Kienzle Samuel, Junghans Lisa, Wieschalka Stefan, Diem Katharina, Takors Ralf, Radde Nicole Erika, Kunzelmann Marco, Presser Beate, Nold Verena
Development Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstraße 65, 88397 Biberach an der Riß, Germany.
Institute of Biochemical Engineering, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany.
Bioengineering (Basel). 2025 Mar 19;12(3):319. doi: 10.3390/bioengineering12030319.
Intra-experimental factor setting shifts in intensified design of experiments (iDoE) enhance understanding of bioproduction processes by capturing their dynamics and are thus essential to fulfill quality by design (QbD) ambitions. Determining the influence of process history on the cellular responses, often referred to as memory effect, is fundamental for accurate predictions. However, the current iDoE designs do not explicitly consider nor quantify the influence of process history. Therefore, we propose the one-factor-multiple-columns (OFMC)-format for iDoE planning. This format explicitly describes stage-dependent factor effects and potential memory effects as across-stage interactions (ASIs) during a bioprocess. To illustrate its utility, an OFMC-iDoE that considers the characteristic growth phases during a fed-batch process was planned. Data were analyzed using ordinary least squares (OLS) regression as previously described via stage-wise analysis of the time series and compared to direct modeling of end-of-process outcomes enabled by the OFMC-format. This article aims to provide the reader with a framework on how to plan and model iDoE data and highlights how the OFMC-format simplifies planning, and data acquisition, eases modeling and gives a straightforward quantification of potential memory effects. With the proposed OFMC-format, optimization of bioprocesses can leverage which factor settings are most beneficial in which state of the mammalian culture and thus elevate performance and quality to the next level.
强化实验设计（iDoE）中的实验内因素设置转移通过捕捉生物生产过程的动态变化增强了对这些过程的理解，因此对于实现设计质量（QbD）目标至关重要。确定过程历史对细胞反应的影响（通常称为记忆效应）是进行准确预测的基础。然而，当前的iDoE设计并未明确考虑或量化过程历史的影响。因此，我们提出了用于iDoE规划的单因素多列（OFMC）格式。这种格式将阶段依赖性因素效应和潜在的记忆效应明确描述为生物过程中的跨阶段相互作用（ASI）。为了说明其效用，我们规划了一个考虑补料分批过程中特征性生长阶段的OFMC-iDoE。如前所述，通过对时间序列进行逐阶段分析，使用普通最小二乘法（OLS）回归对数据进行分析，并将其与OFMC格式实现的过程结束时结果的直接建模进行比较。本文旨在为读者提供一个关于如何规划和建模iDoE数据的框架，并强调OFMC格式如何简化规划和数据采集、便于建模并直接量化潜在的记忆效应。通过所提出的OFMC格式，生物过程的优化可以利用哪些因素设置在哺乳动物培养的哪种状态下最有益，从而将性能和质量提升到一个新的水平。
