Artificial Intelligence in Oncology Drug Discovery and Development
eBook - PDF

Artificial Intelligence in Oncology Drug Discovery and Development

  1. 192 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Artificial Intelligence in Oncology Drug Discovery and Development

About this book

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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Yes, you can access Artificial Intelligence in Oncology Drug Discovery and Development by John W. Cassidy,Belle Taylor, John W. Cassidy, Belle Taylor in PDF and/or ePUB format, as well as other popular books in Computer Science & Bioinformatics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
IntechOpen
Year
2020
Print ISBN
9781789846898
eBook ISBN
9781789858983
Topic
Computer Science
Subtopic
Bioinformatics
Index
Computer Science

Table of contents

  1. Artificial Intelligence in Oncology Drug Discovery and Development
  2. Contents
  3. Preface
  4. Section 1 - AI in Drug Development
  5. Chapter 1 - Introduction: An Overview of AI in Oncology Drug Discovery and Development
  6. Chapter 2 - Applications of Machine Learningin Drug Discovery I: Target Discovery and Small Molecule Drug Design
  7. Section 2 - Structuring Data
  8. Chapter 3 - Dimensionality and Structure in Cancer Genomics: A Statistical Learning Perspective
  9. Chapter 4 - Electronic Medical Records and Machine Learning in Approachesto Drug Development
  10. Section 3 - Drug Repurposing and Clinical Trials
  11. Chapter 5 - Applications of Machine Learning in Drug Discovery II: Biomarker Discovery, Patient Stratification and Pharmacoeconomics
  12. Chapter 6 - Efficacy Evaluation in the Era of Precision Medicine: The Scope for AI
  13. Chapter 7 - AI Enabled Precision Medicine: Patient Stratification, Drug Repurposing and Combination Therapies
  14. Section 4 - Patient Perspectives
  15. Chapter 8 - Toward the Clinic: Understanding Patient Perspectives on AI and Data-Sharing for AI-Driven Oncology Drug Development