Computational Approaches in Drug Discovery Development and Systems Pharmacology

Book Computational Approaches in Drug Discovery  Development and Systems Pharmacology Cover

Download or read online Computational Approaches in Drug Discovery Development and Systems Pharmacology PDF book by Rupesh Kumar Gautam in ePUB, PDF or Kindle eBooks. Published by Elsevier in 02 January 2023 the book become immediate popular and critical acclaim in Medical books with total hardcover page 500. Click Download Book button to get book file. Read some info about this book below.

  • Author : Rupesh Kumar Gautam
  • Publisher : Elsevier
  • Release : 02 January 2023
  • ISBN : 9780323993739
  • Page : 500 pages
  • Language : English
  • Total View : 5184 Views
  • File Size : 50,7 Mb

Computational Approaches in Drug Discovery Development and Systems Pharmacology Book PDF summary

Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics. Explains computer use in pharmacology using real-life case studies Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research Describes the role of AI in pharmacology and applications of CADD in various diseases

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