Machine Learning in Drug Development: Part 1
- 1st Edition, Volume 64 - October 17, 2025
- Latest edition
- Editors: Joy Feng, Katherine Seley-Radtke
- Language: English
Machine Learning in Drug Development: Part One, Volume 64 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field. Chapters in this release inc… Read more
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Description
Description
Machine Learning in Drug Development: Part One, Volume 64 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field. Chapters in this release include Artificial Intelligence in Small Molecule and Nucleic Acid Research: A Review, AI-aided Drug Development for Protein Degraders: Design, Lead Identification, and Optimization, AI-aided Drug Development for Protein Degraders: Biology Validation, Disease-association, Drug Repurposing, Transforming Modern Drug Discovery with Machine Learning, Artificial Intelligence in the Development of Antiviral Drugs: Progress and Applications, Artificial Intelligence for Drug Target Identification, and Machine Learning in Proteomic Biomarker Discovery.
Key features
Key features
- Provides the authority and expertise of leading contributors from an international board of authors
- Presents the latest release in Annual Reports on Medicinal Chemistry series
- Updated release includes the latest information in the field
Readership
Readership
Ideally suited for chemists engaged in multidisciplinary teams for drug discovery including medicinal chemists and others involved in chemical biology and bio-organic disciplines and computational chemistry
Table of contents
Table of contents
2. AI-aided Drug Development for Protein Degraders: Design, Lead Identification, and Optimization
3. AI-aided Drug Development for Protein Degraders: Biology Validation, Disease-association, Drug Repurposing
4. Transforming Modern Drug Discovery with Machine Learning
5. Artificial Intelligence in the Development of Antiviral Drugs: Progress and Applications
6. Artificial Intelligence for Drug Target Identification
7. Machine Learning in Proteomic Biomarker Discovery
Product details
Product details
- Edition: 1
- Latest edition
- Volume: 64
- Published: October 17, 2025
- Language: English
About the editors
About the editors
JF
Joy Feng
Joy is an Associate Professor of Pediatrics at Emory University with a 25-year experience in the pharmaceutical industry. She received her B.S. from Peking University School of Pharmaceutical Sciences, her Ph.D. in Medicinal Chemistry from Dr. Raymond Bergeron’s lab at the University of Florida School of Pharmacy, and postdoctoral training in enzymology in Dr. Karen Anderson’s lab at Yale University School of Medicine. Joy’s research focuses on drug mechanisms of action, drug combinations, drug resistance, drug metabolism, off-target effects, and toxicity. Joy contributed to the approval of three marketed drugs: Emtricitabine (FTC) for HIV, Sofosbuvir for HCV, and is one of the inventors of Remdesivir, the first FDA-approved direct antiviral for treating COVID-19, and Obeldesivir (GS-5245), currently in clinical trials for the treatment of RSV infection.
KS