Artificial Intelligence And Machine Learning In Drug Design And Development

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Artificial Intelligence and Machine Learning in Drug Design and Development

Author : Abhirup Khanna,May El Barachi,Supna Jain,Manoj Kumar,Anand Nayyar
Publisher : Wiley-Scrivener
Page : 0 pages
File Size : 49,6 Mb
Release : 2024-07-23
Category : Computers
ISBN : 1394234163

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Artificial Intelligence and Machine Learning in Drug Design and Development by Abhirup Khanna,May El Barachi,Supna Jain,Manoj Kumar,Anand Nayyar Pdf

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 for Drug Discovery and Development

Author : Jianfeng Pei,Alex Zhavoronkov
Publisher : Frontiers Media SA
Page : 229 pages
File Size : 44,6 Mb
Release : 2021-11-16
Category : Science
ISBN : 9782889716494

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Artificial intelligence for Drug Discovery and Development by Jianfeng Pei,Alex Zhavoronkov Pdf

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.

Artificial Intelligence in Drug Discovery

Author : Nathan Brown
Publisher : Royal Society of Chemistry
Page : 425 pages
File Size : 51,9 Mb
Release : 2020-11-04
Category : Computers
ISBN : 9781839160547

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Artificial Intelligence in Drug Discovery by Nathan Brown Pdf

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.

Drug Design using Machine Learning

Author : Inamuddin,Tariq Altalhi,Jorddy Neves Cruz,Moamen Salah El-Deen Refat
Publisher : John Wiley & Sons
Page : 388 pages
File Size : 43,6 Mb
Release : 2022-10-04
Category : Medical
ISBN : 9781394167234

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Drug Design using Machine Learning by Inamuddin,Tariq Altalhi,Jorddy Neves Cruz,Moamen Salah El-Deen Refat Pdf

DRUG DESIGN USING MACHINE LEARNING The use of machine learning algorithms in drug discovery has accelerated in recent years and this book provides an in-depth overview of the still-evolving field. The objective of this book is to bring together several chapters that function as an overview of the use of machine learning and artificial intelligence applied to drug development. The initial chapters discuss drug-target interactions through machine learning for improving drug delivery, healthcare, and medical systems. Further chapters also provide topics on drug repurposing through machine learning, drug designing, and ultimately discuss drug combinations prescribed for patients with multiple or complex ailments. This excellent overview Provides a broad synopsis of machine learning and artificial intelligence applications to the advancement of drugs; Details the use of molecular recognition for drug development through various mathematical models; Highlights classical as well as machine learning-based approaches to study target-drug interactions in the field of drug discovery; Explores computer-aided technics for prediction of drug effectiveness and toxicity. Audience The book will be useful for information technology professionals, pharmaceutical industry workers, engineers, university researchers, medical practitioners, and laboratory workers who have a keen interest in the area of machine learning and artificial intelligence approaches applied to drug advancements.

Data Science, AI, and Machine Learning in Drug Development

Author : Harry Yang
Publisher : CRC Press
Page : 335 pages
File Size : 46,8 Mb
Release : 2022-10-04
Category : Business & Economics
ISBN : 9781000652673

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Data Science, AI, and Machine Learning in Drug Development by Harry Yang Pdf

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 for Drug Development, Precision Medicine, and Healthcare

Author : Mark Chang
Publisher : CRC Press
Page : 372 pages
File Size : 51,9 Mb
Release : 2020-05-07
Category : Business & Economics
ISBN : 9781000766721

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Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare by Mark Chang Pdf

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.

Artificial intelligence in Pharmaceutical Sciences

Author : Mullaicharam Bhupathyraaj,K. Reeta Vijaya Rani,Musthafa Mohamed Essa
Publisher : CRC Press
Page : 265 pages
File Size : 50,9 Mb
Release : 2023-11-23
Category : Medical
ISBN : 9781000994599

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Artificial intelligence in Pharmaceutical Sciences by Mullaicharam Bhupathyraaj,K. Reeta Vijaya Rani,Musthafa Mohamed Essa Pdf

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.

Artificial Intelligence in Oncology Drug Discovery and Development

Author : John Cassidy,Belle Taylor
Publisher : BoD – Books on Demand
Page : 194 pages
File Size : 52,7 Mb
Release : 2020-09-09
Category : Medical
ISBN : 9781789846898

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Artificial Intelligence in Oncology Drug Discovery and Development by John Cassidy,Belle Taylor Pdf

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.

Artificial Intelligence in Drug Design

Author : Alexander Heifetz
Publisher : Humana
Page : 0 pages
File Size : 50,8 Mb
Release : 2022-11-05
Category : Medical
ISBN : 1071617893

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Artificial Intelligence in Drug Design by Alexander Heifetz Pdf

This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.

The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry

Author : Stephanie K. Ashenden
Publisher : Academic Press
Page : 266 pages
File Size : 54,9 Mb
Release : 2021-04-23
Category : Computers
ISBN : 9780128204498

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The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry by Stephanie K. Ashenden Pdf

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

A Handbook of Artificial Intelligence in Drug Delivery

Author : Anil K. Philip,Aliasgar Shahiwala,Mamoon Rashid,Md Faiyazuddin
Publisher : Academic Press
Page : 644 pages
File Size : 50,7 Mb
Release : 2023-03-27
Category : Computers
ISBN : 9780323903738

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A Handbook of Artificial Intelligence in Drug Delivery by Anil K. Philip,Aliasgar Shahiwala,Mamoon Rashid,Md Faiyazuddin Pdf

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

AI to machine learning in Pharmaceuticals

Author : Satyabrata Jena,Dr. Narottam Pal, Dr. V Mohan Goud,Prof. (Dr.) KNV Rao
Publisher : AG PUBLISHING HOUSE (AGPH Books)
Page : 224 pages
File Size : 47,7 Mb
Release : 2022-11-16
Category : Study Aids
ISBN : 9789395936750

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AI to machine learning in Pharmaceuticals by Satyabrata Jena,Dr. Narottam Pal, Dr. V Mohan Goud,Prof. (Dr.) KNV Rao Pdf

The convergence of big data, artificial intelligence (AI), and machine learning (ML) has resulted in a paradigm change in the manner in which novel medications are generated and healthcare is given. It is vital to systematically harness data from varied sources and utilize digital technologies and sophisticated analytics in order to allow data-driven decision making in order to fully capitalize on the breakthroughs in technology that have been made in recent years. The field of data science is now in a position where it has an unparalleled chance to steer such a paradigm shift. This book provides a high-level overview of fundamental concepts in algorithmic theory, data representation techniques, and generative modelling. Use the discovery of antibiotics as a case study in machine learning applied to the production of drugs, and then examine several applications in drug-likeness prediction, antimicrobial resistance, & avenues for further investigation. In the most recent years, there has been a marked increase in the application of machine learning algorithms to the process of drug discovery, and this book offers a comprehensive overview of the rapidly developing field. An introduction to the ways in which machine learning iv and artificial intelligence are being used in the pharmaceutical industry. The introductory discussion focuses on the use of machine learning to better understand medication-target interactions as a means of enhancing drug delivery as well as healthcare and medical systems. In addition to this, give subjects on medication repurposing using machine learning, drug designing, and finally, address drug combinations that are recommended to patients who have several or complicated diseases.

AI And Machine Learning In Pharmaceuticals

Author : Dr. K. ILANGO,Dr. P. VALENTINA
Publisher : AG PUBLISHING HOUSE (AGPH Books)
Page : 247 pages
File Size : 41,7 Mb
Release : 2022-11-08
Category : Study Aids
ISBN : 9789395936576

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AI And Machine Learning In Pharmaceuticals by Dr. K. ILANGO,Dr. P. VALENTINA Pdf

Artificial intelligence (AI) and machine learning (ML) have emerged over the last decade as the cutting-edge technologies most expected to revolutionise the pharmaceutical R&D industry. Revolutionary developments in computer technology and the concomitant evaporation of earlier limits on the collection/processing of enormous amounts of data are contributing factors. Meanwhile, the price of developing and delivering new medicines to the market for patients has skyrocketed. Despite these challenges, the pharmaceutical sector is interested in AI/ML methods because of their predictivity, automation, and the efficiency boost that is projected as a result. Over the last 15–20 years, ML techniques have been increasingly used in the drug development process. Clinical trial design, conduct, and analysis are the most recent areas of drug research to see beneficial disruption from AI/ML. Due to the rising dependence on digital technology in the execution of clinical trials, the COVID-19 pandemic could further drive the employment of AI/ML in clinical trials. Getting through the associated buzzwords and noise is crucial as we progress toward a future where AI/ML is more integrated into R&D. Similarly crucial is the acknowledgement that the scientific method is still relevant for concluding evidence. By doing so, we can better iv evaluate the potential benefits of AI/ML in the pharmaceutical industry and make well-informed decisions on the best use. The purpose of this paper is to clarify important ideas, provide examples of their application, and provide a well-rounded perspective on how to best use AI/ML techniques in research and development.

Artificial Intelligence and Machine Learning in Healthcare

Author : Ankur Saxena,Shivani Chandra
Publisher : Springer Nature
Page : 228 pages
File Size : 44,8 Mb
Release : 2021-05-06
Category : Science
ISBN : 9789811608117

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Artificial Intelligence and Machine Learning in Healthcare by Ankur Saxena,Shivani Chandra Pdf

This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.

Data Science, AI, and Machine Learning in Drug Development

Author : Harry Yang
Publisher : CRC Press
Page : 0 pages
File Size : 45,7 Mb
Release : 2022-09-19
Category : Business & Economics
ISBN : 1003150888

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Data Science, AI, and Machine Learning in Drug Development by Harry Yang Pdf

"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"--