Bioinformatics Tools for Pharmaceutical Drug Product Development

Bioinformatics Tools for Pharmaceutical Drug Product Development

Author: Vivek Chavda

Publisher: John Wiley & Sons

Published: 2023-03-14

Total Pages: 452

ISBN-13: 1119865115

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BIOINFORMATICS TOOLS FOR Pharmaceutical DRUG PRODUCT DLEVELOPMENT A timely book that details bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies, for drug development in the pharmaceutical and medical sciences industries. The book contains 17 chapters categorized into 3 sections. The first section presents the latest information on bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies. The following 2 sections include bioinformatics tools for the pharmaceutical sector and the healthcare sector. Bioinformatics brings a new era in research to accelerate drug target and vaccine design development, improving validation approaches as well as facilitating and identifying side effects and predicting drug resistance. As such, this will aid in more successful drug candidates from discovery to clinical trials to the market, and most importantly make it a more cost-effective process overall. Readers will find in this book: Applications of bioinformatics tools for pharmaceutical drug product development like process development, pre-clinical development, clinical development, commercialization of the product, etc.; The ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach; The broad and deep background, as well as updates, on recent advances in both medicine and AI/ML that enable the application of these cutting-edge bioinformatics tools. Audience The book will be used by researchers and scientists in academia and industry including drug developers, computational biochemists, bioinformaticians, immunologists, pharmaceutical and medical sciences, as well as those in artificial intelligence and machine learning.


Pharmacogenomics in Drug Discovery and Development

Pharmacogenomics in Drug Discovery and Development

Author: Qing Yan

Publisher: Springer Nature

Published: 2022-09-06

Total Pages: 618

ISBN-13: 107162573X

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This new edition offers a state-of-the-art and integrative vision of pharmacogenomics by exploring new concepts and practical methodologies focusing on disease treatments, from cancers to cardiovascular and neurodegenerative disorders and more. The collection of these theoretical and experimental approaches facilitates problem-solving by tackling the complexity of personalized drug discovery and development. Written by leading experts in their fields for the highly successful Methods in Molecular Biology series, the book aims to provide across-the-board resources to support the translation of pharmacogenomics into better individualized health care. Authoritative and up-to-date, Pharmacogenomics in Drug Discovery and Development, Third Edition aims to aid researchers in approaching the challenges in pharmacogenomics and personalized medicine with the introduction of these novel ideas and cutting-edge methodologies.


Artificial Intelligence in Drug Discovery

Artificial Intelligence in Drug Discovery

Author: Nathan Brown

Publisher: Royal Society of Chemistry

Published: 2020-11-04

Total Pages: 425

ISBN-13: 1839160543

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Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.


Chemoinformatics and Bioinformatics in the Pharmaceutical Sciences

Chemoinformatics and Bioinformatics in the Pharmaceutical Sciences

Author: Navneet Sharma

Publisher: Academic Press

Published: 2021-05-21

Total Pages: 514

ISBN-13: 0128217472

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Chemoinformatics and Bioinformatics in the Pharmaceutical Sciences brings together two very important fields in pharmaceutical sciences that have been mostly seen as diverging from each other: chemoinformatics and bioinformatics. As developing drugs is an expensive and lengthy process, technology can improve the cost, efficiency and speed at which new drugs can be discovered and tested. This book presents some of the growing advancements of technology in the field of drug development and how the computational approaches explained here can reduce the financial and experimental burden of the drug discovery process. This book will be useful to pharmaceutical science researchers and students who need basic knowledge of computational techniques relevant to their projects. Bioscientists, bioinformaticians, computational scientists, and other stakeholders from industry and academia will also find this book helpful. - Provides practical information on how to choose and use appropriate computational tools - Presents the wide, intersecting fields of chemo-bio-informatics in an easily-accessible format - Explores the fundamentals of the emerging field of chemoinformatics and bioinformatics


Bioinformatics and Drug Discovery

Bioinformatics and Drug Discovery

Author: Richard S. Larson

Publisher:

Published: 2012

Total Pages: 374

ISBN-13: 9781617799655

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Recent advances in drug discovery have been rapid. The second edition of Bioinformatics and Drug Discovery has been completely updated to include topics that range from new technologies in target identification, genomic analysis, cheminformatics, protein analysis, and network or pathway analysis. Each chapter provides an extended introduction that describes the theory and application of the technology. In the second part of each chapter, detailed procedures related to the use of these technologies and software have been incorporated. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Bioinformatics and Drug Discovery, Second Edition seeks to aid scientists in the further study of the rapidly expanding field of drug discovery.


Pharmaceutical Biotechnology

Pharmaceutical Biotechnology

Author: Gary Walsh

Publisher: John Wiley & Sons

Published: 2013-04-25

Total Pages: 499

ISBN-13: 111868575X

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Pharmaceutical Biotechnology offers students taking Pharmacy and related Medical and Pharmaceutical courses a comprehensive introduction to the fast-moving area of biopharmaceuticals. With a particular focus on the subject taken from a pharmaceutical perspective, initial chapters offer a broad introduction to protein science and recombinant DNA technology- key areas that underpin the whole subject. Subsequent chapters focus upon the development, production and analysis of these substances. Finally the book moves on to explore the science, biotechnology and medical applications of specific biotech products categories. These include not only protein-based substances but also nucleic acid and cell-based products. introduces essential principles underlining modern biotechnology- recombinant DNA technology and protein science an invaluable introduction to this fast-moving subject aimed specifically at pharmacy and medical students includes specific ‘product category chapters’ focusing on the pharmaceutical, medical and therapeutic properties of numerous biopharmaceutical products. entire chapter devoted to the principles of genetic engineering and how these drugs are developed. includes numerous relevant case studies to enhance student understanding no prior knowledge of protein structure is assumed


Artificial Intelligence in Microbiology: Scope and Challenges Volume 1

Artificial Intelligence in Microbiology: Scope and Challenges Volume 1

Author:

Publisher: Elsevier

Published: 2024-08-02

Total Pages: 300

ISBN-13: 0443296251

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Nowadays, the field of microbiology is undergoing a revolutionary change due to the emergence of Artificial Intelligence (AI). AI is being used to analyze massive data in a predictable form, about the behavior of microorganisms, to solve microbial classification-related problems, exploring the interaction between microorganisms and the surrounding environment. It also helps to extract novel microbial metabolites which have been used in various fields like medical, food and agricultural industries. As the pace of innovation in Microbiology is accelerating, the use of AI in these industries will be beneficial. AI will not only show its extraordinary potential in expanding the market of antibiotics, food, and agriculture but also offer an eco-friendly, safer, and profitable solution to the respective industries. It would be challenging to search out specific features and discuss future research on AI in microbiology with a wide perspective. - Uncovering extended functions of AI in Microbiology. - Production and development of novel drug targets through AI. - Challenges for using and selecting appropriate AI tools in health, agriculture and food sector


Open Source Software in Life Science Research

Open Source Software in Life Science Research

Author: Lee Harland

Publisher: Elsevier

Published: 2012-10-31

Total Pages: 583

ISBN-13: 1908818247

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The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems.The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an 'omics' platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry. - Discusses a broad range of applications from a variety of sectors - Provides a unique perspective on work normally performed behind closed doors - Highlights the criteria used to compare and assess different approaches to solving problems


Using Traditional Design Methods to Enhance AI-Driven Decision Making

Using Traditional Design Methods to Enhance AI-Driven Decision Making

Author: Nguyen, Tien V. T.

Publisher: IGI Global

Published: 2024-01-10

Total Pages: 528

ISBN-13:

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In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.