Artificial Intelligence in the Pharmaceutical and Healthcare Industry. Employment of AI within Bayer Pharmaceuticals PDF Download
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Author: Francesca Bradaschia
Publisher: GRIN Verlag
ISBN: 3346409376
Category : Computers
Languages : en
Pages : 10
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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.
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.
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: 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: Nathan Brown
Publisher: Royal Society of Chemistry
ISBN: 1839160543
Category : Computers
Languages : en
Pages : 425
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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: Mullaicharam Bhupathyraaj
Publisher: CRC Press
ISBN: 1000994554
Category : Medical
Languages : en
Pages : 181
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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: Yoshiki Oshida
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110717859
Category : Technology & Engineering
Languages : en
Pages : 520
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Book Description
The use of artificial intelligence (AI) in various fields is of major importance to improve the use of resourses and time. This book provides an analysis of how AI is used in both the medical field and beyond. Topics that will be covered are bioinformatics, biostatistics, dentistry, diagnosis and prognosis, smart materials, and drug discovery as they intersect with AI. Also, an outlook of the future of an AI-assisted society will be explored.
Author: Klaus Schwab
Publisher: Currency
ISBN: 1524758876
Category : Business & Economics
Languages : en
Pages : 192
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Book Description
World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress.
Author: Nicole Burkardt
Publisher: GRIN Verlag
ISBN: 3638866998
Category : Business & Economics
Languages : en
Pages : 33
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Book Description
Essay from the year 2007 in the subject Business economics - Trade and Distribution, grade: 74% - A, University of Sunderland, language: English, abstract: International trade can to some extent be explained by the theory of absolute and comparative advantage. By nature, countries have distinctive immobile production factors and hence different relative production costs for the same good/service (Lawler and Seddighi, 2001). The theory of the absolute advantage by Adam Smith is that a country should specialise on the product/service where it has an absolute advantage over any other country in order to increase productivity and output. Ricardo’s theory of the comparative advantage says a country should export products where it has the greatest comparative advantage or where the comparative disadvantage is smallest and should import goods in which its comparative disadvantage is greatest (Trebilcock and Howse, 2005). This model still represents the basis for international trade theory, but it was further modified and reformulated which will be discussed later on. The pharmaceutical industry in Switzerland by looking at innovation, R&D expenditure, export figures and the growth level will be analysed. All this is interrelated to theoretical background of newer trade theories of Vernon, Krugman and Cantwell.
Author: Arman Kilic
Publisher: Academic Press
ISBN: 012822519X
Category : Medical
Languages : en
Pages : 0
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Book Description
Artificial Intelligence and Machine Learning in Healthcare discusses the potential of groundbreaking technologies on the delivery of care. A lot have been said about how artificial intelligence and machine learning can improve healthcare, however there are still many doubts and concerns among health professionals, all of which are addressed in this book. Sections cover History and Basic Overview of AI and ML, with differentiation of supervised, unsupervised and deep learning, Applications of AI and ML in Healthcare, The Future of Healthcare with AI, Challenges to Adopting AI in Healthcare, and ethics and legal processes for implementation. This book is a valuable resource for bioinformaticians, clinicians, graduate students and several members of biomedical field who needs to get up to speed on the revolutionary role of AI and Machine Learning in healthcare. Provides an overview of AI and ML to the medical practitioner who may not be well versed in these fields Encompasses a thorough review of what has been accomplished and demonstrated recently in the fields of AI and ML in healthcare Discusses the future of AI and ML in healthcare, with a review of possible wearable technology and software and how they may be used for medical care
Author: OECD
Publisher: OECD Publishing
ISBN: 9264545190
Category :
Languages : en
Pages : 152
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Book Description
The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises.
