基于数值模拟验证的中药原生药粉制备微丸成型规律研究

Study on forming law of pellets prepared from original powder of traditional Chinese medicine based on numerical simulation verification

目的探讨陈皮Citri Reticulatae Pericarpium、枳壳Aurantii Fructus、白芍Paeoniae Radix Alba、牡丹皮Moutan Cortex、木瓜Chaenomelis Fructus、干姜Zingiberis Rhizoma、菊花Chrysanthemi Flos、山药Dioscoreae Rhizoma这8种中药原生药粉制得的软材物理性质与微丸成型性的关系,为后续挤出滚圆制备微丸提供合理的处方依据。方法以微晶纤维素为载体,8种中药原生药粉为模型药,设置挤出机速度为60 r/min、滚圆机速度为1200 r/min,在30%载药量和4种加水量下制得32个处方的软材、挤出物和微丸,测定软材物理性质参数,得到微丸形态,采用数据统计软件分析软材物理性质和微丸形态间的关系,得到微丸成型性预测结果。基于枳壳的物理性质参数采用计算流体动力学(computational fluid dynamics,CFD)进行模拟验证,探讨微丸成型性预测结果的准确性。结果软材的物理性质和微丸的形态有一定的关系,以黏附性/内聚性(Ad/Co)为1级分类指标,硬度/弹性(Ha/Sp)为2级分类指标,硬度×内聚性(Ha×Co)为3级分类指标,黏附性(Ad)为4级分类指标,含水量为5级分类指标,可将微丸分为3类,该分类结果准确性为96.87%。基于中药枳壳物理性质参数的CFD结果表明该模拟结果与枳壳的微丸成型性预测结果相一致。结论该32个处方软材的物理性质与微丸的成型性有一定的相关性,CFD模拟进行微丸成型性的预测具有一定的可行性。

Objective To explore the relationship between the physical properties of soft materials and the formability of pellets made from eight kinds of original powders from traditional Chinese medicine(TCM), namely Chenpi(Citri Reticulatae Pericarpium), Zhiqiao(Aurantii Fructus), Baishao(Paeoniae Radix Alba), Mudanpi(Moutan Cortex), Mugua(Chaenomelis Fructus), Ganjiang(Zingiberis Rhizoma), Juhua(Chrysanthemi Flos), Shanyao(Dioscoreae Rhizoma), and to provide a reasonable basis for the preparation of pellets by extrusion and spheronization. Methods Using microcrystalline cellulose as carrier, eight kinds of TCM original powders as model drugs under 30% drug loading and four kinds of water addition and setting extruder speed at 60 r/min and spheronizer speed at 1200 r/min, 32 prescriptions of soft material, extrusion and pellets were prepared. The physical property parameters of soft material were measured to obtain the morphology pattern of pellets. The relationship between the physical property of soft material and the morphology of pellets was analyzed by using data statistics software to obtain the prediction results of the formability of pellets. Based on the physical property parameters of Aurantii Fructus, computational fluid dynamics(CFD) was used to simulate and verify the experimental results and the accuracy of prediction results of pellet formability was discussed. Results The physical properties of soft materials were related to the morphology of pellets. Using adhesiveness/cohesiveness(Ad/Co) as the first level classification index, hardness/springness(Ha/Sp) as the second level classification index, hardness × cohesiveness(Ha × Co) as the third level classification index, Ad as the fourth level classification index and water content as the fifth level classification index, pellets could be divided into three categories and the accuracy of the classification was 96.87%. The CFD results based on the physical parameters of Aurantii Fructus demonstrated that the simulation results were consistent with the prediction results of the pellet formability. Conclusion There is a certain correlation between the physical properties of the 32 kinds of soft materials and the formability of the pellets. It is feasible to predict the formability of pellets by CFD simulation.