicinal chemists, pharmacologists, toxicologists, phytochemists, biochemists, biologists, R&D personnel, researchers, students, teachers and those working in the field of drug discovery. It will fill the knowledge gaps that exist in the current CADD approaches and methodologies/ protocols being widely used in both academic and research practices. Further, a special focus on current status of various computational drug design approaches (SBDD, LBDD, de novo drug design, pharmacophore-based search), bioinformatics tools and databases, computational screening and modeling of phytochemicals/natural products, artificial intelligence and machine learning, and network pharmacology and systems biology would certainly guide researchers, students or readers to conduct their research in the emerging area(s) of interest. It is also expected to be highly beneficial to various stakeholders working in the pharmaceutical and biotechnology industries (R&D), the academic as well as research sectors.

Concepts and Experimental Protocols of Modelling and Informatics in Drug Design discusses each experimental protocol utilized in the field of bioinformatics, focusing especially on computer modeling for drug development. It helps the user in understanding the field of computer-aided molecular modeling (CAMM) by presenting solved exercises and examples. The book discusses topics such as fundamentals of molecular modeling, QSAR model generation, protein databases and how to use them to select and analyze protein structure, and pharmacophore modeling for drug targets. Additionally, it discusses data retrieval system, molecular surfaces, and freeware and online servers. The book is a valuable source for graduate students and researchers on bioinformatics, molecular modeling, biotechnology and several members of biomedical field who need to understand more about computer-aided molecular modeling. Presents exercises with solutions to aid readers in validating their own protocol Brings a thorough interpretation of results of each exercise to help readers compare them to their own study Explains each parameter utilized in the algorithms to help readers understand and manipulate various features of molecules and target protein to design their study

Chemoinformatics strategies to improve drug discovery results With contributions from leading researchers in academia and the pharmaceutical industry as well as experts from the software industry, this book explains how chemoinformatics enhances drug discovery and pharmaceutical research efforts, describing what works and what doesn't. Strong emphasis is put on tested and proven practical applications, with plenty of case studies detailing the development and implementation of chemoinformatics methods to support successful drug discovery efforts. Many of these case studies depict groundbreaking collaborations between academia and the pharmaceutical industry. Chemoinformatics for Drug Discovery is logically organized, offering readers a solid base in methods and models and advancing to drug discovery applications and the design of chemoinformatics infrastructures. The book features 15 chapters, including: What are our models really telling us? A practical tutorial on avoiding common mistakes when building predictive models Exploration of structure-activity relationships and transfer of key elements in lead optimization Collaborations between academia and pharma Applications of chemoinformatics in pharmaceutical research experiences at large international pharmaceutical companies Lessons learned from 30 years of developing successful integrated chemoinformatic systems Throughout the book, the authors present chemoinformatics strategies and methods that have been proven to work in pharmaceutical research, offering insights culled from their own investigations. Each chapter is extensively referenced with citations to original research reports and reviews. Integrating chemistry, computer science, and drug discovery, Chemoinformatics for Drug Discovery encapsulates the field as it stands today and opens the door to further advances.