Where ML is actually being applied on the floor: predictive quality, predictive maintenance, and anomaly detection, and the validation questions each raises.
This course covers where machine learning is currently being applied in pharmaceutical manufacturing operations, predictive quality and predictive maintenance use cases and their data requirements, anomaly detection applications for environmental monitoring and process data, and the validation burden that comes with a model that continues learning after deployment.
A model that improves itself on new data is a fundamentally different validation problem than a static piece of software, since the thing being validated keeps changing. Sites adopting ML tools need to understand this distinction before, not after, deployment.
Completion certificate, PDF slide download, and access to the complete GMP course library from day one.
Start this course →