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Anotace knihy

Artificial Intelligence for Drug Product Lifecycle Applications explains the use of artificial intelligence (AI) in drug discovery and development paths including the clinical and post-approval phase. The book gives methods for each of the drug development steps, from the Fundamentals up to Post-approval drug product. AI is a synergistic assembly of enhanced optimization strategies with particular application in pharmaceutical development and advanced tools for promoting cost-effectiveness throughout drug lifecycle. Specifically, AI brings together the potential to improve drug approval rates, reduce development costs, get medications to patients faster and help patients comply with their treatments. Accelerated pharmaceutical development and drug product approval rates will enable larger profits from patent-protected market exclusivity. Artificial Intelligence for Drug Product Lifecycle offers the tools and knowledge to create the right AI strategy to extend the landscape of AI applications across the drug lifecycle. It will be especially useful for pharmaceutical scientists, health care professionals and regulatory scientists, as well as advanced students and postgraduates actively involved in pharmaceutical product and process development involving the use of Artificial Intelligence in drug delivery applications. Classifies AI methodologies and application examples into different categories representing the various steps of the drug development cycleCovers timely literature review combined with clear artwork to improve understandingExamines deep learning, machine learning in drug discovery

Parametry knihy

Zařazení knihy Knihy v angličtině Medicine Other branches of medicine Pharmacology

• Plný název: Artificial Intelligence for Drug Product Lifecycle Applications
• Autor: Alberto Pais, Carla Vitorino, Sandra Nunes, Tânia Cova
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 600
• EAN: 9780323918190
• ISBN: 0323918190
• ID: 44719292
• Rozměry: 234 × 191 mm
• Datum vydání: 01. September 2024

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