COVID-19 Update: We are currently shipping orders daily. However, due to transit disruptions in some geographies, deliveries may be delayed. To provide all customers with timely access to content, we are offering 50% off Science and Technology Print & eBook bundle options. Terms & conditions.
The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry - 1st Edition - ISBN: 9780128200452

The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry

1st Edition

0.0 star rating Write a review
Editor: Stephanie Kay Ashenden
Paperback ISBN: 9780128200452
Imprint: Academic Press
Published Date: 1st March 2021
Page Count: 200
Sales tax will be calculated at check-out Price includes VAT/GST

Institutional Subscription

Secure Checkout

Personal information is secured with SSL technology.

Free Shipping

Free global shipping
No minimum order.

Description

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.

Key Features

  • Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research
  • Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved
  • Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide

Readership

Academic and industrial researchers interested in drug discovery, chemical biology, computational chemistry, medicinal chemistry, and bioinformatics

Table of Contents

  1. Drug discovery in the era of AI and ML
    2. The druggable targets (target identification and validation)
    3. Finding the sweet spot of compound properties – (lead identification – lead optimisation) - Compounds, Chemistry and Cheminformatics
    4. Drug safety and predicting toxicology
    5. Image analytics
    6. Biology and Bioinformatics
    7. Bayesian Approaches to problem solving
    8. Natural Language Processing
    9. Case studies

Details

No. of pages:
200
Language:
English
Copyright:
© Academic Press 2021
Published:
1st March 2021
Imprint:
Academic Press
Paperback ISBN:
9780128200452

About the Editor

Stephanie Kay Ashenden

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.

Affiliations and Expertise

Senior Artificial Intelligence and Machine Learning Data Scientist, AstraZeneca

Ratings and Reviews