黑骨藤追风活络胶囊制备工艺、化学成分分析方法及作用机制研究数据集
收藏资源简介：
1、数据采集：根据苗医药理论、风寒湿痹症状及其诱因、药材药性药味及其主治功能等进行中药材筛选，采集中药材品种、中药材用量、加工工序、工艺名称、处理方式、工艺指标、工艺参数、实验数据等； 2、数据处理： （1）通过抗炎、镇痛等药效学实验验证，经数据清洗（如剔除误差）、数据分析（如趋势分析法等），形成制备工艺数据集，获得药材名称、加工工序、工艺名称、处理方式、工艺指标、工艺参数等。 （2）UPLC-Q-TOF-MS、网络药理学、分子对接及体外细胞实验等，经数据清洗、统计及分析等，形成化学成分分析方法关键数据集以及作用机制研究数据集，获得色谱条件、质谱条件、供试品配制方法等，同时通过药材-活性成分-交集靶点网络的构建，获取作用靶点及其影响规律。 3、数据应用：适用于中风湿病治疗药物的生产、工艺改进、新药研发等场景，可为制剂生产过程控制提供数据支持，有利于提升产业化效率，促进规模化生产，促进质量控制。为阐明该药物质基础和治疗作用机制提供数据支撑，有利于该药的推广使用。
1. Data Collection: Based on Miao medical theory, symptoms of wind-cold-damp arthralgia and their inducing factors, as well as medicinal properties, tastes and indicated therapeutic functions of medicinal herbs, Chinese medicinal materials are screened, and data including varieties of Chinese medicinal materials, their dosages, processing procedures, process names, treatment methods, process indicators, process parameters and experimental data are collected. 2. Data Processing: (1) Validate through pharmacodynamic experiments such as anti-inflammatory and analgesic tests. After data cleaning (e.g., eliminating erroneous data) and data analysis (e.g., trend analysis), a preparation process dataset is developed, and information including names of medicinal materials, processing procedures, process names, treatment methods, process indicators and process parameters are obtained. (2) Conduct experiments including UPLC-Q-TOF-MS analysis, network pharmacology analysis, molecular docking and in vitro cell experiments. After data cleaning, statistical analysis and other processing steps, key datasets for chemical composition analysis methods and mechanism of action research datasets are established, with chromatographic conditions, mass spectrometry conditions, test sample preparation methods and other relevant data are obtained. Meanwhile, by constructing the "medicinal materials - active ingredients - overlapping targets" network, the action targets and their influencing regularities are obtained. 3. Data Application: This dataset is applicable to scenarios such as production of drugs for treating rheumatic diseases, process improvement and new drug development. It can provide data support for process control during pharmaceutical preparation production, helping improve industrialization efficiency, promote large-scale production and strengthen quality control. It also provides data support for elucidating the material basis and therapeutic mechanism of the drug, which facilitates the popularization and application of the drug.
