Machine Learning in Drug Development: Part 1
- 1st Edition, Volume 64 - October 28, 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
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.
- 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
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
1. Artificial Intelligence in Small Molecule and Nucleic Acid Research: A Review
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
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
- Edition: 1
- Latest edition
- Volume: 64
- Published: October 28, 2025
- Language: English
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.
Affiliations and expertise
Associate Professor and Associate Director Division of the Laboratory of Biochemical Pharmacology Department of Pediatrics Emory University School of Medicine Children’s Healthcare of Atlanta Atlanta, USAKS
Katherine Seley-Radtke
Prof. Katherine Seley-Radtke group’s NIH-funded research employs a chemical biology approach to
nucleoside, nucleotide and heterocyclic drug discovery and development with therapeutic
emphasis on antiviral, anticancer and antiparasitic targets and overcoming resistance to currently
used drugs. Current focus is targeting Ebola, Zika, Dengue and MERS viruses. She has served as
the Program Director for UMBC’s Chemistry-Biology Interface graduate training program
funded by NIH since 2007. This program promotes hands on cross disciplinary research for
almost 50 PhD students from four departments at UMBC and UMB. She is currently the
Immediate Past President and Secretary-Elect for the International Society of Nucleosides,
Nucleotides and Nucleic Acids and a Board member of the International Society for Antiviral
Research. Prof. Seley-Radtke also serves as a standing member for several NIH study sections
and is an Associate Editor for three scientific journals – Antiviral Chemistry & Chemotherapy,
Molecules – Chemical Biology, and Current Protocols in Chemical Biology.
Affiliations and expertise
Professor of Chemistry and Biochemistry, University of Maryland, Baltimore County, MD, USARead Machine Learning in Drug Development: Part 1 on ScienceDirect