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）是制药领域从分批式生产转向连续化工艺流程的关键单元操作，但目前学界对制粒动力学（granulation kinetics）与停留时间（residence time）的认知仍较为匮乏。实验结果高度依赖螺杆构型（screw configuration）与制剂处方，因此普适性有限。本数据集依托的研究中，研究者采用重复螺杆构型的实验方案，测定了单位进料负载（specific feed load, SFL）、液固比（liquid-to-solid ratio, L/S）以及分流进料螺杆的添加对亲水乳糖/微晶纤维素（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（residence time distribution）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。基于摄像头的粒径分析仪（QICPIC）检测结果显示，仅在低L/S与低SFL工况下细颗粒占比升高，其余工况下第一与第二捏合段（kneading section）的粒径分布无显著差异。平均停留时间通过L/S与SFL的双线性拟合（bilinear fit）进行估算。此外，通过对停留时间分布的连续摄像头监测，研究人员观测到显著的物料流脉动，并将其与双螺杆制粒机的持料量（hold-up）相关联。上述结果表明，高平均停留时间工况下会出现快速制粒动力学与过程不稳定性，对当前湿法制粒采用双捏合室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（particle dynamics）的多尺度模拟方法（multiscale simulation approach）的必要性。本数据集可作为双螺杆湿法制粒过程建模（process modeling）的核心基础，因其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与粒径分布数据。此外，数据集还附带可直接运行的Python工具，用于数据分析、完整性校验，以确保本数据集符合FAIR原则（FAIR principles）并具备可复用性。