CAPE-Lab - Computer-Aided Process Engineering Laboratory, Department of Industrial Engineering, University of Padova, via Marzolo 9, 35131 Padova PD, Italy.
Synthetic Molecule Design & Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN 46074, USA.
Int J Pharm. 2021 Aug 10;605:120808. doi: 10.1016/j.ijpharm.2021.120808. Epub 2021 Jun 16.
In continuous solid-dosage form manufacturing, the powder feeding system is responsible for supplying downstream the correct formulation of the drug product ingredients. The composition of the powder delivered by the feeding system is inferred from the measurements of powder mass flow from the system feeders. The mass flows are, in turn, inferred from the loss in weight measured in the feeder hoppers. Most loss-in-weight feeders post-process the mass flow signal to deliver a smoothed value to the user. However, such estimated mass flows can exhibit a low signal-to-noise ratio. As the feeders are critical elements of the control strategy of the manufacturing line, better instantaneous estimates of mass flow are desirable for improving the quality assurance. In this study, we propose a model-based approach for monitoring the composition of the powder fed to a continuous solid-dosage line. The monitoring system is based on a moving-horizon state estimator, which carries out model-based reconciliation of the feeder mass measurements, thus enabling accurate composition estimation of the powder mixture. Experimental datasets from a direct compression line are used to validate the methodology. Results demonstrate improvement with respect to current industrial solutions.
在连续固体制剂生产中，粉末给料系统负责为下游提供正确配方的药物成分。给料系统输送的粉末组成是根据系统给料器测量的粉末质量流量推断出来的。质量流量反过来又是从给料斗中测量的失重推断出来的。大多数失重给料器对质量流量信号进行后处理，为用户提供平滑的值。然而，这种估计的质量流量可能会表现出低信噪比。由于给料器是制造线控制策略的关键要素，因此更好的瞬时质量流量估计对于提高质量保证是可取的。在这项研究中，我们提出了一种基于模型的方法来监测连续固体制剂生产线中给料的粉末组成。监测系统基于移动窗口状态估计器，对给料器的质量测量进行基于模型的一致性处理，从而能够对粉末混合物进行准确的组成估计。使用直接压缩生产线的实验数据集来验证该方法。结果表明，该方法相对于当前的工业解决方案有所改进。
