Abstract
Artificial intelligence (AI) is not an unknown technique in biopharmaceuticals. There are initiatives in regulatory activities introducing AI algorithms as valid analytical methods, as well as published good practices to implement AI-supported processes in a number of applications (U.S. Food and Drug Administration, 2021). Therefore, two AI algorithms (neural networks and support vector machines) were introduced by the European Pharmacopoeia (Council of Europe, 2017) as valid chemometric methods when applied to analytical data in pharma contexts. A more recent publication elaborated by the US Food and Drug Administration described a methodology for AI application in medical devices (U.S. Food and Drug Administration, 2019). AI works as a multivariate mechanism to create rules and models that represent a reality described by the data generated from the analyzed system and this characteristic brings a unique opportunity to control operations along the drug life cycle. This chapter introduces the context for AI in drug manufacturing process development, quality, regulation, and production. It specifically considers the science, applications, available programs, and a number of use cases presenting evidence of the benefits from AI applications in multivariate process control.
Published Version
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