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Future of Manufacturing Q4 2022

Artificial intelligence is the best tool for turning manufacturing data into actionable knowledge​​​

iStock / Getty Images Plus / SweetBunFactory

Toni Manzano

Co-founder and CSO, Aizon

Luiza Mukaeda

Senior Solutions Engineer, Aizon

Artificial intelligence (AI) is the perfect tool for drug manufacturers to optimise manufacturing processes and improve outcomes, for both the manufacturer and the patient. 

What is driving technological transformation in biopharma manufacturing?

Luiza Mukaeda: Drug manufacturers increasingly realise the importance of producing high-quality drugs in a faster, more efficient and more affordable way to keep up with market demand — but always with patients’ needs in mind. AI is the best way to accomplish this. It improves manufacturers’ processes and outcomes and helps them gain a competitive advantage.

Toni Manzano: To transform information into knowledge, manufacturers first have to extract and analyse data. With a small amount of data, knowledge transformation can be accomplished with a spreadsheet and a calculator. But in today’s manufacturing industry — which generates petabytes of data daily — that approach just isn’t possible anymore. The only way to do it is with AI. It’s the best tool for knowledge creation.

How is this technological revolution different from previous ones?

TM: In previous industrial revolutions, it was always industry — rather than wider society — that was pushing to leverage new technologies. However, in this fourth industrial revolution, society is pushing the industry to leverage new technologies — in this case, AI. Look at the impact of ChatGPT, for instance. Everyone is talking about it. Everyone is excited by it. That’s important because if society is fully behind AI, there will be no going back. Businesses have to understand that if they’re not on board the AI train, they will be left behind.

To transform information into knowledge, manufacturers first have to extract and analyse data.

Toni Manzano

Can you give an example of how AI works in drug manufacturing?

TM: Biopharma manufacturing requires equipment such as reactors, vessels, centrifuges, and more — each of which includes hundreds of sensors. AI can listen to all of the sensors at the same time, study all the variables and predict what will happen during the manufacturing process, based on past performance. It can also interact with the system and fix any issues in real time before problems occur so that manufacturers always have a perfect batch. This is the real power of AI.

LM: It’s always interesting when our customers find out what AI is — and what it is not. AI is not a robot telling them what to do. It’s not replacing human beings. It’s not magic. But it can simplify reams and reams of data in a logical, mathematical way and find outliers much faster than any human can.

How should manufacturers accelerate a transformation programme?

LM: It starts with problem-finding. Manufacturers have to understand the problem they have, and how AI can best help them solve it. Then they need to look at possible barriers to AI adoption. Technical challenges should always be considered, but these can mostly be overcome. The biggest challenge, however, is change management, which is why supporting in-house teams is so vital. Staff have to understand what AI is, what it can do, how it can help them, and the possibilities and opportunities it offers. It’s about awareness and changing mindsets. Setup is easy because everything works in the cloud. All they need is an internet connection.

How do you see AI changing biopharma over the next five years?

TM: Recently, for the first time in history, the US Food and Drug Administration (FDA) published a discussion paper called AI in Drug Manufacturing. This means the FDA also recognises the power of this innovation, which could mark its escalation among manufacturing businesses. In five years, I believe we will see AI become part of drug manufacturers’ marketing because patients will feel more secure knowing that the drugs they take have been supervised 24/7 by AI.

LM: I feel hopeful because I see the industry producing better, more accessible drugs in a more efficient way. It’s an exciting time.

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