Open access peer-reviewed Edited Volume

Artificial Intelligence in Oncology Drug Discovery and Development

Edited by John Cassidy

Cambridge Cancer Genomics

Co-editor:

Belle Taylor

Cambridge Cancer Genomics

There exists a profound conflict at the heart of oncology drug development. The efficiency of the drug development process is falling, leading to higher costs per approved drug, at the same time personalised medicine is limiting the target market of each new medicine. Even as the global economic burden of cancer increases, the current paradigm in drug development is unsustainable. In this book, we discuss the development of techniques in machine learning for improving the efficiency of oncology drug development and delivering cost-effective precision treatment. We consider how to structure data for drug repurposing and target identification, how to improve clinical trials and how patients may view artificial intelligence.

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Knowledge Unlatched

This book has been funded by Knowledge Unlatched. More information on this initiative can be found on http://www.knowledgeunlatched.org

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Artificial Intelligence in Oncology Drug Discovery and DevelopmentEdited by John Cassidy

Published: September 9th 2020

DOI: 10.5772/intechopen.88376

ISBN: 978-1-78985-897-6

Print ISBN: 978-1-78984-689-8

eBook (PDF) ISBN: 978-1-78985-898-3

Copyright year: 2020

Books open for chapter submissions

346 Total Chapter Downloads

Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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