目的 采用表面改性技术优化葛根芩连方（Gegen Qinlian Compound，GQC）浸膏粉综合性能，筛选最佳改性剂及改性工艺，为制剂开发提供指导。方法 利用球磨机（ball mill，BM）和喷雾干燥（spray drying，SD）包覆改性技术，选用二氧化硅（SiO₂）、乙基纤维素（ethylcellulose，EC）、硬脂酸镁（magnesium stearate，ST）3种改性剂，制备GQC改性浸膏粉（分别编号为GQC/BM-SiO₂、GQC/BM-EC、GQC/BM-ST和GQC/SD-SiO₂、GQC/SD-EC、GQC/SD-ST）。测定改性前后GQC浸膏粉的吸湿率（H）、含水量（HR）、休止角（α）、松密度（D_a）、振实密度（D_c）、豪斯纳比（IH）、卡尔指数（IC）、间隙率（I_e）、中值径（D₅₀）、粒径分布宽度（span）、粒径范围（width）及比表面积（SSA）总计12个二级指标，绘制物理指纹图谱，进行相似度分析。将各二级指标转换为5个一级指标，采用熵权-变异系数法确定权重，计算浸膏粉综合性能评分，筛选最优方案，扫描电子显微镜（scanning electron microscope，SEM）观察粒子表面形态结构变化。主成分分析（principal component analysis，PCA）法评价二级指标贡献率，偏最小二乘分析（partial least squares analysis，PLSA）法分析关键指标H、SSA的相关性。结果 获得GQC浸膏粉及其6组改性浸膏粉（GQC/BM-SiO₂、GQC/BM-EC、GQC/BM-ST和GQC/SD-SiO₂、GQC/SD-EC、GQC/SD-ST），绘制物理指纹图谱并计算相似度。BM改性时，与未改性GQC浸膏粉相比，GQC/BM-SiO₂、GQC/BM-ST、GQC/BM-EC的相似度分别为0.953、0.920、0.969，改性不明显；SD改性时，与未改性GQC浸膏粉相比，GQC/SD-SiO₂、GQC/SD-ST、GQC/SD-EC的相似度分别为0.477、0.449、0.439，改性效果好。一级指标权重系数为流动性0.104 8，积聚性0.134 1，压缩性0.111 0，稳定性0.133 1，均匀性0.517 0。BM组中，GQC/BM-ST综合评分最高，为50.54，提高了18.92%；SD组改性后综合评分均值为62.65，提高了47.41%，GQC/SD-ST效果最佳，为63.21。SEM显示，硬脂酸镁改性剂均匀包覆浸膏粉表面，粒子表面光滑，大小均匀，圆整度高。PCA显示，IH、D₅₀、span、width、SSA贡献率大。PLSA显示，H与α、IC、width、IH、D₅₀、span、SSA关联显著，与粉体密度相关；SSA与D₅₀、width、span关联显著，粒径及跨距影响最大。结论 表面改性技术可提高GQC浸膏粉综合性能，SD改性效果较好，硬脂酸镁改性剂评分最高，为制剂开发提供参考。

Objective To optimize the comprehensive properties of Gegen Qinlian Compound (GQC, 葛根芩连方) extract powder using surface modification technology, screen the best modifier and process, and provide guidance for formulation development. Methods The ball mill (BM) and spray drying (SD) coating modification techniques were used, and three modifiers, silicon dioxide (SiO₂), ethyl cellulose (EC) and magnesium stearate (ST), were selected. The GQC modified extract powders were prepared and designated GQC/BM-SiO₂, GQC/BM-EC, GQC/BM-ST and GQC/SD-SiO₂, GQC/SD-EC, GQC/SD-ST. All powders were measured secondary indicators, including H, HR, α, D_a, D_c, IH, IC, I_e, D₅₀, span, width and SSA, draw physical fingerprints, and conduct similarity analysis. Convert the secondary indicators into 5 primary indicators, determine the weights using the entropy weight coefficient of variation method, calculate the comprehensive performance score, screen for the optimal solution, and observe the changes in particle surface morphology and structure using scanning electron microscopy (SEM). Principal component analysis (PCA) evaluates the contribution rate of secondary indicators, while partial least squares analysis (PLSA) analyzes the correlation between key indicators H and SSA. Results GQC and six groups of modified powders (GQC/BM-SiO₂, GQC/BM-EC, GQC/BM-ST and GQC/SD-SiO₂, GQC/SD-EC, GQC/SD-ST) were obtained, and physical fingerprints were drawn and similarity was calculated. The similarity between GQC extract powder and GQC/BM-SiO₂, GQC/BM-ST, GQC/BM-EC were 0.953, 0.920, and 0.969 respectively, indicating negligible modification, GQC extract powder compared with GQC/SD-SiO₂, GQC/SD-ST, QC/SD-EC the similarity were 0.477, 0.449, and 0.439, respectively, indicating significant modification effect. The weight coefficients of the first level indicators are: liquidity 0.104 8, accumulation 0.134 1, compressibility 0.111 0, stability 0.133 1, and uniformity 0.517 0. The comprehensive score of magnesium stearate modifier in the BM group was the highest at 50.54, an increase of 18.92%. The mean value was 62.65 an increase of 47.41%, After SD modification, the best modification effect of GQC/SD-ST was 63.21. SEM shows that ST uniformly coats the surface of the extract powder, with smooth particle surfaces, uniform sizes, and high roundness. PCA analysis shows that IH, D₅₀, span, width, and SSA contribute significantly. PLSA analysis showed a significant correlation between H and α, IC, width, IH, D₅₀, span, SSA, which were related to powder density, SSA is significantly associated with D₅₀, width, and span, with particle size and span having the greatest impact. Conclusion Surface modification technology can improve the comprehensive performance of GQC extract powder. SD modification has a better effect, and ST modifier has the highest score, providing reference for formulation development.

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江苏省“青蓝工程”优秀教学团队资助项目（2024）；江苏省“青蓝工程”优秀青年骨干教师资助项目（2022）；泰州市科技支撑计划（社会发展）项目（TS202425）；泰州市科技支撑计划（社会发展）项目（SSF20230030）；江苏省大学生创新创业训练计划项目（202413981004Y）