Journal
JOURNAL OF BIOTECHNOLOGY
Volume 179, Issue -, Pages 17-25Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jbiotec.2014.03.004
Keywords
Biopharmaceutical manufacture; Stochastic discrete-event simulation; Decision tree classification; Multivariate data analysis; Data mining
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Funding
- UK Engineering 82 Physical Sciences Research Council (EPSRC) for the EPSRC Centre for Innovative Manufacturing Emergent Macromolecular Therapies
- consortium of industrial and governmental users
- Engineering and Physical Sciences Research Council [EP/I033270/1] Funding Source: researchfish
- EPSRC [EP/I033270/1] Funding Source: UKRI
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Higher titre processes can pose facility fit challenges in legacy biopharmaceutical purification suites with capacities originally matched to lower titre processes. Bottlenecks caused by mismatches in equipment sizes, combined with process fluctuations upon scale-up, can result in discarding expensive product. This paper describes a data mining decisional tool for rapid prediction of facility fit issues and debottlenecking of biomanufacturing facilities exposed to batch-to-batch variability and higher titres. The predictive tool comprised advanced multivariate analysis techniques to interrogate Monte Carlo stochastic simulation datasets that mimicked batch fluctuations in cell culture titres, step yields and chromatography eluate volumes. A decision tree classification method, CART (classification and regression tree) was introduced to explore the impact of these process fluctuations on product mass loss and reveal the root causes of bottlenecks. The resulting pictorial decision tree determined a series of if-then rules for the critical combinations of factors that lead to different mass loss levels. Three different debottlenecking strategies were investigated involving changes to equipment sizes, using higher capacity chromatography resins and elution buffer optimisation. The analysis compared the impact of each strategy on mass output, direct cost of goods per gram and processing time, as well as consideration of extra capital investment and space requirements. (C) 2014 The Authors. Published by Elsevier B.V.
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