Data Science Ai And Machine Learning In Drug Development

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Data Science, AI, and Machine Learning in Drug Development

Harry Yang
Data Science AI and Machine Learning in Drug Development Book PDF

Author : Harry Yang
Publisher : CRC Press
Page : 335 pages
File Size : 53,7 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

Data Science, AI, and Machine Learning in Drug Development

Harry Yang
Data Science AI and Machine Learning in Drug Development Book PDF

Author : Harry Yang
Publisher : Unknown
Page : 0 pages
File Size : 41,8 Mb
Release : 2022-10
Category : Artificial intelligence
ISBN : 0367714418

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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. 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

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

Stephanie K. Ashenden
The Era of Artificial Intelligence Machine Learning and Data Science in the Pharmaceutical Industry Book PDF

Author : Stephanie K. Ashenden
Publisher : Academic Press
Page : 266 pages
File Size : 48,7 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

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare

Mark Chang
Artificial Intelligence for Drug Development Precision Medicine and Healthcare Book PDF

Author : Mark Chang
Publisher : CRC Press
Page : 372 pages
File Size : 42,6 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 Drug Discovery

Nathan Brown
Artificial Intelligence in Drug Discovery Book PDF

Author : Nathan Brown
Publisher : Royal Society of Chemistry
Page : 425 pages
File Size : 44,6 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.

Artificial intelligence for Drug Discovery and Development

Jianfeng Pei,Alex Zhavoronkov
Artificial intelligence for Drug Discovery and Development Book PDF

Author : Jianfeng Pei,Alex Zhavoronkov
Publisher : Frontiers Media SA
Page : 229 pages
File Size : 48,9 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 Healthcare

Adam Bohr,Kaveh Memarzadeh
Artificial Intelligence in Healthcare Book PDF

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 44,7 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

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

AI to machine learning in Pharmaceuticals

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

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 : 47,5 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.

Artificial Intelligence in Oncology Drug Discovery and Development

John Cassidy,Belle Taylor
Artificial Intelligence in Oncology Drug Discovery and Development Book PDF

Author : John Cassidy,Belle Taylor
Publisher : BoD – Books on Demand
Page : 194 pages
File Size : 43,9 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

Alexander Heifetz
Artificial Intelligence in Drug Design Book PDF

Author : Alexander Heifetz
Publisher : Unknown
Page : 529 pages
File Size : 55,5 Mb
Release : 2021
Category : Artificial intelligence
ISBN : 1071617877

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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.

Drug Design using Machine Learning

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

Author : Inamuddin,Tariq Altalhi,Jorddy Neves Cruz,Moamen Salah El-Deen Refat
Publisher : John Wiley & Sons
Page : 388 pages
File Size : 42,9 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.

Machine Learning for Drug Discovery

Marcelo C. R. Melo,Jacqueline R. M. A. Maasch,Cesar de la Fuente-Nunez
Machine Learning for Drug Discovery Book PDF

Author : Marcelo C. R. Melo,Jacqueline R. M. A. Maasch,Cesar de la Fuente-Nunez
Publisher : American Chemical Society
Page : 218 pages
File Size : 51,7 Mb
Release : 2022-03-11
Category : Computers
ISBN : 9780841299238

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Machine Learning for Drug Discovery by Marcelo C. R. Melo,Jacqueline R. M. A. Maasch,Cesar de la Fuente-Nunez Pdf

Machine Learning for Drug Discovery is designed to suit the needs of graduate students, advanced undergraduates, chemists or biologists otherwise new to this research domain with minimal previous exposure to Machine Learning (ML) methods, or computational scientists with minimal exposure to medicinal chemistry. The e-book covers basic algorithmic theory, data representation methods, and generative modeling at a high level. The authors spotlight antibiotic discovery as a case study in ML for drug development and discuss diverse applications in drug-likeness prediction, antimicrobial resistance, and areas for future inquiry. For a more dynamic learning experience, open-source code demonstrations in Python are included.

Artificial intelligence in Pharmaceutical Sciences

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

Author : Mullaicharam Bhupathyraaj,K. Reeta Vijaya Rani,Musthafa Mohamed Essa
Publisher : CRC Press
Page : 265 pages
File Size : 54,9 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 Drug Design

Alexander Heifetz
Artificial Intelligence in Drug Design Book PDF

Author : Alexander Heifetz
Publisher : Humana
Page : 0 pages
File Size : 40,6 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.

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications

Om Prakash Jena,Bharat Bhushan,Utku Kose
Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications Book PDF

Author : Om Prakash Jena,Bharat Bhushan,Utku Kose
Publisher : CRC Press
Page : 332 pages
File Size : 46,8 Mb
Release : 2022-02-25
Category : Computers
ISBN : 9781000533972

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Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications by Om Prakash Jena,Bharat Bhushan,Utku Kose Pdf

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments. This book aims to endow different communities with the innovative advances in theory, analytical results, case studies, numerical simulation, modeling, and computational structuring in the field of ML/DL models for healthcare applications. It will reveal different dimensions of ML/DL applications and will illustrate their use in the solution of assorted real-world biomedical and healthcare problems. Features: Covers the fundamentals of ML and DL in the context of healthcare applications Discusses various data collection approaches from various sources and how to use them in ML/DL models Integrates several aspects of AI-based computational intelligence such as ML and DL from diversified perspectives which describe recent research trends and advanced topics in the field Explores the current and future impacts of pandemics and risk mitigation in healthcare with advanced analytics Emphasizes feature selection as an important step in any accurate model simulation where ML/DL methods are used to help train the system and extract the positive solution implicitly This book is a valuable source of information for researchers, scientists, healthcare professionals, programmers, and graduate-level students interested in understanding the applications of ML/DL in healthcare scenarios. Dr. Om Prakash Jena is an Assistant Professor in the Department of Computer Science, Ravenshaw University, Cuttack, Odisha, India. Dr. Bharat Bhushan is an Assistant Professor of Department of Computer Science and Engineering (CSE) at the School of Engineering and Technology, Sharda University, Greater Noida, India. Dr. Utku Kose is an Associate Professor in Suleyman Demirel University, Turkey.