The biomanufacturing industry is growing rapidly and becoming one of the key drivers of personalized and lifesaving medicines but faces critical challenges, including: (1) deviations in manufacturing caused by human error and lack of process knowledge on the manufacturing floor; (2) the lengthy lead time for process development and manufacturing as well as quality testing before release; and (3) highly regulated commercial product manufacturing systems that are "hard to change" after approval.
Creation of a modularized extensible online training platform on leading-edge process analytical technologies (PAT). The platform can provide large-scale, low-cost, and high quality life-long customized training for industry, non-profits, and college students, support workforce innovation, and facilitate biomanufacturing 4.0. Integrated with existing professional training certification programs on process control, design of experiments, and data analytics, this PAT training platform includes: (1) end-to-end bioprocess hybrid models, which can leverage the existing mechanistic models from each unit operation, provide risk- and science-based production process understanding, and quantify the spatiotemporal causal interdependencies of critical process parameters (CPPs) and critical quality attributes (CQAs); (2) bioprocess risk and sensitivity analyses, which can guide process specifications and troubleshooting, reduce release times, and support quality-by-design (QbD); and (3) risk-based prediction, which can provide a reliable guidance on decision making, accelerate process development, and support manufacturing automation.
In addition, the digital twin-based virtual lab (vLab) and realistic case studies were developed to reinforce the biomanufacturing mechanism learning, support the understanding of bioprocess uncertainties, provide experiential learning, and facilitate real problem-solving skills development.
Creation of a modularized extensible online training platform on process analytical technologies (PAT). The platform can provide large-scale, low-cost, and high-quality life-long customized training for industry, non-profits, and college students.
By utilizing the proposed platform, the initial industrial partners (i.e., Sartorius, Janssen, Genentech, Merck) can: (1) support large-scale workforce training and equip trainees with comprehensive science- and risk-based knowledge on end-to-end biomanufacturing processes, which is required by FDA; (2) minimize costly human errors, reduce lost batches due to out-of-specification, and improve root cause analyses related to deviations; (3) accelerate process development, real-time release, and the move to intensified, robust, flexible and automated biomanufacturing; and (4) periodically update the workforce with leading-edge PAT.
Developed advanced modeling and simulation tools, including an integrated biomanufacturing simulator (upstream and downstream), an N-linked glycosylation mechanistic model, and a dynamic Bayesian network hybrid model with sensitivity analysis.
Created predictive analytics resources, such as a PAT library, Raman spectra sensor monitoring simulator, and implemented Raman spectroscopy-based process monitoring and data analytics techniques.
Built computational tools and libraries, including Python code for global sensitivity analysis and a process control library to enhance understanding of parameter relationships and process performance.
Designed and deployed a user-friendly virtual lab (vLab) interface on AWS, enabling remote access and interactive learning experiences.
Developed comprehensive training materials covering risk analysis, predictive analysis, process modeling, Raman spectroscopy, and process control to support workforce skill development.
Zheng, H., Xie, W., Ryzhov, I. O., & Xie, D. (2022). Policy Optimization in Dynamic Bayesian Network Hybrid Models of Biomanufacturing Processes. INFORMS Journal on Computing, 35(1), 66–82. https://doi.org/10.1287/ijoc.2022.1232
Xie, W., Presenter, PC4.1-206: Modularized PAT Online Training Platform to Accelerate the Workforce Innovation in Biopharmaceuticals Manufacturing, NIIMBL National Meeting, Washington, D.C., July 27, 2022.
Xie, W., Braatz, R. D., Auclair, J., Wolfrum, J., Sinskey, A. J., Springs, S., Trygg, J., Eriksson, L., McCready, C., Li, Z., Saucedo, V., Varughese, J., Carvalho, M., Dziennik, S., Polilli, B., Rode, C., & Jones, T., Modularized PAT Online Training Platform to Accelerate Workforce Innovation in Biopharmaceuticals Manufacturing, NIIMBL Member Forum, Virtual, October 27, 2022.
Xie, W., Braatz, R. D., Auclair, J., Wolfrum, J., Sinskey, A. J., Springs, S., Trygg, J., Eriksson, L., McCready, C., Polilli, B., Rode, C., Jones, T., Li, Z., Saucedo, V., Varughese, J., Carvalho, M., Dziennik, S., Modularized PAT Online Training Platform to Accelerate Workforce Innovation in Biopharmaceuticals Manufacturing, NIIMBL National Meeting, Washington, DC, July 26, 2022.
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Northeastern University
Genentech, Inc.
Janssen Research & Development, LLC
Massachusetts Institute of Technology
Massachusetts Life Sciences Center
Merck Sharp & Dohme LLC
Sartorius Stedim
