Artificial intelligence in Pharmaceutical Sciences PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Artificial intelligence in Pharmaceutical Sciences PDF full book. Access full book title Artificial intelligence in Pharmaceutical Sciences by Mullaicharam Bhupathyraaj. Download full books in PDF and EPUB format.
Author: Mullaicharam Bhupathyraaj
Publisher: CRC Press
ISBN: 1000994597
Category : Medical
Languages : en
Pages : 265
Get Book
Book Description
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.
Author: Mullaicharam Bhupathyraaj
Publisher: CRC Press
ISBN: 1000994597
Category : Medical
Languages : en
Pages : 265
Get Book
Book Description
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.
Author: Stephanie K. Ashenden
Publisher: Academic Press
ISBN: 0128204494
Category : Computers
Languages : en
Pages : 266
Get Book
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: Nathan Brown
Publisher: Royal Society of Chemistry
ISBN: 1839160543
Category : Computers
Languages : en
Pages : 425
Get Book
Book Description
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.
Author: Anil K. Philip
Publisher: Academic Press
ISBN: 0323903738
Category : Computers
Languages : en
Pages : 644
Get Book
Book Description
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
Author: Ankit Gangwal
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 358
Get Book
Book Description
Major disruption worldover is due to AI, blockchain, 3D organ printing and others. Almost all the industries are being affected by AI. Health sector, particularly pharmaceutical sciences is also not an exception. The book has been designed to cover basics and role of AI in drug discovery, including clinical trials and other departments of health and pharmaceutical sciences. All the content has been compiled after referring and mining hundreds of latest and original first-hand updates from inventors, experts, organizations (who/which are engaged in drug discovery research directly or indirectly through AI) like Insilico, Google, Microsoft, INVIDIA, Novartis, Intel, IBM, Exscientia, Berg, Atomwise, XtalPi, Recursion, H2OAi, Recursion, BenevolentAI, Minds.ai, Deep Genomics, AiCure, Trials.ai, GNS Healthcare, MIT, Okwin, Flatiron, Syapse etc. It was unavoidable to explore content from websites and newspapers as authors were interested to cover latest content. All topics are explained in very simple language with clear aim and outcome using flow charts, tables and infographics. Professionals from medical, pharmacy, nursing and dental and medical imaging arena will find this book very useful. Students of all levels will find book very beneficial as few topics have been just touched, few have been shallow in complexity and rest are covered in detail. Full precautions have been exercised to address the needs of pharmacy students so that they can easily and effortlessly understand the subject matter of this book. Recent examples from various corporates, universities and daily life have found place in this unique book in a very explicit manner. At the end, questions have been added for the readers, mainly students. Authors are always open to suggestions, comments from our valuable readers. We wish you a happy reading......
Author: Alexander Heifetz
Publisher:
ISBN: 9781071617878
Category : Artificial intelligence
Languages : en
Pages : 529
Get Book
Book Description
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.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
Get Book
Book Description
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
Author: Dr. K. ILANGO
Publisher: AG PUBLISHING HOUSE (AGPH Books)
ISBN: 9395936576
Category : Study Aids
Languages : en
Pages : 247
Get Book
Book Description
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.
Author: Mark Chang
Publisher: CRC Press
ISBN: 1000767302
Category : Business & Economics
Languages : en
Pages : 235
Get Book
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: Francesca Bradaschia
Publisher: GRIN Verlag
ISBN: 3346409376
Category : Computers
Languages : en
Pages : 10
Get Book
Book Description
Seminar paper from the year 2021 in the subject Computer Sciences - Artificial Intelligence, grade: 1,0, , language: English, abstract: During the past years, a continuously increasing number of corporations have decided to adopt Artificial Intelligence (AI) systems to improve their efficiency and reduce costs. This research paper aims to analyse the rise, applications, and developments of AI in the pharmaceutical and healthcare industry. Specifically, the employment of AI within the German multinational Bayer Pharmaceuticals is discussed, and further implementation suggestions are outlined. Furthermore, current opportunities, such as epidemic outbreak predictions and image recognition platforms for medication ingestion tracking, and challenges, for example legal issues and ethical challenges, are examined. The future role of AI systems in the pharmaceutical and healthcare industry can hardly be anticipated. Nevertheless, thus far these systems have represented a unique and tremendous asset within societies and companies, and it is most likely that in the course of time their role will be of always greater importance. Nowadays, organizations are defined by higher complexity, changing client demands, increased competition and adoption of new technologies. On the path towards an increased digitalization of economies and societies, the management of information and of knowledge, and the way people connect, collaborate and learn are drastically changing. As more and more possibilities for disruptive change are offered by digitalization, individuals and organizations need to redesign their leadership, innovation, knowledge processes and information practices.
