As the regulators push for “vigilant” oversight of our key processes, the natural response is to change our traditional approach to data review, visualization and monitoring, focusing on product quality assurance rather than ensuring simple “compliance” with GXP regulations. For non-traditional GXP software (data visualization/artificial intelligence), a new approach must be established to replace the previous “CSV” framework, which was not designed to evaluate risks in such systems. Regulators call for an approach that demonstrates “credibility”, followed by lifecycle management following QRM principles. In this virtual and in-person workshop, we tackle important steps in the transformation process, including but not limited to:

1. A new and agile Quality System framework to handle implementation of data analytics software and/or AI/ML models that would not be possible using a traditional CSV approach

2. Getting our data into a usable format (FAIR), breaking down data siloes

3. Developing meaningful data/metadata review processes, both routinely (during batch release) and periodically (at meaningful intervals) in accordance with good data governance principles

4. Developing meaningful metrics according to FDA’s QMM protocol, enabling evidence-based decision making so that decisions can be made well before a critical defect

In this two-day hands-on workshop, we will introduce the key concepts of data analytics and data science via hands-on exercises; fostering understanding of these technologies for non-IT / Data Scientists, to support managing these tools within a regulated GXP environment. Some of the regulatory guidance referenced in this course includes:

• Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products (2025)

• Artificial Intelligence in Drug Manufacturing whitepaper (2023)

• Quality Metrics drawn from FDA’s “Quality Management Maturity” whitepaper (2022/2023)

Our afternoon instructor-led case studies will be conducted in small groups and focus on developing our critical thinking skills. The afternoon sessions will enable non-IT participants to:

1. Evaluate new strategies for qualification and validation using the principles of QRM

2. Understand and manage risk due to data migrations & transformations using non-traditional software

3. Transform disparate data sets into a common format to achieve FAIR data principles

4. Build data dashboards to demonstrate vigilant oversight of our key processes

5. Integrate our new data review strategies into existing management review programs

At the conclusion of this workshops, participants will have gained the hands'-on experience necessary to:

• Develop the critical thinking skill necessary to transform an existing data governance structure into a world-class, predictive system

• Develop and review risk management documentation necessary to justify use of data analytics in a regulated GXP environment

• Train and educate colleagues on how data analytics and AI can be used to demonstrate a mature quality system, as we work to democratize the use of data within our organizations

• Prepare their organizations for the proposed updates to EU Annex 11 (2026)

Meet us at the Northeastern University Innovation Campus at Burlington in 2025!

Data Analytics and
Quality Intelligence for Non-IT