Digital Manufacturing at Amgen

By: Shane Greenstein and Sarah Mehta and Kyle R. Myers

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Synopsis: This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics-or therapeutics made from living cells-is subject to unforeseen variability and thus requires a highly controlled environment. Mistakes are costly, given that the manufacturing process takes several weeks from start to finish. Set in early 2020, the case asks students to evaluate two opportunities facing case protagonists Myra Coufal and Chris Garvin. The first involves working with a new team to build a standard multivariate model for a fairly new commercial product with limited production data. The second involves building a predictive machine learning model to automate one step of the manufacturing process for a top-selling product that generates sizable margins. The case includes a supplemental problem set that provides students the opportunity to analyze data and make an informed choice between the two opportunities.