Kunzelmann Marco, Wittmann Anja, Presser Beate, Brosig Philipp, Marhoffer Pia Kristin, Haider Marlene Antje, Martin Julia, Berger Martina, Wucherpfennig Thomas
Development Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstraße 65, 88397 Biberach an der Riß, Germany.
HP BioP Operations Network Mammalian, Boehringer Ingelheim Pharma GmbH & Co. KG, Birkendorferstraße 65, 88397 Biberach an der Riß, Germany.
Bioengineering (Basel). 2024 Oct 30;11(11):1089. doi: 10.3390/bioengineering11111089.
Within process development, numerous experimental studies are undertaken to establish, optimize and characterize individual bioprocess unit operations. These studies pursue diverse objectives such as enhancing titer or minimizing impurities. Consequently, Design of Experiment (DoE) studies are planned and analyzed independently from each other, making it challenging to interlink individual data sets to form a comprehensive overview at the conclusion of the development process. This paper elucidates the methodology for constructing a Life-Cycle-DoE (LDoE), which integrates data-driven process knowledge through design augmentations. It delves into the strategy, highlights the challenges encountered and provides solutions for overcoming them. The LDoE approach facilitates the augmentation of an existing model with new experiments in a unified design. It allows for flexible design adaptations as per the requirements of subject matter experts (SME) during process development, concurrently enhancing model predictions by utilizing all available data. The LDoE boasts a broad application spectrum as it consolidates all data generated within bioprocess development into a single file and model. The study demonstrates that the LDoE approach enables a process characterization study (PCS) to be performed solely with development data. Furthermore, it identifies potentially critical process parameters (pCPPs) early, allowing for timely adaptations in process development to address these challenges.
在工艺开发过程中,开展了大量实验研究,以建立、优化和表征各个生物工艺单元操作。这些研究追求不同的目标,如提高滴度或减少杂质。因此,实验设计(DoE)研究是相互独立地进行规划和分析的,这使得在开发过程结束时将各个数据集相互关联以形成全面概述变得具有挑战性。本文阐述了构建生命周期实验设计(LDoE)的方法,该方法通过设计扩充来整合数据驱动的工艺知识。它深入探讨了策略,突出了遇到的挑战,并提供了克服这些挑战的解决方案。LDoE方法有助于在统一设计中用新实验扩充现有模型。它允许根据工艺开发过程中主题专家(SME)的要求进行灵活的设计调整,同时通过利用所有可用数据来增强模型预测。LDoE具有广泛的应用范围,因为它将生物工艺开发过程中生成的所有数据整合到一个文件和模型中。该研究表明,LDoE方法能够仅使用开发数据进行工艺表征研究(PCS)。此外,它能早期识别潜在的关键工艺参数(pCPPs),从而在工艺开发过程中及时进行调整以应对这些挑战。