Machine Learning in Drug Development: Part 2: Volume 65 (Annual Reports in Medicinal Chemistry, Volume 65) - Hardcover

Hardcover

ISBN 10: 0443417636 ISBN 13: 9780443417634

Publisher: Academic Press, 2025

Synopsis

Machine Learning in Drug Development: Part Two, Volume 65 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. Chapters in this volume explore Transforming Modern Drug Discovery with Machine Learning – Applications in Ligand-based Drug Design, Optimizing Multi-Modal Drug Design Through Computational Pocket Mapping and Data Integration, Harnessing AI for Nucleic Acid Drug Discovery: Small Molecule Targeting DNA and RNA, AI-aided Drug Development for Protein Degraders: Design, Lead Identification, and Optimization, and more.

Additional section delve into 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 the Annual Reports on Medicinal Chemistry series
• Includes the latest information in the field

About this title

About the Authors

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.

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.

From the Back Cover

Machine Learning in Drug Development: Part 2, Volume 65 in the Annual Reports on Medicinal Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors.

Chapters in this volume explore the integration of artificial intelligence and machine learning in modern drug discovery, including applications in ligand-based design, protein degraders, nucleic acid targeting, and antiviral drug development. Additional topics include AI-driven strategies for drug target identification, computational pocket mapping, multi-modal data integration, and the use of machine learning in proteomic biomarker discovery.

Edition details

• Publisher: Academic Press
• Publication date: 2025
• Language: English
• ISBN 10: 0443417636
• ISBN 13: 9780443417634
• Binding: Hardcover
• Number of pages: 136
• Editor: Seley-Radtke