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.
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Table of Contents
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
Authors
Stephanie K. Ashenden Senior Artificial Intelligence and Machine Learning Data Scientist, AstraZeneca. Dr. Ashenden is Senior Artificial Intelligence and Machine Learning Data Scientist at AstraZeneca, working in the Discovery Sciences, IMed-Biotech Unit. She received her PhD in 2018 from the Department of Chemistry, Cambridge University. Dr. Ashenden has three publications, but in very high impact resources (Methods in Enzymology, Journal of Chemical Information and Modeling, and Journal of Medicinal Chemistry).Dr. Ashenden is a very early career researcher, but has an extensive research network, academic and industrial experience, and a drive to conduct and report high quality research. She will be working with more experienced researchers on the project to help guide and offer experience.
