Artificial Intelligence for Drug Product Lifecycle Applications explains the use of artificial intelligence (AI) in drug discovery and development paths, including the clinical and postapproval phases. This book gives methods for each of the drug development steps, from the fundamentals to postapproval drug product. AI is a synergistic assembly of enhanced optimization strategies with particular applications in pharmaceutical development and advanced tools for promoting cost-effectiveness throughout the drug lifecycle. Specifically, AI brings together the potential to improve drug approval rates, reduce development costs, get medications to patients faster, and help patients comply with their treatments.Accelerated pharmaceutical development and drug product approval rates will enable larger profits from patent-protected market exclusivity. This book offers the tools and knowledge to create the right AI strategy to extend the landscape of AI applications across the drug lifecycle. It is especially useful for pharmaceutical scientists, health care professionals, and regulatory scientists, as well as advanced students and postgraduates actively involved in pharmaceutical product and process development involving the use of artificial intelligence in drug delivery applications. - Classifies AI methodologies and application examples into different categories representing the various steps of the drug development cycle - Combines timely literature review with clear artworks to improve understanding - Examines deep learning and machine learning in drug discovery

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

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.

Amid the dynamic growth of artificial intelligence, this book presents a collection of findings and advancements from the second edition of the A2IA-Artificial Intelligence and Industrial Applications conference. The conference, hosted by ENSAM-Meknès at Moulay Ismail University, Morocco, fosters knowledge exchange in AI, focusing primarily on its industrial applications. Covering a wide range of topics, the book highlights the adaptable nature of AI and its increasing impact on industrial sectors. It brings together contributions from an international cohort of researchers, discussing themes such as intelligent manufacturing and maintenance, intelligent supply chain management, various modes of learning including supervised, unsupervised, reinforcement, semi-supervised, and graph-based, as well as neural networks, deep learning, planning, and optimization. A defining feature of this edition is its extensive scope and emphasis on the practical applications of AI, along with its foundational elements. It facilitates an understanding of AI's current state and potential future direction, showcasing recent developments that bridge the gap between theory and practice. Designed for a diverse readership, this book is of interest to AI practitioners, academics, and enthusiasts, as well as to those new to the field. It provides an opportunity to explore AI's critical role in industrial applications, and the practical insights it offers are likely to be beneficial for decision-making within industrial settings.

The confluence of big data, artificial intelligence (AI), and machine learning (ML) has led to a paradigm shift in how innovative medicines are developed and healthcare delivered. To fully capitalize on these technological advances, it is essential to systematically harness data from diverse sources and leverage digital technologies and advanced analytics to enable data-driven decisions. Data science stands at a unique moment of opportunity to lead such a transformative change. Intended to be a single source of information, Data Science, AI, and Machine Learning in Drug Research and Development covers a wide range of topics on the changing landscape of drug R & D, emerging applications of big data, AI and ML in drug development, and the build of robust data science organizations to drive biopharmaceutical digital transformations. Features Provides a comprehensive review of challenges and opportunities as related to the applications of big data, AI, and ML in the entire spectrum of drug R & D Discusses regulatory developments in leveraging big data and advanced analytics in drug review and approval Offers a balanced approach to data science organization build Presents real-world examples of AI-powered solutions to a host of issues in the lifecycle of drug development Affords sufficient context for each problem and provides a detailed description of solutions suitable for practitioners with limited data science expertise

This cutting-edge reference book discusses the intervention of artificial intelligence in the fields of drug development, modified drug delivery systems, pharmaceutical technology, and medical devices development. This comprehensive book includes an overview of artificial intelligence in pharmaceutical sciences and applications in the drug discovery and development process. It discusses the role of machine learning in the automated detection and sorting of pharmaceutical formulations. It covers nanosafety and the role of artificial intelligence in predicting potential adverse biological effects. FEATURES Includes lucid, step-by-step instructions to apply artificial intelligence and machine learning in pharmaceutical sciences Explores the application of artificial intelligence in nanosafety and prediction of potential hazards Covers application of artificial intelligence in drug discovery and drug development Reviews the role of artificial intelligence in assessment of pharmaceutical formulations Provides artificial intelligence solutions for experts in the pharmaceutical and medical devices industries This book is meant for academicians, students, and industry experts in pharmaceutical sciences, medicine, and pharmacology.

"AI Pharma: Artificial Intelligence in Drug Discovery and Development" is a comprehensive exploration of how artificial intelligence is reshaping the pharmaceutical industry. It reveals how machine learning, deep learning, and other advanced technologies are revolutionizing drug discovery and development. The book meticulously charts the evolution of AI's role, starting from the surge in data collection and processing to the latest breakthroughs in predictive modeling. It unveils AI's transformative impact on research and development, delving into how AI tools streamline target identification, molecule generation, and clinical trials, leading to faster, more accurate results. Key industry experts share insights on the challenges of navigating the vast amount of data produced, stressing the importance of data cleaning, curation, and ethical considerations in collection. Case studies highlight how startups and leading companies use AI algorithms for deep learning in drug development, identifying disease targets and generating new compounds with unprecedented precision. The book emphasizes practical applications, like predictive models for toxicity and safety in preclinical trials and patient recruitment optimization in clinical trials. Additionally, it tackles the intersection of AI with emerging technologies like the Internet of Medical Things (IoMT) and blockchain, showcasing how these complement AI in securing data and enhancing pharmaceutical supply chains. Readers will gain a deep understanding of the regulatory landscape, exploring FDA guidelines and global regulations that shape AI adoption. Interwoven throughout are the voices of thought leaders who address legal and ethical challenges, highlight the significance of partnerships, and stress the need for transparent and trustworthy AI models. They emphasize cross-disciplinary collaboration and tailored training strategies to cultivate AI talent that meets the growing needs of pharma. By examining the future of deep learning, computational research, and explainable AI, the book provides a strategic roadmap that researchers, policymakers, and developers can follow. Ultimately, this book is not only a roadmap but also a clarion call, urging stakeholders to build collaborative ecosystems that harness AI's potential for innovative pharmaceutical research and development. Through a rich, detailed narrative, readers are guided to understand the profound implications and exciting opportunities that await in this AI-driven pharmaceutical landscape

Carbon dots (CDs) as an emerging carbon nanomaterial have attracted considerable attention and have been widely used in numerous fields. When compared with semiconductor quantum dots and organic dyes, CDs have a low toxicity, good biocompatibility and good anti-photobleaching. These qualities give them the potential to be a greener optical probe than other types of quantum dots and organic dyes. Covering several common synthesis strategies, including biomass synthesis, large-scale synthesis and sustainable synthesis technology, this book focuses on the green synthesis of CDs and their applications in the fields of bioanalytical, catalytic, biomedical, and environmental sciences. It is a useful reference for anyone working in green chemistry, analytical chemistry, biomedical or environmental science.

This book highlights recent advances in computational intelligence for signal processing, computing, imaging, artificial intelligence, and their applications. It offers support for researchers involved in designing decision support systems to promote the societal acceptance of ambient intelligence, and presents the latest research on diverse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field. As such, it offers a valuable resource for researchers, developers and educators whose work involves recent advances and emerging technologies in computational intelligence.

Marketing is a dynamic and ever-evolving field that requires constant adaptation and innovation to keep up with the changing times. In today's world, marketing strategies are more important than ever, as businesses strive to stay ahead of the competition and meet the changing needs and preferences of consumers. This book brings together a diverse range of topics related to marketing, including consumer preferences, AI and machine learning, online gaming, market segmentation, and more. Each chapter offers valuable insights and practical tips that can help businesses develop effective marketing strategies and reach their target audience. Whether you are a marketing professional, business owner, or a student looking to learn about marketing, this book has something for everyone. With real-life case studies and examples, readers will learn from successful marketing campaigns and gain a deeper understanding of the factors that influence consumer behaviour. The chapters in this book cover a wide range of topics, from the impact of AI and machine learning in marketing strategy to the influence of product packaging on consumer behaviour. Each chapter offers unique perspectives and insights into the world of marketing, providing readers with a comprehensive overview of this fascinating field. The book will be an invaluable resource for our understanding of marketing concepts, theories, and practices. The chapters have provided us with insightful and thought-provoking discussions on various topics, such as consumer behavior, marketing strategies, and emerging trends in the industry. We hope this book will inspire you to think creatively and strategically about your marketing efforts and help you achieve your business goals. We encourage you to read each chapter thoroughly, take notes, and apply the principles and techniques discussed to your marketing endeavors. With the insights and knowledge gained from this book, you will be better equipped to navigate the complex world of marketing and develop effective strategies that resonate with your target audience.