Advancing continuous biomanufacturing of monoclonal antibodies using an experimentally validated modeling platform

使用经过实验验证的建模平台推进单克隆抗体的连续生物制造

• 批准号: 10681327
• 负责人: Marianthi Ierapetritou
• 金额: $ 95.81万
• 依托单位: UNIVERSITY OF DELAWARE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10681327
• 关键词: Advancing; continuous; biomanufacturing; monoclonal; antibodies

Project Summary Due to increased demand for biologics, there is an ongoing need to scientifically and commercially advance manufacturing in both upstream cell culture and downstream purification steps. Our goal is to provide an experimental infrastructure complemented by a computational framework to investigate the continuous manufacturing of monoclonal antibodies (mAbs). The modeling approach will be based and validated using specific experimental evidence to enhance our process understanding and improve model performance and utilization during the design phase. The proposed innovations stem from the following objectives that will be delivered as the outcome of this project, namely, 1) To develop a multiscale model for perfusion bioreactor capturing the effects of operating parameters and cell line characteristics on critical quality attributes (CQAs) validated by experimental results; 2) To develop methods for optimizing continuous chromatographic operations, including primary capture and polishing steps, under a range of process conditions for optimal clearance of process- and product-related impurities; and 3) To develop predictive models that will enable determination of optimal operating conditions with direct coupling of upstream and downstream units accounting for product quality attributes. To enable process control, which is the ultimate target of advanced manufacturing, we will explore the design space and identify the relationships between critical process parameters (CPPs), critical material attributes (CMAs), and targeted CQAs. We will develop predictive models for all the important unit operations, validated by experiments, that can be used to determine the design space along with statistical analysis of experimental data to identify all critical parameters/attributes. The validated models will then be used as a virtual tool to perform risk assessment for in-plant downstream operations such as scale-up/start-up/shutdown and compare process operating scenarios. In terms of combining the developed strategies, we envision the integration with a continuous upstream facility to achieve a fully automated continuous biomanufacturing line exploring and optimizing the process interactions. This proof-of-concept line will be used to clearly quantify risk and performance-based metrics.

项目摘要 由于对生物制剂的需求增加，因此持续进行科学和商业上的进步 在上游细胞培养和下游纯化步骤中制造。我们的目标是提供 实验基础设施与计算框架相辅相成，以研究连续 单克隆抗体（mAb）的生产。建模方法将基于和验证 具体的实验证据，以增强我们的过程理解并提高模型性能和 在设计阶段的利用。拟议的创新源于以下目标 作为该项目的结果，即1）开发灌注生物反应器的多尺度模型 捕获操作参数和细胞系特征对关键质量属性（CQAS）的影响 通过实验结果验证； 2）开发用于优化连续色谱操作的方法， 包括主要捕获和抛光步骤，在一系列过程条件下，以最佳清除 过程和产品相关的杂质； 3）开发预测模型，以确定 最佳的运行条件，直接耦合上游和下游单元的产品 质量属性。 为了实现流程控制，这是高级制造的最终目标，我们将探索设计 空间并确定关键过程参数（CPP），关键材料属性之间的关系 （CMA）和目标CQA。我们将为所有重要的单位操作开发预测模型，并经过验证 通过实验，可以用来确定设计空间以及实验的统计分析 数据以识别所有关键参数/属性。然后，经过验证的模型将用作执行的虚拟工具 对下游操作的风险评估，例如扩大/启动/关闭和比较过程 操作场景。在结合发达策略方面，我们设想了整合 连续上游设施，以实现全自动的连续生物制造线探索和 优化过程交互。概念验证线将用于清楚量化风险和 基于绩效的指标。