Full Description
Artificial Intelligence for Drug Product Lifecycle Applications explains the use of artificial intelligence (AI) in drug discovery and development paths, including the clinical and postapproval phases. This book gives methods for each of the drug development steps, from the fundamentals to postapproval drug product. AI is a synergistic assembly of enhanced optimization strategies with particular applications in pharmaceutical development and advanced tools for promoting cost-effectiveness throughout the 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. This book offers the tools and knowledge to create the right AI strategy to extend the landscape of AI applications across the drug lifecycle. It is 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.
Contents
1. Artificial Intelligence: the foundation principles
2. Artificial Intelligence: A regulatory perspective
3. Automating Drug Discovery
4. Pharmacometrics and machine learning in drug development
5. Multi-omics/genomics in predictive and personalized medicine
6. AI and machine learning in pharmaceutical formulation and manufacturing
7.Process analytics for the manufacturing of nanomedicines: challenges and opportunities
8. The role of artificial intelligence and machine learning in clinical trials
9. AI in Healthcare
