Author: Ramin Homayouni
Publisher: Frontiers Media SA
ISBN: 2832518915
Category : Science
Languages : en
Pages : 116

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Book Description

Author: Ramin Homayouni
Publisher: Frontiers Media SA
ISBN: 2889765393
Category : Science
Languages : en
Pages : 90

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Book Description

Author: Harry Yang
Publisher: CRC Press
ISBN: 100065267X
Category : Business & Economics
Languages : en
Pages : 335

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Book Description
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

Author: Daniel D. Lee
Publisher: SkyCuration
ISBN:
Category : Computers
Languages : en
Pages : 228

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Book Description
"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

Author: Stephanie K. Ashenden
Publisher: Academic Press
ISBN: 0128204494
Category : Computers
Languages : en
Pages : 266

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Book Description
The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide

Author: Mark Chang
Publisher: CRC Press
ISBN: 1000766721
Category : Business & Economics
Languages : en
Pages : 372

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Book Description
Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.

Author: Abhirup Khanna
Publisher: John Wiley & Sons
ISBN: 1394234171
Category : Computers
Languages : en
Pages : 737

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Book Description
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.

Author: Mbuso Mabuza
Publisher: Lekwandza Media
ISBN:
Category : Medical
Languages : en
Pages : 0

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Book Description
Artificial intelligence (AI) is a simulation of the process of human intelligence through computers. AI has cemented its status as a powerful technology with the ability to propel a paradigm shift in healthcare and medicine of the 21st century and the future. The insights and values gained from AI and its subset, machine learning, are essential for predicting health outcomes and improving decision-making in healthcare and medicine. AI can offer revolutionary insights into medicine, through data from genetics, proteomics and other life sciences that advance the process of drug discovery and development. Discovering drugs is a crucial first step in the biopharmaceutical value chain. Drug discovery is a long, expensive and often unsuccessful process. The biopharmaceutical industry makes efforts to employ AI to improve drug discovery, reduce research and development costs, reduce the time and cost of early drug discovery, and support predicting potential risks/side effects in late clinical trials that can be useful in avoiding traumatic events in clinical trials. The rapid growth in life sciences and machine learning algorithms has led to enormous statistical access to the growth of AI-based start-ups focused on drug innovation in recent years. The growing need to curb drug discovery costs and reduce time involved in the drug development process, the rising adoption of cloud-based applications and services, and the impending patent expiry of blockbuster drugs are some of the key factors driving the growth of this market. However, shortage of AI workforce and ambiguous regulatory guidelines for medical software and lack of data sets in this field are some of the factors expected to restrain the growth of this market in the coming years.

Author: Brian S. Hilbush
Publisher: John Wiley & Sons
ISBN: 1119745632
Category : Technology & Engineering
Languages : en
Pages : 301

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Book Description
Learn how AI and data science are upending the worlds of biology and medicine In Silico Dreams: How Artificial Intelligence and Biotechnology Will Create the Medicines of the Future delivers an illuminating and fresh perspective on the convergence of two powerful technologies: AI and biotech. Accomplished genomics expert, executive, and author Brian Hilbush offers readers a brilliant exploration of the most current work of pioneering tech giants and biotechnology startups who have already started disrupting healthcare. The book provides an in-depth understanding of the sources of innovation that are driving the shift in the pharmaceutical industry away from serendipitous therapeutic discovery and toward engineered medicines and curative therapies. In this fascinating book, you'll discover: An overview of the rise of data science methods and the paradigm shift in biology that led to the in silico revolution An outline of the fundamental breakthroughs in AI and deep learning and their applications across medicine A compelling argument for the notion that AI and biotechnology tools will rapidly accelerate the development of therapeutics A summary of innovative breakthroughs in biotechnology with a focus on gene editing and cell reprogramming technologies for therapeutic development A guide to the startup landscape in AI in medicine, revealing where investments are poised to shape the innovation base for the pharmaceutical industry Perfect for anyone with an interest in scientific topics and technology, In Silico Dreams also belongs on the bookshelves of decision-makers in a wide range of industries, including healthcare, technology, venture capital, and government.

Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309679591
Category : Medical
Languages : en
Pages : 143

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Book Description
On March 24, 2020, a 1-day public workshop titled The Role of Digital Health Technologies in Drug Development was convened by the National Academies of Sciences, Engineering, and Medicine. This workshop builds on prior efforts to explore how virtual clinical trials facilitated by digital health technologies (DHTs) might change the landscape of drug development. To explore the challenges and opportunities in using DHTs for improving the probability of success in drug R&D, enabling better patient care, and improving precision medicine, the workshop featured presentations and panel discussions on the integration of DHTs across all phases of drug development. Throughout the workshop, participants considered how DHTs could be applied to achieve the greatest impactâ€"and perhaps even change the face of how clinical trials are conductedâ€"in ways that are also ethical, equitable, safe, and effective. This publication summarizes the presentations and discussions from the workshop.