Chris Dayton, Co-Founder & CEO of Quality Assured AI, explores how AI is being responsibly integrated into the pharmaceutical industry, with a focus on quality management, regulatory compliance, and data security. He discusses the use of closed systems and air-gapped architectures to protect sensitive data, the challenges of deploying AI in regulated environments, and the importance of mitigating hallucinations in AI models. Chris also shares lessons from launching and scaling the platform, transitioning into the CEO role, and building AI literacy within organizations—highlighting how thoughtful AI adoption can drive innovation while reducing operational strain and burnout.Chapters:00:00 Introduction to Quality Assured AI02:51 The Role of AI in Pharmaceuticals06:02 Understanding AI Implementation Challenges09:04 The Importance of Data Security11:50 Navigating Regulatory Compliance15:00 The Evolution of AI in Quality Management17:59 The Human Element in AI Integration20:56 Client Onboarding and Customization23:49 Feedback and Market Reception26:59 Future Growth and Scalability29:50 Parting Thoughts and AdviceGuest Information:Guest's Name: Chris DaytonGuest's Title/Position:  Co-Founder & CEOGuest's Linkedin: https://www.linkedin.com/in/chris-dayton-b414bb57/Company / Affiliation: Quality Assured AI  https://www.qualityassured.ai/Guest's Bio: Chris Dayton is the Co-Founder and CEO of Quality Assured Ai, a company delivering closed-system, on-premise AI solutions purpose-built for pharmaceutical Quality Assurance and Quality Management. With over a decade of experience across protein, cell, and gene therapy manufacturing, he has served as a lead investigator, QMS author, and technical operations manager overseeing QDS authorship and validation approvals. Chris has designed and deployed AI/ML models that streamline deviation drafting, SOP generation, and CAPA support while maintaining strict compliance with FDA, EMA, and MHRA regulatory frameworks. He has consulted with top-25 global pharmaceutical companies on GxP-aligned AI pilots and is a recognized thought leader in AI governance for life sciences, speaking at PDA events and leading AI literacy initiatives for QA and regulatory professionals.Takeaways:Quality Assured AI focuses on the quality and regulatory side of pharmaceuticals.AI can significantly reduce the time needed for documentation in the pharmaceutical industry.Closed system deployments ensure data security and compliance with regulations.Understanding and addressing hallucinations in AI is crucial for reliability.AI should not continuously learn from user interactions in regulated environments.Effective training and onboarding are essential for successful AI integration.Feedback from users highlights the practical benefits of AI in quality management.Collaboration with consulting groups enhances scalability and deployment efficiency.AI literacy is vital for stakeholders in the pharmaceutical industry.Future growth includes expanding AI capabilities to automate more processes. The Healthy Enterprise Podcast is produced by Bullzeye Global Growth Partners  https://bullzeyeglobal.com/

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