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Generative AI for Drug Discovery and Development

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Book Details
Language
English
Publishers
Independently published (7 Jun. 2024)
Weight
0.27 KG
Publication Date
07/06/2024
Pages
191 pages
ISBN-13
9798327877184
Dimensions
15.24 x 1.12 x 22.86 cm
SKU
9798327877184
Author Name
Rakesh Kumar (Author)
With a distinguished career spanning over 22+ years, Rakesh Kumar is an accomplished senior leader renowned for leading global projects across diverse sectors. Their expertise encompasses banking, aerospace, rail, and automotive industries, demonstrating a proven track record in steering multi-million dollar projects from conception to successful completion. Certified as a Project Management Professional (PMP) and Scrum Fundamentals, Rakesh excels in project management processes, including initiation, planning, execution, control, and closure.Armed with a Master's in Engineering from Motilal Nehru National Institute of Technology (MNNIT) and a Bachelor's in Engineering from the National Institute of Technology, Tiruchirappalli, Rakesh has consistently delivered exceptional results. As a leader, they drive teams of 100+ members, fostering operational excellence aligned with business and technology strategies. Based on interaction and lack of depth of understanding of topic during critical project requiements now Rakesh aims to contribute to developing lots of practice materials on the latest technology.Read more about this authorRead less about this author
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In recent years, the intersection of artificial intelligence (AI) and drug discovery has sparked a revolution in pharmaceutical research. The integration of generative AI techniques has opened new frontiers in the quest for novel therapeutics, offering unprecedented opportunities to accelerate drug discovery and development processes.

"Generative AI for Drug Discovery and Development" explores the transformative potential of AI-driven approaches in revolutionizing the pharmaceutical industry. This book serves as a comprehensive guide to the application of generative AI methodologies in drug discovery, covering a wide range of topics including molecular generation, compound screening, predictive modeling, and ethical considerations.

Through a combination of theoretical insights, practical methodologies, and real-world case studies, it offers readers a deep understanding of the principles, challenges, and opportunities inherent in the use of AI for drug discovery. From the historical evolution of generative AI in pharmaceutical research to the latest advancements in deep learning techniques for compound optimization, each chapter delves into key aspects of the drug discovery process and provides valuable insights into how AI-driven approaches are reshaping the landscape of drug development.

Additionally, the book addresses critical considerations such as data quality, interpretability, and ethical implications, ensuring a holistic understanding of the opportunities and challenges posed by generative AI in drug discovery. Written for researchers, practitioners, and students alike, "Generative AI for Drug Discovery and Development" aims to demystify the complexities of AI-driven drug discovery and empower readers with the knowledge and tools needed to harness the full potential of generative AI in advancing pharmaceutical research.

Whether you are a seasoned scientist seeking to stay abreast of the latest innovations or a newcomer looking to explore the cutting-edge technologies shaping the future of medicine, this book offers invaluable insights into the transformative power of generative AI in drug discovery and development. .

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