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Pfizer, one of the world’s premier biopharmaceutical companies, uses machine learning (ML) and artificial intelligence (AI) for near-real-time monitoring of mammalian cell culture bioreactors to boost batch yield and reduce the risk of contamination. Using Amazon Web Services (AWS), the company developed Manufacturing Intelligence Edge (MI Edge), a platform that uses AI and ML for continuous monitoring of bioreactors at its global manufacturing sites. MI Edge increased the frequency of measurements from one sample per day to near-real-time monitoring every few seconds. This improved frequency helps operators to adjust parameters as needed throughout the batch, resulting in greater yield, shorter cycle times, and reduced risk of contamination, delivering more medicine for patients, faster.
This post covers the use case, services, architecture, and sample code implemented for the initial proof of concept (PoC). The steps included are preparing the model, creating an inferencing function, creating a bridge component, and deploying components to the edge.