As breakthrough cellular therapy discoveries are translated into reliable, commercializable applications, effective stem cell biomanufacturing requires systematically developing and optimizing bioprocess design and operation. This article proposes a rigorous computational framework for stem cell biomanufacturing under uncertainty. Our mathematical tool kit incorporates: high‐fidelity modeling, single variate and multivariate sensitivity analysis, global topological superstructure optimization, and robust optimization. The advantages of the proposed bioprocess optimization framework using, as a case study, a dual hollow fiber bioreactor producing red blood cells from progenitor cells were quantitatively demonstrated. The optimization phase reduces the cost by a factor of 4, and the price of insuring process performance against uncertainty is approximately 15% over the nominal optimal solution. Mathematical modeling and optimization can guide decision making; the possible commercial impact of this cellular therapy using the disruptive technology paradigm was quantitatively evaluated. © 2017 American Institute of Chemical Engineers AIChE J, 64: 3011–3022, 2018

中文翻译：

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不确定条件下的干细胞生物制造：优化红细胞生产的案例研究

随着突破性的细胞疗法发现被转化为可靠的、可商业化的应用，有效的干细胞生物制造需要系统地开发和优化生物工艺设计和操作。本文为不确定条件下的干细胞生物制造提出了一个严格的计算框架。我们的数学工具包包含：高保真建模、单变量和多变量敏感性分析、全局拓扑超结构优化和稳健优化。所提出的生物过程优化框架的优点作为案例研究，从祖细胞生产红细胞的双中空纤维生物反应器得到了定量证明。优化阶段将成本降低了 4 倍，确保过程性能不受不确定性影响的代价大约是标称最优解的 15%。数学建模和优化可以指导决策；定量评估了这种使用颠覆性技术范式的细胞疗法可能产生的商业影响。© 2017 美国化学工程师学会爱车学报, 64: 3011–3022, 2018