Empowering next-generation pharmaceutical development and quality assurance with AI: a strategy to encourage adoption

We propose that all capacities to emulate human intelligence by a computer system can be considered as AI. With this broad definition, many applications of AI are already in place to enhance control strategies in pharmaceutical CMC (chemistry, manufacturing, and controls). However, further adoption of AI faces formidable challenges including trust, interpretability, talent and culture, and digital readiness. We discuss strategies to overcome these challenges and encourage adoption.

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