Machine learning. Tagging. Natural Language Processing (NLP).
You may have heard these terms in relation to artificial intelligence (A.I.).
More and more companies within regulated industries such as pharma, medical devices, and food are using A.I. tools for a variety of tasks, including marketing and demand prediction and deviation analysis. But did you know that deep analysis of regulatory enforcement data can help quality and compliance teams stay on top of global regulatory trends, particularly when it comes to inspections?
At Redica Systems, we have customized AI tools to perform deep analysis of regulatory and compliance data, e.g., FDA 483 observations, Warning Letters, EMA Non-Compliance Reports, etc.
To build up your A.I. expertise when it comes to regulatory enforcement data, on Aug. 3, Redica Systems hosted the webinar, “A.I. for Quality and Compliance Teams,” featuring Redica Systems Senior GMP Quality Expert Jerry Chapman. He has been directly involved with the Redica Systems platform, developing tagging capabilities, Expert Models, and more.
What You Will Learn
- A basic understanding of data sources, machine learning, NLP, and A.I. tools
- Building and applying Expert Models
- Two case studies, one on sterile manufacturing/503B and one on data integrity
Who Should Attend
Any regulatory and compliance professional that relies on regulatory enforcement data (FDA 483 observations, Warning Letters, etc.) for their firm.
About the Presenter
Jerry Chapman is a Senior GMP Quality Expert at Redica Systems. He writes the Redica Systems column “Conference Spotlight” and is working with our data engineers to build machine learning models for analysis of agency enforcement documents. He brings 40 years’ experience in the pharma industry, including 31 years at Eli Lilly in technical and leadership positions in research and product development, manufacturing, plant quality, site quality, corporate quality, and quality systems.
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