Artificial Intelligence in Drug Discovery for Neglected and Rare Diseases
Buch in deiner Nähe kaufen
Beschreibung
This book offers a comprehensive exploration of how artificial intelligence (AI) is transforming the development of therapeutics for some of the world’s most overlooked infectious diseases, including tuberculosis, malaria, leishmaniasis, and Chagas disease. This book presents state-of-the-art advancements in AI-driven target identification, drug repurposing, and de novo drug design.
It delves into deep learning techniques such as CNNs, RNNs, VAEs, and GANs, for predicting drug-pathogen interactions, enhancing molecular docking, and integrating multi-omics data for biomarker discovery. Practical methodologies are outlined for leveraging AI in ADMET prediction and drug design, with accessible frameworks to support application in real-world research.
The book features case studies that demonstrate how AI addresses key challenges such as drug resistance, toxicity, and vaccine development, while also covering ethical and regulatory considerations critical to ensuring equitable access in low-resource settings.
Designed for scientists in drug discovery, computational biology, and pharmaceutical research, this book serves as an essential guide for applying AI technologies in neglected disease research. By bridging cutting-edge computational methods with practical drug development challenges, it offers a timely and valuable resource for accelerating innovation in global health.
This book offers a comprehensive exploration of how artificial intelligence (AI) is transforming the development of therapeutics for some of the world’s most overlooked infectious diseases, including tuberculosis, malaria, leishmaniasis, and Chagas disease. This book presents state-of-the-art advancements in AI-driven target identification, drug repurposing, and de novo drug design.
It delves into deep learning techniques such as CNNs, RNNs, VAEs, and GANs, for predicting drug-pathogen interactions, enhancing molecular docking, and integrating multi-omics data for biomarker discovery. Practical methodologies are outlined for leveraging AI in ADMET prediction and drug design, with accessible frameworks to support application in real-world research.
The book features case studies that demonstrate how AI addresses key challenges such as drug resistance, toxicity, and vaccine development, while also covering ethical and regulatory considerations critical to ensuring equitable access in low-resource settings.
Designed for scientists in drug discovery, computational biology, and pharmaceutical research, this book serves as an essential guide for applying AI technologies in neglected disease research. By bridging cutting-edge computational methods with practical drug development challenges, it offers a timely and valuable resource for accelerating innovation in global health.
Specifically addresses tuberculosis, leishmaniasis, and other neglected diseases affecting low resource settings Explains AI-powered deep learning models for predicting drug-pathogen interactions and optimizing drug design Includes a special section on ethical and regulatory challenges in AI-driven drug discovery
Autor*in
Geeta Deswal
Themen in »Artificial Intelligence in Drug Discovery for Neglected and Rare Diseases«
Host-Pathogen Interaction AI for Phenotypic Screening QSAR Model Development Immune Profiling Predictive Analytics Tuberculosis Parasitic Diseases