Tag Archives: Artificial Intelligence

ASQ Raleigh Life Sciences Special Interest Group Meeting — November 19, 2025

, , , ,

This event is free and open to the public. No ASQ membership is required. ASQ members will receive RU credits for attending.

Title: Unlocking Efficiency, Consistency, and Insight: Potential Use Cases for Artificial Intelligence in Quality Assurance

Presenter: Nathan Blazei, ASQ-CQA, RAC-US, Senior Director, Strategic Solutions at Kymanox

Bio:

Nathan is a versatile life sciences professional with nearly 25 years of experience across biopharmaceuticals, medical devices, and combination products in individual contributor and leadership roles. He has experience working for start-ups and global manufacturers, as well as in professional services/consulting. He is passionate about commercializing safe and effective products that will improve the quality of life for patients and their caregivers.

Nathan’s career foundation began in engineering, product and process development, manufacturing, continuous improvement, and program management roles. Over time, he made a transition to focus on quality and regulatory compliance to complement his technical experience. At the intersection of these disciplines is where he has found success over the years, as he can provide solutions that are not only technically sound, but also compliant with evolving regulatory requirements and at the leading edge of industry best practices.

Nathan acquired the Certified Quality Auditor (CQA) designation through the American Society for Quality (ASQ) and hold a Regulatory Affairs Certification (RAC-US) through the Regulatory Affairs Professionals Society (RAPS). Additionally, he is currently a Board Member for the Parenteral Drug Association (PDA), Southeast Chapter. Nathan has presented at domestic and international industry events on various topics relevant to the life sciences to share best practices, lessons learned, and new approaches to solving problems.

 

Register here.

SIG Meeting – September 2025

Event, SIG, , , , ,

A group of 11 of us met to “talk quality” in an informal atmosphere over beer and wine on Thursday, September 11, at Frontier RTP – Building 800. Frontier’s Thursday OOO event provided drinks.

We had exciting news to share: one of our first-time attendees in July secured new employment through a connection he made with us!

There was no pre-scheduled topic for discussion, but one of our members asked how those attending thought AI would be used in Quality. It was pointed out that there are different types of AI such as:

  • Generative AI: Capable of creating new content such as text, images, music, or code
  • Machine Learning: Allows systems to learn from data and improve without explicit programming
  • Deep Learning: Uses artificial neural networks to learn complex patterns from large datasets.
  • Natural Language Processing: Understands, interprets, and generates human language
  • Computer Vision: Interprets visual information from images and videos
  • Exper Systems: Emulates decision-making

We expect our companies to experiment with and utilize all of these capabilities. We wonder about supervision and control, though. For example, suppose a vision system is continually updating its defect detection capability. How can we ensure process control and prevent unintended changes that might allow more or different types of defects to slip through or introduce new false failures?

Tim Whetten