Abstract OBJECTIVE To develop a vancomycin individualized dosing-assisted decision platform suitable for practical clinical application scenarios and provide individualized dosing recommendations for the rational use of vancomycin. METHODS Based on the vancomycin population pharmacokinetic model that had been constructed and verified to be feasible, the vancomycin individualized assisted decision-making platform was developed by using Idea2019, JDK1.8, ETL and other software tools. The platform development had gone through three main stages, included ①requirement analysis; ②design stage; ③software testing and optimization. RESULTS The vancomycin individualized assisted decision-making platform, which was successfully developed and applied, had the advantages of simple page, perfect function and convenient operation, and was divided into four main modules according to functions, namely retrieval module, information module, concentration prediction module and reporting module. The platform could connect to the hospital intranet platform to automatically obtain patient information, medication information and blood concentration test results, and calculate individual pharmacokinetic parameters for subsequent concentration prediction based on the embedded population pharmacokinetic model, combined with individual parameters. The concentration prediction module incorporated the Bayesian feedback method with patient medication information, drug concentration measurement results and relevant covariate parameter values, took the guideline-recommended trough concentration and AUC range as the target value, calculated the individualized drug administration scheme that met the target concentration range, and set up custom simulation functions considering the actual clinical application scenarios, which was of more popularization and application value. CONCLUSION Based on the vancomycin population pharmacokinetic model that has been successfully constructed in the previous stage, with the assistance of Idea2019, JDK1.8, ETL and other software tools, a vancomycin individualized dosing-assisted decision platform has successfully constructed, which can more efficiently and conveniently assist monitoring pharmacists to provide individualized dosing advice for clinical use of vancomycin.

ObjectiveAlmond， which is bitter in taste， contains traces of toxic substances. For the sake of the safety of prescriptions containing this medicinal material， the processing method of "soaking in boiling water" was selected. Moreover， through literature research and network pharmacology， the characteristic index of this medicinal material was determined. On this basis， a method was established for the determination of amygdalin in Qingfei Paidu Granules （QFPD） and the transfer rate of it in the processing of this prescription was monitored， aiming at improving the quality control system of QFPD. MethodThe high performance liquid chromatography conditions are as follows： YMC Triart C₁₈ column （4.6 mm × 150 mm， 5 µm）， mobile phase of methanol-water with flow of 1.0 mL·min^-1， column temperature of 35 ℃， and detection wavelength of 210 nm. ResultThe linear curve fitted well and the average recovery of amygdalin was 97.74% with RSD of 4.3%. The transfer rates of amygdalin from the medicinal material to the extract， from extract to concentrate， and from concentrate to granules were investigated with this method. The result showed that the average transfer rate from the medicinal material to the granules was （60±3.91）%. The comparison of transfer rate between the processes suggesting that the extraction of the medicinal material might be the key part influencing the prescription preparation. ConclusionThe method is simple， sensitive， reproducible， stable， and accurate， and the index is reasonable. Thus， the method can be used for the quality control of QFPD and determination of transfer rate of components in the preparation of QFPD. This study further improves the quality control standard of almond in QFPD， which can serve as a reference for the clinical application of QFPD.