An in silico platform simulating cell metabolic behavior

我的研究项目旨在开发中国仓鼠卵巢（CHO）细胞体外培养代谢行为的计算机模拟平台。CHO现在是业界用于生产下一代治疗药物的主要细胞平台，如用于诊断和各种治疗的单克隆抗体。这一长期目标满足了生物工业对模拟工具的迫切需求，以增强和加速生物过程的开发和优化工作。计算机模拟工具可以测试一系列关于工业感兴趣的各种问题的假设，例如培养基组成，细胞系选择和确定代谢工程的目标，以及确定有效的分批喂料培养策略。在过去的几年里，我的研究项目取得了显著的进展和重要的贡献。我已经证明，描述CHO细胞代谢通量动力学的数学模型可以模拟生物反应器培养，并识别相同来源的细胞系在分批培养和补料分批培养条件下不同培养基中的行为差异。此外，我还展示了建模方法对于研究医学和环境问题中涉及的各种细胞类型也很有用。在这些结果的支持下，在社区的兴趣和鼓励下，我现在提议进一步开发我的计算机平台，旨在加强其在广泛的工业和医疗应用中的预测能力。更具体地说，我的研究计划将分为三个不同的协同研究轴，每个轴至少由一名博士生进行。第一个研究轴将包括重访用于描述酶动力学的数学公式。这些工作应该导致建模方法的数学验证，从而确认其与社区的相关性。第二个研究轴将解决代谢现象，即Warburg效应，它限制CHO细胞的生产力并导致大量乳酸的释放。这项工作也将对基于代谢疗法的癌症治疗方法产生影响；肿瘤细胞特别表现出Warburg效应。第三个研究轴将使用芯片平台确定有效的间歇培养管理策略，从而证明其在实现这一目标方面的有用性。总的来说，这三个连贯和相互协同的研究轴应该导致一个预测性的硅平台。

My research program aims to develop an in silico simulation platform for Chinese Hamster Ovary (CHO) cells metabolic behavior in in vitro culture. CHO is now the major cell platform used by industry to produce next-generation therapeutics such as monoclonal antibodies used in diagnostics and in various therapies. This long-term objective meets bioindustry's critical need for access to a simulation tool enhancing and accelerating bioprocess development and optimization work. A computer simulation tool can allow testing a range of hypotheses on various issues of interest to industry, such as medium composition, cell line selection and identifying targets for metabolic engineering, as well as identifying efficient fed-batch culture strategies. My research program has made significant progress and important contributions in the past few years. I have demonstrated that a mathematical model describing flux kinetics of CHO cells metabolism can simulate bioreactor cultures and identify behavioral differences between cell lines of the same origin, when they are submitted to different culture media under batch and fed-batch culture conditions. Moreover, I showed the modeling approach is also useful for studying various cell types involved in medical and environmental problematics. Backed by these results and with interest and encouragement from the community, I am now proposing further development of my in silico platform, aiming to strengthen its predictive capacity for use in a wide spectrum of industrial and medical applications. More specifically, my research program will be declined into three distinct synergistic research axes, each conducted at least by a Ph.D. student. The first research axis will consist of revisiting mathematical formulations used to describe enzymes kinetics. These works should result in a mathematical validation of the modeling approach, and thus confirm its relevance for the community. A second research axis will address a metabolic phenomenon, the Warburg effect, which limits CHO cells productivity and resulting in the release of significant amount of lactate. This work shall also have an impact on cancer treatment approaches based on metabolic therapies; tumor cells specifically exhibit the Warburg effect. A third research axis will identify efficient fed-batch culture management strategies using the in silico platform, thus demonstrating its usefulness in achieving this end. Overall, these three coherent and mutually synergistic research axes should lead to a predictive in silico platform.