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The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry
Comprehensive overview on how Artificial Intelligence and Machine Learning can assist in driving and improving the drug discovery process
Stephanie K. Ashenden (Edited by)
9780128200452, Elsevier Science
Paperback, published 28 April 2021
264 pages, 60 illustrations (20 in full color)
23.4 x 19 x 1.8 cm, 0.56 kg
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.
1. Introduction Drug Discovery 2. Intro to ML 3. Data Types 4. Target ID and Val 5. Hit Discovery 6. Lead Optimisation 7. Evaluating Safety and Toxicity 8. Precision Medicine and Finding the 'right patient': Date-driven Identification of Disease Subtypes 9. Image Analysis in Drug Discovery 10. Clinical Trials, Real World Evidence and Digital Medicine 11. To and From the Patient
Subject Areas: Machine learning [UYQM], Expert systems / knowledge-based systems [UYQE], Artificial intelligence [UYQ], Biotechnology [TCB], Pharmacology [MMG]
