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Study On Quality Consistency Evaluation Method Of Salvia Miltiorrhiza And Ligustrazine Hydrochloride Injection And Its Intermediates

Posted on:2021-01-02Degree:MasterType:Thesis
Country:ChinaCandidate:L B ChenFull Text:PDF
GTID:2404330629982382Subject:Pharmacy
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To improve the quality consistency and complete the quality evaluation methods of traditional Chinese medicine intermediates and preparations,Salvia miltiorrhiza and Ligustrazine Hydrochloride injection and its intermediates were taken as research object in this thesis.Quality consistency evaluation methods were developed by using traditional quality analysis techniques,near-infrared?NIR?spectroscopy and multivariate statistical tools.This work raised the existing quality evaluation requirements of Salvia miltiorrhiza and Ligustrazine Hydrochloride injection,laying the foundation for quality control in the production process.The main contents and achievements are summarized as follows:1.Methods of high performance liquid chromatography-ultraviolet?HPLC-UV?fingerprints analysis of the salvia miltiorrhiza extract and quantitative analysis for 5-hydroxymethylfurfural?5-HMF?,danshensu?DSS?,protocatechualdehyde?PA?,rosmarinic acid?RA?,lithospermic acid?LA?,salvianolic acid B?SAB?,and salvianolic acid A?SAA?were developed.Methodological verification of fingerprint analysis and quantitative analysis was completed with good performance.Fingerprints of 30 batches of Salvia miltiorrhiza extracts were established and seven indicators were quantified.And the quality consistency of Salvia miltiorrhiza extract was evaluated from the perspective of fingerprint similarity and indicator content.2.Principal component analysis?PCA?was used to evaluate the quality consistency of Shiliu supernatant.A PCA model was established by using the contents data of seven indicators of factory samples.The factory diluted samples,laboratory prepared samples and abnormal samples were taken as monitoring objects to investigate the quality consistency evaluation ability of model by Hotelling's T2 and DModX.The results showed that this model could monitor the sample anomalies accurately and evaluate the quality of the Shiliu supernatant effectively.Different from the traditional control charts,Hotelling's T2 and DModX statistics were co-charted in one graph,which can describe the abnormal monitoring information intuitively at the same time,setting an example for the quality consistency evaluation of the Shiliu supernatant.3.NIR spectroscopy quantitative models were established for seven indicators in Shiliu supernatant.Combining with four band selection algorithms of successive projections algorithm?SPA?,competitive adaptive reweighted sampling?CARS?,interval PLS?iPLS?and synergy interval PLS?siPLS?,the model performance of the solution and lyophilized powder were respectively studied.The quantitative model established by the lyophilized powder spectrum combining with the CARS band selection algorithm had good performance with low root mean square error of prediction?RMSEP?as well as R2cal and R2pre reaching above 0.950,showing high prediction accuracy.The establishment of NIR quantitative models laid the foundation for rapid evaluation of quality consistency for Shiliu supernatants.4.A quality consistency assessment method based on multiple global analysis indicators was established.And key quality control indicators were identified.The quality consistency of preparation was evaluated based on 18 indicators including carbohydrate,active substances phenolic acids and inorganic salts.Compared with the evaluation results of traditional HPLC-UV fingerprint,the consistency evaluation method based on multiple global analysis indicators was more comprehensive and effective.And the key quality control indicators including Na+,fructose?Fru?,glucose?Glc?,manninotriose?Man?,DSS and SAB were identified with the loading plot.The identification of key quality control indicators can set a good example for the quality control of injections.
Keywords/Search Tags:Salvia miltiorrhiza and Ligustrazine Hydrochloride injection, Quality consistency, Fingerprint, Near-infrared, Principal component analysis, Multiple global analysis indicators
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