本文選題：黨參 + 黃芪　； 參考：《浙江大學(xué)》2017年碩士論文

【摘要】：隨著"質(zhì)量源于設(shè)計(jì)"等先進(jìn)藥品質(zhì)控理念逐漸應(yīng)用于生產(chǎn)實(shí)踐,中藥質(zhì)量控制的重心也由成品檢驗(yàn)往原料品質(zhì)控制和制藥過(guò)程質(zhì)量控制轉(zhuǎn)移。針對(duì)重要操作單元,采用過(guò)程分析技術(shù)建立有效過(guò)程監(jiān)控方法,能顯著提升制藥過(guò)程質(zhì)控水平,進(jìn)而提升中藥質(zhì)量一致性。本文以參芪扶正注射液醇沉工藝為研究對(duì)象,開(kāi)展近紅外光譜與多變量數(shù)據(jù)分析技術(shù)相結(jié)合的應(yīng)用研究,主要包括以下內(nèi)容:1.建立黃芪一次醇沉過(guò)程在線(xiàn)監(jiān)控模型。采用近紅外光譜與多變量統(tǒng)計(jì)過(guò)程控制相結(jié)合的方法,建立了黃芪一次醇沉過(guò)程監(jiān)控模型。通過(guò)計(jì)算各時(shí)間點(diǎn)處的主成分得分、HotellingT2和DModX統(tǒng)計(jì)量,觀察過(guò)程是否處在受控范圍內(nèi),據(jù)此判斷過(guò)程運(yùn)行是否正常。結(jié)果表明所建模型具有較好的監(jiān)控能力,能及時(shí)識(shí)別過(guò)程異常。2.建立黨參一次醇沉上清液多指標(biāo)近紅外光譜快速分析法。通過(guò)實(shí)驗(yàn)設(shè)計(jì)和濃縮-稀釋的方法獲得具有代表性的樣本集。逐一優(yōu)化各建模步驟,最終所得模型預(yù)測(cè)性能良好,實(shí)現(xiàn)了黨參一次醇沉上清液中黨參炔苷、總黃酮、色素、總固體等多指標(biāo)快速定量。3.建立黃芪二次醇沉的在線(xiàn)近紅外光譜分析法。建立黃芪醇沉液中毛蕊異黃酮苷、芒柄花苷、紫檀烷葡萄糖苷、異黃烷葡萄糖苷、黃芪甲苷、黃芪皂苷Ⅱ等6個(gè)化學(xué)指標(biāo)的HPLC-UV-ELSD測(cè)定法。在建立近紅外光譜校正模型時(shí),通過(guò)實(shí)驗(yàn)設(shè)計(jì)構(gòu)建了包含原料、關(guān)鍵工藝參數(shù)、環(huán)境溫度、光譜采集方式等變異的校正集樣本,采用獨(dú)立外部驗(yàn)證樣本用于模型評(píng)價(jià),用實(shí)驗(yàn)設(shè)計(jì)法找出預(yù)處理策略的優(yōu)化方向,調(diào)整算法參數(shù),減少了試錯(cuò)法的計(jì)算次數(shù),提高了模型對(duì)目標(biāo)工藝過(guò)程的預(yù)測(cè)性能,模型復(fù)雜程度低,穩(wěn)健性較好,實(shí)現(xiàn)了黃芪二次醇沉中總固體和6種化學(xué)成分的同時(shí)測(cè)定。4.基于準(zhǔn)確度輪廓的黃芪二次醇沉過(guò)程多指標(biāo)在線(xiàn)近紅外光譜分析方法的驗(yàn)證。首先設(shè)立獨(dú)立驗(yàn)證批次,計(jì)算模型性能指標(biāo),從總體上評(píng)價(jià)模型預(yù)測(cè)能力;然后分別從真實(shí)性、精密度、準(zhǔn)確度、線(xiàn)性與范圍、專(zhuān)屬性、穩(wěn)健性和不確定度幾個(gè)方面考察方法性能;再以準(zhǔn)確度輪廓作為方法有效性的決策工具,計(jì)算各模型在不同含量水平下預(yù)測(cè)誤差的β-期望容許區(qū)間,選擇落在誤差接受限±15%以?xún)?nèi)的有效含量范圍;最終獲得總固體、毛蕊異黃酮苷、芒柄花苷、紫檀烷葡萄糖苷、異黃烷葡萄糖苷、黃芪甲苷和黃芪皂苷Ⅱ等指標(biāo)的有效含量范圍分別為:8.44-39.8%、0.541-2.26 mg/mL、0.118-0.502 mg/mL、0.220-0.940 mg/mL、0.106-0.167 mg/mL、0.137-0.320 mg/mL 和 0.484-0.879 mg/mL。在以上濃度范圍內(nèi),近紅外光譜在線(xiàn)分析方法能夠?qū)崿F(xiàn)黃芪二次醇沉過(guò)程中7個(gè)指標(biāo)的準(zhǔn)確定量,且方法穩(wěn)健性良好。
[Abstract]:With the application of "quality from Design" and other advanced drug quality control concepts in production practice, the focus of quality control of traditional Chinese medicine is also transferred from finished product inspection to raw material quality control and pharmaceutical process quality control. According to the important operation unit, using process analysis technology to establish an effective process monitoring method can significantly improve the quality control level of pharmaceutical process, and then improve the consistency of quality of traditional Chinese medicine. In this paper, the alcohol precipitation technology of Shenqi Fuzheng injection was taken as the research object, and the application of near infrared spectroscopy combined with multivariate data analysis technology was carried out, mainly including the following contents: 1: 1. An online monitoring model for primary alcohol precipitation process of Astragalus membranaceus was established. The monitoring model of primary alcohol precipitation process of Astragalus membranaceus was established by combining near infrared spectroscopy with multivariable statistical process control. By calculating the statistics of Hotelling T2 and DModX at each time point, we observed whether the process was in a controlled range and judged whether the process was running normally. The results show that the model has better monitoring ability and can identify process anomalies in time. A fast near-infrared spectrum analysis method for the supernatant of primary alcohol precipitation of Codonopsis pilosula was established. The representative sample set was obtained by experimental design and concentration-dilution method. Each modeling step was optimized one by one, and the prediction performance of the model was good, and the rapid quantification of Codonosine, total flavonoids, pigment and total solids in the supernatant of primary alcohol precipitation of Codonopsis pilosula was achieved. An on-line near-infrared spectrometric analysis of secondary alcohol precipitation of Astragalus membranaceus was established. A HPLC-UV-ELSD method was established for the determination of isoflavone glycosides in Astragalus membranaceus alcohol precipitate, Astragalus saponin 鈪，

本文編號(hào)：1939237