Pharmaceutical manufacturing, quality, and supply chain management can all benefit from the wise application of artificial intelligence (AI). But what approach should pharma manufacturers take to harnessing AI in these areas? And what are the risks?

To explore these questions, we sat down with Pat Day, a principal consultant at Lachman Consultants. Following more than 25 years working inside the pharmaceutical industry, Pat now serves as a consultant, focusing on areas such as risk management, data integrity and data governance, and supply chain logistics — and now, AI.

We discussed:

• Where AI can offer the most immediate benefits in pharmaceutical manufacturing and quality
• The common mistake corporate leaders make in AI initiatives — and the risks that result (hint: protect your institutional knowledge)

• The value of AI “sprints”

• Why companies should approach AI projects as experiments — that are allowed to fail

• What the regulators are saying so far, and why industry shouldn’t wait for agency “permission”

• The opportunity to use AI to develop data skills in quality and regulatory teams

Given all he has seen, Pat offers his advice for rethinking ROI for AI in pharma manufacturing and quality and suggests best practices for thoughtful implementation.

Learn more & connect!

• Visit brandwidthsolutions.com for more information about our services!

• Connect with our guest, Pat Day: LinkedIn

• Learn more about Lachman Consultants

• Connect with our podcast host, Laura Bush: LinkedIn