The first one was the AI Maturity Model that we created in the AI Operations Team. It was our new initiative where pharma companies can self-identify themselves to which level they are in terms of AI adoption. But not only that, they are able to describe what is the journey that they want to take in order to achieve the expected final level in terms of AI adoption. This was a big undertaking which included the FDA’s involvement as well as many pharma companies in conjunction with the AI Operations Team at Xavier University led the AI Maturity Level initiative. This model is free and available on the Xavier site. This is exciting to me because this demonstrates what happens when universities, regulatory bodies, and private enterprises come together to solve problems.
My second favorite takeaway is that AI can be demonstrated as something real in pharma now. This year, we were able to present different use cases. We saw use cases with Pfizer and with AstraZeneca. I had the pleasure to interview Matt Schmucki, the Quality Lean Coach from AstraZeneca, where he explained the process that the AI Operations Task Force did with him and his AstraZeneca team to identify critical factors and potential problems in the granulation operation at AstraZeneca. Matt said, “The results gave the team a new way to look at the data that we wouldn’t have gotten to without using AI.” He continued that, “with over a hundred different process parameters, it’s difficult to know which multivariable interaction to focus on but AI is very good at looking at these numbers and these trends.” This is incredible and wouldn’t have been possible just a few years ago.
It’s a wonderful time to be a part of AI in pharma. AI is real and we have a maturity level model that points to the journey we can follow to realize the promises this technology can bring.
By Toni Manzano, AI Operations Team Lead for Xavier University and Chief Science Officer for Aizon
Toni Manzano is a co-founder and Chief Science Officer of Aizon, a SaaS company that is transforming manufacturing operations with the use of AI and IIoT technologies for pharmaceutical and biotech companies. For over two decades, he has led software projects for international pharmaceutical companies covering the entire production process and supply chain. Today, Toni is a part of the scientific committee with PDA Europe and with the AI Xavier Manufacturing team. He worked as a researcher at the University of Barcelona as a physicist and teaches big data and artificial intelligence in postgraduate courses at the UAB. He is also a member of the Science Experts in the Spanish Parliament on big data and artificial intelligence. He has written numerous articles and holds a dozen international patents related to the encryption, transmission, storage, and processing of large volumes of data for regulated environments in the cloud.