With the development of traditional Chinese medicines (TCM), the sensory evaluation methods of apparent texture and oral texture of TCM oral liquid formulations have increased the difficulty of texture simulation in the preparation of TCM placebos due to the lack of systematic research, especially the selection of fillers. In this study, the contact angle (CA), advancing angle (AA) and receding angle (RA), and friction coefficient (Uf) combined with oral stimulation results were discovered to characterize the spreading, fluid flow and lubrication behavior of 59 types of TCM oral liquid formulations on their oral properties. Besides, optical density (OD)and sedimentation volume (Sv) combined with particle number was verified with the clarity property of TCM oral liquid formulations on apparent texture. Based on these, principal component analysis (PCA) was used to classify TCM oral liquid formulations and analyze the characteristics of each category based on organoleptic properties. And decision tree was used for validation and inference function. Partial least squares (PLS) regression models were established to predict the clarity property (OD), Sv, lubricity (Uf) and spreading property (CA) based on the TCM oral liquid formulation's fundamental properties. The results show that: (i) the apparent texture and oral texture of TCM oral liquid formulations were quite different; (ii) These formulations could be classified well based on their organoleptic parameters (Sv, OD, AA, RA, CA, Uf20, Uf0.05, Uf40). The order of these formu-lations complex for placebo simulation was identified as Group 1 > Group 2 > Group 3; (iii) Density is beneficial to the OD, Uf20 and CA. The final time (FT), settling velocity (SV) and PN of TCM oral liquid formulations correlated positively with Sv; nevertheless, the CA correlated negatively with Uf20. Overall, this study sys-tematically evaluated the apparent and oral texture properties of TCM oral liquid formulations and found the key properties that affect their organoleptic properties. In the light of classification results, it can predicate appli-cability of fillers for TCM placebo texture simulation.
