Screening of the best drying aid for the extract powder of modified Liujunzi decoction based on physical fingerprint
OBJECTIVE To investigate the effects of different drying aids on the hygroscopic property of extract powder of modified Liujunzi decoction (MLJZD),and screen the best drying aid. METHODS MLJZD extract was mixed with β-cyclodextrin,microcrystalline cellulose,lactose,arabic gum,maltodextrin,corn starch,mannitol,dextrin,soluble starch and pre-gelatinized starch at the mass ratio of 1∶0.3 and 1∶0.5,respectively. The extract powder was prepared after vacuum drying. Physical fingerprints were established with 8 physical indexes,including moisture content,bulk density,vibrating-solid density,gap rate,Carr index,Hausner ratio,angle of rest and hygroscopicity,and then similarity evaluation was performed. The matrix hotspot map was drawn to analyze the influence of physical indexes on hygroscopicity. The moisture absorption rate of MLJZD extract powder was measured at room temperature for 2,4,8,10 h and 1,2,3,7 d. The moisture absorption rate-time curve was drawn,and the best auxiliary materials were selected by comparison. RESULTS The similarity evaluation results of physical fingerprint showed that the prepared MLJZD extract powder were stable and the similarities were above 0.90. The matrix hotspot analysis showed that there was significant correlation between bulk density and vibratory density and the moisture absorption rate of the MLJZD extract powder (P<0.05). The moisture absorption rate-time curve analysis showed that the moisture absorption rate of MLJZD extract powder prepared with the mass ratio of 1∶0.5 was lower than prepared with the mass ratio of 1∶0.3. Under both ratios,lactose showed the best drying aid effect,followed by soluble starch and mannitol. CONCLUSIONS Lactose,as the drying aid (under the mass ratio of 1∶0.5),can obviously improve the hygroabsorbance effect of the extract powder of MLJZD,which provides a reference for the selection of auxiliary materials for MLJZD solid preparations.
万方数据
维普
