Dataset as a basis for process modeling of twin-screw wet granulation: A parametric study of residence time distributions and granulation kinetics

Twin-screw wet granulation is a crucial unit operation in shifting from pharmaceutical batch to continuous processes, but granulation kinetics as well as residence times are yet poorly understood. Experimental findings are highly dependent on screw configuration as well as formulation and therefore have limited universal validity. In the study underlying this dataset, an experimental design with a repetitive screw setup was conducted to measure the effect of specific feed load (SFL), liquid-to-solid ratio (L/S) and inclusion of a distributive feed screw on particle size distribution (PSD) and shape as well as residence time distribution of a hydrophilic Lactose/MCC based formulation. An intermediate sampling point was obtained by changing inlet ports along the screw axis. Camera-based particle size analysis (QICPIC) indicated no significant change of PSD between the first and second kneading section except for low L/S and low SFL where fines increase. Mean residence time was approximated as a bilinear fit of L/S and SFL. Moreover, large mass flow pulsations were observed by continuous camera measurements of residence time distribution and correlated to hold-up of the twin-screw granulator. These findings indicate fast granulation kinetics and process instabilities for high mean residence times, questioning current standards of two kneading compartments for wet granulation. The present study further underlines the necessity of developing a multiscale simulation approach including particle dynamics in the future. This dataset should function as a basis for process modeling of twin-screw wet granulation as fully resolved residence time distributions and PSDs can be directly extracted and applied for validation and calibration. Furthermore it contains fully working copies of python tools to analyze the data, verify integrity and make this dataset reusable according to the FAIR principles.<br>

双螺杆湿法制粒（Twin-screw wet granulation）是制药行业从间歇式生产转向连续化生产过程中的关键单元操作，但目前学界对其制粒动力学以及停留时间的认知仍较为匮乏。实验结果高度依赖螺杆构型与处方组成，因此普遍适用性有限。本数据集依托的研究采用重复螺杆配置的实验设计，测定了特定进料负荷（specific feed load, SFL）、液固比（liquid-to-solid ratio, L/S）以及分配进料螺杆的加入对亲水性乳糖/微晶纤维素（hydrophilic Lactose/MCC）基制剂的粒径分布（particle size distribution, PSD）、颗粒形貌以及停留时间分布的影响。研究通过沿螺杆轴调整进料口位置获取了中间采样点数据。基于相机的粒径分析系统（QICPIC）结果显示，除低液固比与低进料负荷组的细粒占比升高外，第一与第二捏合段之间的粒径分布无显著变化。平均停留时间通过液固比与进料负荷的双线性拟合进行估算。此外，通过对停留时间分布的连续相机监测，研究人员观察到显著的物料流脉动现象，并将其与双螺杆制粒机的持料量相关联。上述结果表明，当平均停留时间较高时，制粒动力学较快且过程存在不稳定性，这对当前采用两个捏合腔进行湿法制粒的行业标准提出了质疑。本研究进一步强调了未来开发包含颗粒动力学的多尺度模拟方法的必要性。本数据集可作为双螺杆湿法制粒过程建模的基础，因为其中包含可直接提取并用于模型验证与校准的完整解析停留时间分布及粒径分布数据。此外，数据集还附带可正常运行的Python工具代码，用于数据分析、完整性验证，并遵循FAIR原则实现数据集的可复用性。