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Book Artificial Intelligence for Translational Pharmacology

Download or read book Artificial Intelligence for Translational Pharmacology written by Zhi-Liang Ji and published by Frontiers Media SA. This book was released on 2020-07-28 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book A Handbook of Artificial Intelligence in Drug Delivery

Download or read book A Handbook of Artificial Intelligence in Drug Delivery written by Anil K. Philip and published by Elsevier. This book was released on 2023-03-31 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Data Science  AI  and Machine Learning in Drug Development

Download or read book Data Science AI and Machine Learning in Drug Development written by Harry Yang and published by CRC Press. This book was released on 2022-10-04 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Data Science  AI  and Machine Learning in Drug Development

Download or read book Data Science AI and Machine Learning in Drug Development written by Harry Yang and published by . This book was released on 2022-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The confluence of big data, AI, and machine learning 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 machine learning 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 machine learning 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 detailed description of solutions suitable for practitioners with limited data science expertise

Book Model informed drug development and evidence based translational pharmacology

Download or read book Model informed drug development and evidence based translational pharmacology written by Yu-Wei Lin and published by Frontiers Media SA. This book was released on 2023-01-12 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Principles of Translational Science in Medicine

Download or read book Principles of Translational Science in Medicine written by Martin Wehling and published by Academic Press. This book was released on 2015-04-02 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Translational Science in Medicine: From Bench to Bedside, Second Edition, provides an update on major achievements in the translation of research into medically relevant results and therapeutics. The book presents a thorough discussion of biomarkers, early human trials, and networking models, and includes institutional and industrial support systems. It also covers algorithms that have influenced all major areas of biomedical research in recent years, resulting in an increasing numbers of new chemical/biological entities (NCEs or NBEs) as shown in FDA statistics. The book is ideal for use as a guide for biomedical scientists to establish a systematic approach to translational medicine. Provides an in-depth description of novel tools for the assessment of translatability of trials to balance risk and improve projects at any given stage of product development New chapters deal with translational issues in the fastest growing population (the elderly), case studies, translatability assessment tools, and advances in nanotherapies Details IPR issues of translation, especially for public-private-partnerships Contains contributions from world leaders in translational medicine, including the former NIH director and authorities from various European regulatory institutions

Book Machine Learning and Big Data Analytics  Proceedings of International Conference on Machine Learning and Big Data Analytics  ICMLBDA  2021

Download or read book Machine Learning and Big Data Analytics Proceedings of International Conference on Machine Learning and Big Data Analytics ICMLBDA 2021 written by Rajiv Misra and published by Springer Nature. This book was released on 2021-09-29 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.

Book Artificial Intelligence in Drug Discovery

Download or read book Artificial Intelligence in Drug Discovery written by Nathan Brown and published by Royal Society of Chemistry. This book was released on 2020-11-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Precision Medicine and Artificial Intelligence

Download or read book Precision Medicine and Artificial Intelligence written by Michael Mahler and published by Academic Press. This book was released on 2021-03-12 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on artificial intelligence (AI), its link to precision medicine (PM), and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as AI has gained significant attention during the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems have enabled the generation of large datasets, making autoimmunity an ideal target for AI and precision medicine. More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large datasets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. - Allows the readers to gain an overview on precision medicine for autoimmune diseases leveraging AI solutions - Provides background, milestone and examples of precision medicine - Outlines the paradigm shift towards precision medicine driven by value-based systems - Discusses future applications of precision medicine research using AI - Other aspects covered in the book include regulatory insights, data analytics and visualization, types of biomarkers as well as the role of the patient in precision medicine

Book Oxford Handbook of Ethics of AI

    Book Details:
  • Author : Markus D. Dubber
  • Publisher : Oxford University Press
  • Release : 2020-06-30
  • ISBN : 0190067411
  • Pages : 1000 pages

Download or read book Oxford Handbook of Ethics of AI written by Markus D. Dubber and published by Oxford University Press. This book was released on 2020-06-30 with total page 1000 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."

Book How Translational Medicine Is Progressively Redefining Healthcare

Download or read book How Translational Medicine Is Progressively Redefining Healthcare written by Fritz Dufour, MBA, DESS and published by Fritz Dufour. This book was released on 2017-12-19 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: The preliminary idea behind translational medicine, conducting biological research to treat diseases, is not a new concept. But, scientists have been serious about placing the patient at all levels of the research process – right at the basic science level phase and all the way to the bedside – since only the 1990s. Today, translational research is a scientific field, although multidisciplinary. That innovation stemmed from the discoveries of new diseases and new technologies that allow healthcare professionals to have new perspectives on how to better and more efficiently treat patients. Translational medicine is viable, and it has already proved itself in many areas. Normally, every great discovery or innovation comes with both rewards and challenges, and continuous improvement is what keeps it alive. Translational research, an innovative concept, is not impervious to that rule. This paper examines the antecedents of translational medicine and how it came about. It considers the importance of incorporating basic science, applied science or clinical research, and the patient at every turn of the processes by analyzing the importance of translational research and its direct applications. On the other hand, this paper considers the challenges faced by translational medicine in an age where healthcare costs are skyrocketing, and suggests what can be done to circumvent the downsides. Finally, because the field is relatively new and promising, the discussion that follows also considers the outlook for translational medicine, and how important it is for scientists – artificial intelligence experts, computer, or bioengineers, healthcare professionals and healthcare management professionals – to lay right now the groundwork for future generations.

Book Current and Future Role of Artificial Intelligence in Cardiac Imaging

Download or read book Current and Future Role of Artificial Intelligence in Cardiac Imaging written by Steffen Erhard Petersen and published by Frontiers Media SA. This book was released on 2020-10-09 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Book Pharmaceutical Medicine and Translational Clinical Research

Download or read book Pharmaceutical Medicine and Translational Clinical Research written by Divya Vohora and published by Academic Press. This book was released on 2017-11-14 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pharmaceutical Medicine and Translational Clinical Research covers clinical testing of medicines and the translation of pharmaceutical drug research into new medicines, also focusing on the need to understand the safety profile of medicine and the benefit-risk balance. Pharmacoeconomics and the social impact of healthcare on patients and public health are also featured. It is written in a clear and straightforward manner to enable rapid review and assimilation of complex information and contains reader-friendly features.As a greater understanding of these aspects is critical for students in the areas of pharmaceutical medicine, clinical research, pharmacology and pharmacy, as well as professionals working in the pharmaceutical industry, this book is an ideal resource. Includes detailed coverage of current trends and key topics in pharmaceutical medicine, including biosimilars, biobetters, super generics, and Provides a comprehensive look at current and important aspects of the science and regulation of drug and biologics discovery

Book Network Pharmacology

    Book Details:
  • Author : Shao Li
  • Publisher :
  • Release : 2021
  • ISBN : 9789811607547
  • Pages : 0 pages

Download or read book Network Pharmacology written by Shao Li and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces "network pharmacology" as an emerging frontier subject of systematic drug research in the era of artificial intelligence and big data. Network Pharmacology is an original subject of fusion system biology, bioinformatics, network science and other related disciplines. It emphasizes on starting from the overall perspective of the system level and biological networks, the analysis of the laws of molecular association between drugs and their treatment objects, reveals the systematic pharmacological mechanisms of drugs, and guides the research and development of new drugs and clinical diagnosis and treatment. After it was proposed, network pharmacology has been paid attention by researchers, and it has been rapidly developed and widely used. In order to systematically reveal the biological basis of diagnosis and treatment in traditional Chinese medicine and modern medicine, we proposed a new concept of "network target" for the first time, which has become the core theory of "network pharmacology". The core principle of a network target is to construct a biological network that can be used to decipher complex diseases. The network is then used as the therapeutic target, to which multicomponent remedies are applied. This book mainly includes four parts: 1) The concept and theory of network pharmacology; 2) Common analysis methods, databases and software in network pharmacological research; 3) Typical cases of traditional Chinese medicine modernization and modern drug research based on network pharmacology; 4) Network pharmacology practice process based on drugs and diseases.

Book Artificial intelligence for Drug Discovery and Development

Download or read book Artificial intelligence for Drug Discovery and Development written by Jianfeng Pei and published by Frontiers Media SA. This book was released on 2021-11-16 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Big Data Analysis and Artificial Intelligence for Medical Sciences

Download or read book Big Data Analysis and Artificial Intelligence for Medical Sciences written by Paola Lecca and published by John Wiley & Sons. This book was released on 2024-07-29 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analysis and Artificial Intelligence for Medical Sciences Overview of the current state of the art on the use of artificial intelligence in medicine and biology Big Data Analysis and Artificial Intelligence for Medical Sciences demonstrates the efforts made in the fields of Computational Biology and medical sciences to design and implement robust, accurate, and efficient computer algorithms for modeling the behavior of complex biological systems much faster than using traditional modeling approaches based solely on theory. With chapters written by international experts in the field of medical and biological research, Big Data Analysis and Artificial Intelligence for Medical Sciences includes information on: Studies conducted by the authors which are the result of years of interdisciplinary collaborations with clinicians, computer scientists, mathematicians, and engineers Differences between traditional computational approaches to data processing (those of mathematical biology) versus the experiment-data-theory-model-validation cycle Existing approaches to the use of big data in the healthcare industry, such as through IBM’s Watson Oncology, Microsoft’s Hanover, and Google’s DeepMind Difficulties in the field that have arisen as a result of technological changes, and potential future directions these changes may take A timely and up-to-date resource on the integration of artificial intelligence in medicine and biology, Big Data Analysis and Artificial Intelligence for Medical Sciences is of great benefit not only to professional scholars, but also MSc or PhD program students eager to explore advancement in the field.

Book Machine Learning in Chemistry

Download or read book Machine Learning in Chemistry written by Jon Paul Janet and published by American Chemical Society. This book was released on 2020-05-28 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important