An automated planning engine for biopharmaceutical production |
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Authors: | Robert C Leachman Lenrick Johnston Shan Li Zuo-Jun Shen |
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Institution: | 1. Dept. of Industrial Engineering and Operations Research, University of California at Berkeley, Berkeley, CA 94720-1777, United States;2. Bioproduction Group, Inc., 1250 Addison Street, Suite 107, Berkeley, CA 94702, United States;3. Zicklin School of Business, Baruch College, The City University of New York, New York, NY 10010-5585, United States |
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Abstract: | We introduce an optimization-based production planning tool for the biotechnology industry. The industry’s planning problem is unusually challenging because the entire production process is regulated by multiple external agencies – such as the US Food and Drug Administration – representing countries where the biopharmaceutical is to be sold. The model is structured to precisely capture the constraints imposed by current and projected regulatory approvals of processes and facilities, as well as capturing the outcomes of quality testing and processing options, facility capacities and initial status of work-in-process. The result is a supply chain “Planning Engine” that generates capacity-feasible batch processing schedules for each production facility within the biomanufacturing supply chain and an availability schedule for finished product against a known set of demands and regulations. Developing the formulation based on distinct time grids tailored for each facility, planning problems with more than 27,000 boolean variables, more than 130,000 linear variables and more than 80,000 constraints are automatically formulated and solved within a few hours. The Planning Engine’s development and implementation at Bayer Healthcare’s Berkeley, CA manufacturing site is described. |
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Keywords: | Biopharmaceutical production |
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