Artificial intelligence and machine learning in drug design and development / edited by Abhirup Khanna... [and 4 others]

Language: English Publisher: Hoboken, NJ : Beverly, MA : John Wiley & Sons, Inc. ; Scrivener Publishing LLC, 2024Copyright date: ©2024Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781394234165 ; 9781394234196; 1394234198; 9781394234189; 139423418XSubject(s): Drug developmentGenre/Form: Electronic books.DDC classification: 615.1/9 LOC classification: RM301.25 | .A78 2024Online resources: Full text is available at Wiley Online Library Click here to view Summary: 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.
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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.

About the Author
Abhirup Khanna is an accomplished professional currently working as an assistant professor at the University of Petroleum and Energy Studies, Dehradun, India. He is an alumnus of The University of Melbourne, Australia. He has authored two books and numerous research publications in the areas of AI, blockchain technology, Internet of Things, and Cloud Computing for international journals and conferences. His research profile demonstrates his commitment to pushing the boundaries of AI and blockchain technology and his potential to drive transformative changes in these fields.

May El Barachi, PhD, is the Director of Computer Science & IT Programs at the University of Wollongong in Dubai, UAE. An Egyptian-Canadian computer scientist, and smart technology expert with degrees in telecom, engineering, computer engineering, and computer science, Dr. El Barachi holds leadership roles in teaching/learning and research. In her current role, she defines the research strategy for the faculty and ensures that the right ecosystem is established for conducting high-impact research.

Sapna Jain, PhD, is an assistant professor at the University of Petroleum and Energy Studies, Dehradun, India. She has earned her PhD in ‘Synthesis of novel bioactive compounds’ from Delhi University. She has published various research papers in renowned national and international journals, as well as two patents concerning the application of a synergistic combination of synthetic and natural products as an antifungal agent.

Manoj Kumar, PhD, is an associate professor at the University of Wollongong in Dubai, UAE as well as the Research Head for Network and Cyber Security Cluster at the university. He obtained his PhD from The Northcap University, Haryana, India. Dr. Kumar has more than 14 years of research, teaching, and corporate experience, and has published more than 175 research articles in international refereed journals and conferences.

Anand Nayyar, PhD, obtained his doctorate from Desh Bhagat University, Punjab, India in 2017 and is currently an assistant professor at the School of Computer Science, Duy Tan University, Viet Nam. He is also the Vice-Chairman of Research and Director of the IoT and Intelligent Systems Lab at Duy Tan University. He has published more than 180 research articles in international refereed journals, 50 books, and has 100+ patents to his credit. He has more than 12,000 citations on Google Scholar.

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