Ai Pharma Artificial Intelligence In Drug Discovery And Development
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Ai Pharma Artificial Intelligence In Drug Discovery And Development
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Author : Daniel D. Lee
language : en
Publisher: SkyCuration
Release Date : 2024-08-12
Ai Pharma Artificial Intelligence In Drug Discovery And Development written by Daniel D. Lee and has been published by SkyCuration this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-12 with Computers categories.
"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
Artificial Intelligence And Machine Learning In Drug Design And Development
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Author : Abhirup Khanna
language : en
Publisher: John Wiley & Sons
Release Date : 2024-06-21
Artificial Intelligence And Machine Learning In Drug Design And Development written by Abhirup Khanna and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-21 with Computers categories.
The book is a comprehensive guide that explores the use of artificial intelligence and machine learning in drug discovery and development covering a range of topics, including the use of molecular modeling, docking, identifying targets, selecting compounds, and optimizing drugs. The intersection of Artificial Intelligence (AI) and Machine Learning (ML) within the field of drug design and development represents a pivotal moment in the history of healthcare and pharmaceuticals. The remarkable synergy between cutting-edge technology and the life sciences has ushered in a new era of possibilities, offering unprecedented opportunities, formidable challenges, and a tantalizing glimpse into the future of medicine. AI can be applied to all the key areas of the pharmaceutical industry, such as drug discovery and development, drug repurposing, and improving productivity within a short period. Contemporary methods have shown promising results in facilitating the discovery of drugs to target different diseases. Moreover, AI helps in predicting the efficacy and safety of molecules and gives researchers a much broader chemical pallet for the selection of the best molecules for drug testing and delivery. In this context, drug repurposing is another important topic where AI can have a substantial impact. With the vast amount of clinical and pharmaceutical data available to date, AI algorithms find suitable drugs that can be repurposed for alternative use in medicine. This book is a comprehensive exploration of this dynamic and rapidly evolving field. In an era where precision and efficiency are paramount in drug discovery, AI and ML have emerged as transformative tools, reshaping the way we identify, design, and develop pharmaceuticals. This book is a testament to the profound impact these technologies have had and will continue to have on the pharmaceutical industry, healthcare, and ultimately, patient well-being. The editors of this volume have assembled a distinguished group of experts, researchers, and thought leaders from both the AI, ML, and pharmaceutical domains. Their collective knowledge and insights illuminate the multifaceted landscape of AI and ML in drug design and development, offering a roadmap for navigating its complexities and harnessing its potential. In each section, readers will find a rich tapestry of knowledge, case studies, and expert opinions, providing a 360-degree view of AI and ML’s role in drug design and development. Whether you are a researcher, scientist, industry professional, policymaker, or simply curious about the future of medicine, this book offers 19 state-of-the-art chapters providing valuable insights and a compass to navigate the exciting journey ahead. Audience The book is a valuable resource for a wide range of professionals in the pharmaceutical and allied industries including researchers, scientists, engineers, and laboratory workers in the field of drug discovery and development, who want to learn about the latest techniques in machine learning and AI, as well as information technology professionals who are interested in the application of machine learning and artificial intelligence in drug development.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Artificial Intelligence In Pharmaceutical Sciences
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Author : Mullaicharam Bhupathyraaj
language : en
Publisher: CRC Press
Release Date : 2023-11-23
Artificial Intelligence In Pharmaceutical Sciences written by Mullaicharam Bhupathyraaj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-23 with Medical categories.
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.
Innovations In Machine Learning
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Author : Dawn E. Holmes
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-09
Innovations In Machine Learning written by Dawn E. Holmes and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-09 with Computers categories.
Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.
Applications Of Machine Learning
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Author : Prashant Johri
language : en
Publisher: Springer Nature
Release Date : 2020-05-04
Applications Of Machine Learning written by Prashant Johri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-04 with Technology & Engineering categories.
This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
Deep Learning For The Life Sciences
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Author : Bharath Ramsundar
language : en
Publisher: O'Reilly Media
Release Date : 2019-04-10
Deep Learning For The Life Sciences written by Bharath Ramsundar and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-10 with Science categories.
Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working
Drug Discovery And Development Third Edition
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Author : James J. O'Donnell
language : en
Publisher: CRC Press
Release Date : 2019-12-13
Drug Discovery And Development Third Edition written by James J. O'Donnell and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-13 with Medical categories.
Drug Discovery and Development, Third Edition presents up-to-date scientific information for maximizing the ability of a multidisciplinary research team to discover and bring new drugs to the marketplace. It explores many scientific advances in new drug discovery and development for areas such as screening technologies, biotechnology approaches, and evaluation of efficacy and safety of drug candidates through preclinical testing. This book also greatly expands the focus on the clinical pharmacology, regulatory, and business aspects of bringing new drugs to the market and offers coverage of essential topics for companies involved in drug development. Historical perspectives and predicted trends are also provided. Features: Highlights emerging scientific fields relevant to drug discovery such as the microbiome, nanotechnology, and cancer immunotherapy; and novel research tools such as CRISPR and DNA-encoded libraries Case study detailing the discovery of the anti-cancer drug, lorlatinib Venture capitalist commentary on trends and best practices in drug discovery and development Comprehensive review of regulations and their impact on drug development, highlighting special populations, orphan drugs, and pharmaceutical compounding Multidiscipline functioning of an Academic Research Enterprise, plus a chapter on Ethical Concerns in Research Contributions by 70+ experts from industry and academia specialists who developed and are practitioners of the science and business
Artificial Intelligence For Drug Discovery And Development
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Author : Jianfeng Pei
language : en
Publisher: Frontiers Media SA
Release Date : 2021-11-16
Artificial Intelligence For Drug Discovery And Development written by Jianfeng Pei and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Science categories.
Topic editor Alex Zhavoronkov is the founder of Insilico Medicine, a company specializing in AI research. He is also a professor at the Buck Institute for Research on Aging. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
The Future Of Pharmaceutical Product Development And Research
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Author :
language : en
Publisher: Academic Press
Release Date : 2020-08-19
The Future Of Pharmaceutical Product Development And Research written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-19 with Medical categories.
The Future of Pharmaceutical Product Development and Research examines the latest developments in the pharmaceutical sciences, also highlighting key developments, research and future opportunities. Written by experts in the field, this volume in the Advances in Pharmaceutical Product Development and Research series deepens our understanding of the product development phase of drug discovery and drug development. Each chapter covers fundamental principles, advanced methodologies and technologies employed by pharmaceutical scientists, researchers and the pharmaceutical industry. The book focuses on excipients, radiopharmaceuticals, and how manufacturing should be conducted in an environment that follows Good Manufacturing Practice (GMP) guidelines. Researchers and students will find this book to be a comprehensive resource for those working in, and studying, pharmaceuticals, cosmetics, biotechnology, foods and related industries.