Leveraging Digital Tools to Optimize Manufacturing Processes


In this Pharmaceutical Commerce video interview, Barry Heavey, Life Sciences Supply Chain Lead, Accenture, discusses how companies can leverage digital tools like artificial intelligence and machine learning to optimize manufacturing processes and ensure efficient production.

As drug discovery and clinical development pipelines accelerate, traditional manufacturing methods are struggling to keep pace. How can biopharma companies leverage cutting-edge digital tools like AI and ML to optimize manufacturing processes and ensure efficient production of novel therapies?

Let's be clear on this, one of the reasons that the industry is challenged as this pace of increases is not just that the pace is getting faster for new drug development, but the drugs themselves are getting more complex. And there are more components to the drugs, more complexity in the manufacturing process that needs to be flawless every time. And so, trying to control and understand the chemistry or biochemistry of the manufacturing process is becoming increasingly challenging as the as the drugs become more complex.

So, we believe that there's a strong use case for augmenting the human using advanced analytics and AI to help them more deeply understand the manufacturing process and get to an optimal level of productivity in the manufacturing process as quickly as possible. So that by the time the drug hopefully is approved, the manufacturing processes is as close to optimal and high yield and sustainable and low carbon footprint as is possible. Because historically, products were often launched with low productivity manufacturing process, and it took a long time for companies to use empirical research to optimize that. So, I think we can see advanced analytics helping to get to that optimal process quicker and future.

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