PDF(Pubmed)
Abstract：
The continuous manufacturing of biologics offers significant advantages in terms of reducing manufacturing costs and increasing capacity, but it is not yet widely implemented by the industry due to major challenges in the automation, scheduling, process monitoring, continued process verification, and real-time control of multiple interconnected processing steps, which must be tightly controlled to produce a safe and efficacious product. The process produces a large amount of data from different sensors, analytical instruments, and offline analyses, requiring organization, storage, and analyses for process monitoring and control without compromising accuracy. We present a case study of a cyber-physical production system (CPPS) for the continuous manufacturing of mAbs that provides an automation infrastructure for data collection and storage in a data historian, along with data management tools that enable real-time analysis of the ongoing process using multivariate algorithms. The CPPS also facilitates process control and provides support in handling deviations at the process level by allowing the continuous train to re-adjust itself via a series of interconnected surge tanks and by recommending corrective actions to the operator. Successful steady-state operation is demonstrated for 55 h with end-to-end process automation and data collection via a range of in-line and at-line sensors. Following this, a series of deviations in the downstream unit operations, including affinity capture chromatography, cation exchange chromatography, and ultrafiltration, are monitored and tracked using multivariate approaches and in-process controls. The system is in line with Industry 4.0 and smart manufacturing concepts and is the first end-to-end CPPS for the continuous manufacturing of mAbs.
摘要：
生物制品的连续制造在降低制造成本和提高产能方面具有显著优势,但由于自动化方面的重大挑战，该行业尚未广泛实施，调度,过程监控,继续过程验证，和实时控制多个互连的处理步骤，必须严格控制，以生产安全有效的产品。该过程从不同的传感器产生大量数据，分析仪器,和离线分析，需要组织，storage,和分析过程监测和控制不影响准确性。我们提供了一个用于连续制造mAb的网络物理生产系统（CPPS）的案例研究，该系统为数据历史记录中的数据收集和存储提供了自动化基础设施。以及数据管理工具，可以使用多变量算法对正在进行的过程进行实时分析。CPPS还通过允许连续列车经由一系列互连的缓冲罐重新调整自身并通过向操作员推荐纠正措施来促进过程控制并在过程水平上处理偏差方面提供支持。通过一系列在线和在线传感器，通过端到端过程自动化和数据收集，成功的稳态运行时间为55h。在此之后,下游机组运行中的一系列偏差，包括亲和捕获色谱，阳离子交换色谱，和超滤，使用多变量方法和过程控制进行监控和跟踪。该系统符合工业4.0和智能制造概念，是第一个端到端CPPS，用于连续制造mAb。
