Machine Learning Deep Drug (18 results)

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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

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Taschenbuch. Condition: Neu. Neuware - Artificial Intelligence is transforming how we discover, develop, and deliver medicines. Using Machine Learning in Drug Discovery and Development offers a powerful and practical roadmap for pharmaceutical and biotech professionals to navigate this transformation with confidence.…

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Hardback. Condition: New. Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipeline-from target identification and protein structure prediction to virtual screening, pharmacokinetic modelling, and drug repurposing.Bridging cheminformatics, chemometrics, and computational science, the book offers practical case studies, emerging methodologies, and curated e-resources. Readers will discover how ML/DL techniques are used to predict drug-target interactions, optimize molecular properties, repurpose previously used drugs, and design multi-target therapeutics. Special topics include chemical language models, natural product-based drug discovery, and modelling drug-induced toxicities.With contributions from leading experts worldwide, this book is an essential resource for researchers, postgraduate students, and professionals in medicinal chemistry, pharmacology, and pharmaceutical sciences. It provides both foundational knowledge and advanced applications, equipping readers to harness AI for innovative and efficient drug development.…

Hardback. Condition: New. Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipeline-from target identification and protein structure prediction to virtual screening, pharmacokinetic modelling, and drug repurposing.Bridging cheminformatics, chemometrics, and computational science, the book offers practical case studies, emerging methodologies, and curated e-resources. Readers will discover how ML/DL techniques are used to predict drug-target interactions, optimize molecular properties, repurpose previously used drugs, and design multi-target therapeutics. Special topics include chemical language models, natural product-based drug discovery, and modelling drug-induced toxicities.With contributions from leading experts worldwide, this book is an essential resource for researchers, postgraduate students, and professionals in medicinal chemistry, pharmacology, and pharmaceutical sciences. It provides both foundational knowledge and advanced applications, equipping readers to harness AI for innovative and efficient drug development.…

Hardcover. Condition: Brand New. 792 pages. 6.15x2.00x9.21 inches. In Stock.

Buch. Condition: Neu. Neuware - Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipeline--from target identification and protein structure prediction to virtual screening, pharmacokinetic modelling, and drug repurposing. Bridging cheminformatics, chemometrics, and computational science, the book offers practical case studies, emerging methodologies, and curated e-resources. Readers will discover how ML/DL techniques are used to predict drug-target interactions, optimize molecular properties, repurpose previously used drugs, and design multi-target therapeutics. Special topics include chemical language models, natural product-based drug discovery, and modelling drug-induced toxicities. With contributions from leading experts worldwide, this book is an essential resource for researchers, postgraduate students, and professionals in medicinal chemistry, pharmacology, and pharmaceutical sciences. It provides both foundational knowledge and advanced applications, equipping readers to harness AI for innovative and efficient drug development.…

Hardcover. Condition: new. Hardcover. Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipelinefrom target identification and protein structure prediction to virtual screening, pharmacokinetic modelling, and drug repurposing.Bridging cheminformatics, chemometrics, and computational science, the book offers practical case studies, emerging methodologies, and curated e-resources. Readers will discover how ML/DL techniques are used to predict drugtarget interactions, optimize molecular properties, repurpose previously used drugs, and design multi-target therapeutics. Special topics include chemical language models, natural product-based drug discovery, and modelling drug-induced toxicities.With contributions from leading experts worldwide, this book is an essential resource for researchers, postgraduate students, and professionals in medicinal chemistry, pharmacology, and pharmaceutical sciences. It provides both foundational knowledge and advanced applications, equipping readers to harness AI for innovative and efficient drug development. Explores how machine learning and deep learning revolutionize drug design, covering applications from target discovery to toxicity prediction and virtual screening across the drug pipeline. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Paperback. Condition: new. Paperback. Artificial Intelligence is transforming how we discover, develop, and deliver medicines. Using Machine Learning in Drug Discovery and Development offers a powerful and practical roadmap for pharmaceutical and biotech professionals to navigate this transformation with confidence.Authored by a globally recognized expert with over 25 years of experience in AI, machine learning, and drug development, this book blends scientific depth with real-world insight. It guides readers through every stage of the drug lifecycle - from molecular discovery and lead optimization to clinical trials, regulatory decision-making, and post-launch monitoring - showing how machine learning accelerates innovation while upholding scientific and ethical integrity.Through clear explanations, relatable analogies, and thought-provoking examples, the book transforms complex algorithms into intuitive concepts. Each chapter bridges data science and pharmacology, preparing readers to apply AI techniques responsibly and effectively in real-world scenarios.Perfect for scientists, data professionals, and life science leaders alike, this is more than a guide - it's a blueprint for the intelligent, ethical, and collaborative future of pharmaceutical innovation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condition: new. Hardcover. Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipelinefrom target identification and protein structure prediction to virtual screening, pharmacokinetic modelling, and drug repurposing.Bridging cheminformatics, chemometrics, and computational science, the book offers practical case studies, emerging methodologies, and curated e-resources. Readers will discover how ML/DL techniques are used to predict drugtarget interactions, optimize molecular properties, repurpose previously used drugs, and design multi-target therapeutics. Special topics include chemical language models, natural product-based drug discovery, and modelling drug-induced toxicities.With contributions from leading experts worldwide, this book is an essential resource for researchers, postgraduate students, and professionals in medicinal chemistry, pharmacology, and pharmaceutical sciences. It provides both foundational knowledge and advanced applications, equipping readers to harness AI for innovative and efficient drug development. Explores how machine learning and deep learning revolutionize drug design, covering applications from target discovery to toxicity prediction and virtual screening across the drug pipeline. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condition: new. Hardcover. Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipelinefrom target identification and protein structure prediction to virtual screening, pharmacokinetic modelling, and drug repurposing.Bridging cheminformatics, chemometrics, and computational science, the book offers practical case studies, emerging methodologies, and curated e-resources. Readers will discover how ML/DL techniques are used to predict drugtarget interactions, optimize molecular properties, repurpose previously used drugs, and design multi-target therapeutics. Special topics include chemical language models, natural product-based drug discovery, and modelling drug-induced toxicities.With contributions from leading experts worldwide, this book is an essential resource for researchers, postgraduate students, and professionals in medicinal chemistry, pharmacology, and pharmaceutical sciences. It provides both foundational knowledge and advanced applications, equipping readers to harness AI for innovative and efficient drug development. Explores how machine learning and deep learning revolutionize drug design, covering applications from target discovery to toxicity prediction and virtual screening across the drug pipeline. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…