Acetaminophen is a well‐known medicine frequently used as analgesic in fever treatment. In pharmaceutical formulation procedure, batch fluidized bed wet granulation is a bottleneck process for the continuous processing of acetaminophen from powder to solid dosage form. To meet the market demand and reduce operating costs, fluid bed wet granulation needs process intensification by converting batch to continuous process. For the scale‐up and batch to continuous conversion procedure, investigation on acetaminophen agglomeration kinetics is necessary. Therefore, this work investigates agglomeration kinetics of acetaminophen through batch fluidized bed wet granulation experiments, and the kinetic parameters are estimated using inverse modeling. Experiments are conducted on a 5‐L capacity pilot scale batch fluidized bed granulator. The effects of various process parameters, namely, binder concentration, spray rate, atomization pressure, and batch size, on particle size distribution are investigated. A 1‐D population balance model with Equi‐Kinetic Energy kernel for agglomeration is simulated to compare with the experimental data. The mean particle diameter increased when binder spray rate and binder concentration are increased and that the mean particle diameter decreased with increase in the atomization pressure and batch size. Experiments data comparison with the model can be used for process intensification with reasonable accuracy.

中文翻译：

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流化床湿法制粒对乙酰氨基酚的团聚动力学研究

对乙酰氨基酚是一种著名的药物，经常在发烧治疗中用作止痛药。在药物配制过程中，分批流化床湿法制粒是将对乙酰氨基酚从粉剂连续转化为固体剂型的瓶颈工艺。为了满足市场需求并降低运营成本，流化床湿法制粒需要通过将批次转换为连续过程来强化过程。对于按比例放大和批量转换为连续转化的程序，对乙酰氨基酚团聚动力学的研究是必要的。因此，这项工作通过分批流化床湿法制粒实验研究了对乙酰氨基酚的团聚动力学，并使用逆模型估算了动力学参数。实验是在5L容量的中试规模分批流化床制粒机上进行的。研究了各种工艺参数（即粘合剂浓度，喷雾速率，雾化压力和批量大小）对粒度分布的影响。模拟了带有等动能内核的一维人口平衡模型，以与实验数据进行比较。当粘合剂喷射速率和粘合剂浓度增加时，平均粒径增加，并且随着雾化压力和批料尺寸的增加，平均粒径减小。实验数据与模型的比较可用于以合理的精度进行过程强化。模拟了带有等动能内核的一维人口平衡模型，以与实验数据进行比较。当粘合剂喷雾速率和粘合剂浓度增加时，平均粒径增加，并且随着雾化压力和批料尺寸的增加，平均粒径减小。实验数据与模型的比较可用于以合理的精度进行过程强化。模拟了带有等动能内核的一维人口平衡模型，以与实验数据进行比较。当粘合剂喷射速率和粘合剂浓度增加时，平均粒径增加，并且随着雾化压力和批料尺寸的增加，平均粒径减小。实验数据与模型的比较可用于以合理的精度进行过程强化。