Artificial Intelligence In Drug Development
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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 Drug Development
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Author : Kavita Sharma
language : en
Publisher: Springer Nature
Release Date : 2024-05-30
Artificial Intelligence In Drug Development written by Kavita Sharma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-30 with Law categories.
This book discusses how Artificial Intelligence developments have revolutionized the area of medicine and how companies use them to develop applications. While the book covers the growth of AI in medicine and the early developments in AI based medical tools, it provides an in-depth analysis of the current developments in relation to the area of medical diagnostics. The book focuses on how enterprises and institutes have developed their intellectual property portfolio, particularly patents, in this area. Cross-country patenting analysis helps in understanding key areas of growth in certain markets and also company strategies and arrangements. The introduction of AI based products in market is subject to regulation. The developments in policy and regulation influence the development and deployment of such products into the market. This book brings focus to the development of policy and regulation and how regulatory developments impact the introduction of AI-based healthcare products from a cross-country perspective. Further, how regulatory developments lead to the evolution of standards, build reliability and safety in this area are also examined. The unique aspect of this book is the comprehensive coverage of the dual aspects of the nature and scope of AI-based innovations in health care and the related drug regulatory aspects which are imperative for the understanding for students, researchers, and those who work in this area.
Artificial Intelligence In Drug Discovery
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Author : Nathan Brown
language : en
Publisher: Royal Society of Chemistry
Release Date : 2020-11-04
Artificial Intelligence In Drug Discovery written by Nathan Brown and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-04 with Computers categories.
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.
Benefits And Risks Of Using Artificial Intelligence For Pharmaceutical Development And Delivery
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Author : World Health Organization
language : en
Publisher: World Health Organization
Release Date : 2024-03-25
Benefits And Risks Of Using Artificial Intelligence For Pharmaceutical Development And Delivery written by World Health Organization and has been published by World Health Organization this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-25 with Medical categories.
WHO recognizes that artificial intelligence (AI) holds great promise for pharmaceutical development and delivery. However, AI also presents risks and ethical challenges that must be addressed if societies, health systems and individuals are to fully reap its benefits. This discussion paper examines the expanding application of AI to each step of development and deployment of medicines and vaccines. AI is already used in most steps of pharmaceutical development, and, in the future, it is likely that nearly all pharmaceutical products that come to market will have been “touched” by AI at some point in their development, approval or marketing. Although these uses of AI may have a commercial benefit, it is imperative that use of AI also has public health benefit and appropriate governance.
Ai For Drug Development And Well Being
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Author : Mark Chang
language : en
Publisher:
Release Date : 2020-09-09
Ai For Drug Development And Well Being written by Mark Chang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-09 with categories.
Artificial intelligence (AI) is transforming the practice of medicine. It is helping doctors diagnose patients more accurately, predict treatment effects on individuals, and recommend better treatments. AI is also transforming the drug discovery and development process, helping pharmaceutical researchers to identify and design active drug candidates, and reducing the cost of the clinical testing phase. Recently, the FDA moved toward a new, tailored review framework for artificial intelligence-based medical devices (Gottlieb, April 2019).This book is intended for a broad readership: sufficiently straightforward for college freshmen and informative enough for researchers. Chapter 1 gives a gentle introduction to the five ML categories of learning: supervised, unsupervised, reinforcement, evolutionary and swarm intelligence. Chapters 2 through 6 discuss the key concepts of the main methods in each of the five AI categories and their applications in pharmaceutical research & development and healthcare. Chapter 7 provides a state-of-the-art review of AI applications in prescription drug discovery, development, pharmacovigilance, and healthcare. Chapter 8 discusses artificial general intelligence and its controversies, challenges, and likely future directions. A few equations are included to effectively deliver key concepts and 100 key references are cited to meet researchers' needs. The book is a simplified version of my previous book: Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare. Readers who want to get hands on experiences may explore the book with computer code in R.
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.
Data Science Ai And Machine Learning In Drug Development
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Author : Harry Yang
language : en
Publisher: CRC Press
Release Date : 2022-10-03
Data Science Ai And Machine Learning In Drug Development written by Harry Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-03 with Business & Economics categories.
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
Artificial Intelligence In Oncology Drug Discovery And Development
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Author : John Cassidy
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-09-09
Artificial Intelligence In Oncology Drug Discovery And Development written by John Cassidy and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-09 with Medical categories.
There exists a profound conflict at the heart of oncology drug development. The efficiency of the drug development process is falling, leading to higher costs per approved drug, at the same time personalised medicine is limiting the target market of each new medicine. Even as the global economic burden of cancer increases, the current paradigm in drug development is unsustainable. In this book, we discuss the development of techniques in machine learning for improving the efficiency of oncology drug development and delivering cost-effective precision treatment. We consider how to structure data for drug repurposing and target identification, how to improve clinical trials and how patients may view artificial intelligence.
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 : 2024-07-18
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 2024-07-18 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.