本文選題：近紅外光譜 + 藥用輔料��； 參考：《佳木斯大學(xué)》2017年碩士論文

【摘要】：目的探索固體藥物制劑復(fù)雜分析系統(tǒng)中輔料的近紅外光譜同時(shí)定量,嘗試打破由于國內(nèi)輔料現(xiàn)有檢測標(biāo)準(zhǔn)缺少及固體制劑輔料多難以制成供分析檢測的合適溶液而形成的仿制藥一致性評(píng)價(jià)實(shí)施中多種輔料難以同時(shí)定量、無恰當(dāng)?shù)姆治龇椒ǖ某跏计款i,探討仿制藥一致性評(píng)價(jià)中幾種藥品的近紅外定量分析的光譜預(yù)處理、波長選擇、模型優(yōu)化與確定。為固體制劑仿制藥一致性評(píng)價(jià)提供藥用輔料的快速檢測提供實(shí)用可行的分析方法。方法(1)將近紅外光譜和化學(xué)計(jì)量學(xué)相結(jié)合快速檢測苯磺酸氨氯地平片輔料含量。通過隨機(jī)青蛙法、變量投影重要性和競爭自適應(yīng)重加權(quán)采樣篩選特征波長變量點(diǎn),采用9種光譜預(yù)處理方法對(duì)原始光譜進(jìn)行處理后,分別建立偏最小二乘法模型和支持向量回歸分析模型,并進(jìn)行兩種模型的比較及應(yīng)用優(yōu)選模型測試樣品。(2)將蒙特卡洛無信息變量消除結(jié)合遺傳算法(MCUVE-GA)用于優(yōu)選格列吡嗪藥用輔料特征光譜變量,建立主成分分析(PCA)與人工神經(jīng)網(wǎng)絡(luò)算法(ANN)模型,比較分析所建立模型與偏最小二乘(PLS)模型的性能,優(yōu)選模型建立方法。(3)利用近紅外光譜法分別結(jié)合間隔偏最小二乘(iPLS)、反向區(qū)間偏最小二乘(BiPLS)、聯(lián)合區(qū)間偏最小二乘算法(SiPLS)進(jìn)行纈沙坦膠囊中藥用輔料含量建模,比較分析各算法在不同劃分區(qū)間數(shù)及區(qū)間選擇時(shí)對(duì)建立模型的影響。(4)利用近紅外漫反射技術(shù)結(jié)合偏最小二乘法建立多潘立酮藥用輔料定量分析模型。通過考察光譜區(qū)域選擇、光譜預(yù)處理及最佳主因子數(shù)選擇等方面對(duì)模型進(jìn)行不斷優(yōu)化,最終確定了最佳建模參數(shù)。結(jié)果(1)近紅外漫反射光譜法快速檢測苯磺酸氨氯地平片輔料結(jié)果表明:對(duì)于所涉及的樣本,在最優(yōu)特征波長變量選擇上,隨機(jī)青蛙法效果較好;在模型預(yù)測結(jié)果上,與支持向量回歸分析模型相比,5個(gè)指標(biāo)的偏最小二乘定量模型的決定系數(shù),預(yù)測均方根誤差評(píng)價(jià)參數(shù)效果較好,相對(duì)分析誤差值均大于3.0。樣品測試值與實(shí)測值標(biāo)準(zhǔn)誤差均小于1.30,配對(duì)t檢驗(yàn)表明,在α=0.05顯著性水平上,兩者無顯著性差異。(2)近紅外光譜法測定格列吡嗪片輔料結(jié)果表明:輔料淀粉、糊精、硬脂酸鎂的偏最小二乘(PLS)模型的評(píng)價(jià)性能參數(shù)優(yōu)于主成分分析(PCA)與人工神經(jīng)網(wǎng)絡(luò)算法(ANN)模型。而蔗糖經(jīng)過共軛梯度學(xué)習(xí)算法訓(xùn)練得到性能參數(shù)優(yōu)于PLS模型。配對(duì)t檢驗(yàn)表明,在α=0.05顯著性水平上,兩者無顯著性差異。(3)近紅外光譜法測定纈沙坦膠囊輔料結(jié)果表明:輔料微晶纖維素和羧甲基淀粉鈉BiPLS模型預(yù)測精度較好于iPLS和SiPLS模型精度,輔料聚維酮和十二烷基硫酸鈉iPLS模型預(yù)測精度較好于BPLS和SiPLS模型精度。配對(duì)t檢驗(yàn)表明,在α=0.05顯著性水平上,兩者無顯著性差異。(4)所建多潘立酮片輔料PLS定量分析模型性能良好,驗(yàn)證集相關(guān)系數(shù)和預(yù)測均方根誤差分別為0.9657,1.29;0.9870,0.877;0.9734,0.688;0.9474,0.734;0.9303,0.880;0.9777,0.0495。結(jié)論近紅外漫反射光譜法結(jié)合化學(xué)計(jì)量學(xué)可快速檢測苯磺酸氨氯地平片、格列吡嗪片、纈沙坦膠囊和多潘立酮片輔料含量,通過選取未參與建模的6組樣品對(duì)模型有效性進(jìn)行確認(rèn)并通過配對(duì)t檢驗(yàn)分析得出近紅外測定的結(jié)果與實(shí)測值之間無顯著性差異。分析方法操作簡便快速、綠色環(huán)保、結(jié)果準(zhǔn)確可靠,重復(fù)性、中間精密性、線性、精確性良好可為其他藥用輔料含量快速檢測提供了借鑒。在實(shí)際應(yīng)用中,通過校正集和預(yù)測集樣品容量增加,對(duì)模型進(jìn)一步再優(yōu)化和驗(yàn)證完善,可以不斷提高模型的適用性和可靠性,更好的滿足實(shí)際生產(chǎn)需求,對(duì)在線檢測有重要的指導(dǎo)意義,同時(shí),也進(jìn)一步擴(kuò)大近紅外光譜分析的應(yīng)用、有望助力于仿制藥一致性評(píng)價(jià)。
[Abstract]:Objective to explore the near infrared spectroscopy of the auxiliary materials in the complex analysis system of solid drug preparation, and to try to break through the lack of the existing inspection standards for the domestic excipients and the difficulty in making the suitable solution of the solid preparation to make the suitable solution for analysis and testing. The initial bottleneck of the method is analyzed. The spectral preprocessing, wavelength selection, model optimization and determination of near infrared quantitative analysis of several drugs in generic drug consistency evaluation provide a practical and feasible analysis method for the rapid detection of pharmaceutical excipients for the consistency evaluation of solid preparations. Method (1) near infrared spectroscopy and chemometrics To detect the content of Amlodipine Besylate Tablets excipient quickly, the feature wavelength variable points are selected by random frog method, variable projection importance and competitive adaptive heavy weight sampling. 9 spectral preprocessing methods are used to process the original spectrum, and the partial least two multiplication model and support vector regression analysis model are set up respectively. Two models were compared and applied to optimize the model test samples. (2) Monte Carlo non information elimination combined with genetic algorithm (MCUVE-GA) was used to optimize the characteristic spectral variables of glipizide medicinal excipients, and the principal component analysis (PCA) and artificial neural network algorithm (ANN) model was established, and the model established and partial least squares (PLS) were compared and analyzed. The performance of the model and the optimal model establishment method. (3) using the near infrared spectroscopy (NIR) combined with spaced partial least squares (iPLS), reverse interval partial least squares (BiPLS) and joint interval partial least squares (SiPLS) to model the content of the auxiliary materials used in Valsartan Capsules. The influence of the model was established. (4) the quantitative analysis model of domperidone medicinal excipients was established by using near infrared diffuse reflectance technique combined with partial least square method. The model was optimized through the selection of spectral region, spectral preprocessing and the selection of the best main factor number. Finally, the optimal modeling parameters were determined. Results (1) near infrared diffuse reflectance The results of rapid detection of Amlodipine Besylate Tablets excipients by spectral method show that the random frog method has better effect on the selection of the optimal characteristic wavelength variables for the selected samples. Compared with the support vector regression analysis model, the decision coefficient of the minimum two multiplying model of the 5 indexes is compared with the model prediction results, and the root mean square error is predicted. The effect of the price parameter is better, the relative error value is greater than the 3.0. sample test value and the measured value standard error is less than 1.30. The paired t test shows that there is no significant difference at the level of the alpha =0.05 significance. (2) the result of the determination of Glipizide Tablets adjunct by near infrared spectroscopy shows that the partial least squares (PLS) of the auxiliary starches, dextrin and magnesium stearate. The evaluation performance parameters of the model are superior to the principal component analysis (PCA) and the artificial neural network algorithm (ANN). While the sucrose is trained by the conjugate gradient learning algorithm, the performance parameters are better than the PLS model. The paired t test shows that there is no significant difference in the significant level of the alpha =0.05. (3) the results of the near infrared spectroscopy for the determination of the Valsartan Capsules excipient result The results showed that the prediction accuracy of the BiPLS model was better than that of iPLS and SiPLS model. The prediction accuracy of the iPLS model was better than that of BPLS and SiPLS. The paired t test showed that there was no significant difference in the significant level of alpha =0.05. (4) the Domperidone Tablets was built. The auxiliary material PLS quantitative analysis model has good performance, the correlation coefficient and the mean square root error of the validation set are 0.9657,1.29, 0.9870,0.877; 0.9734,0.688; 0.9474,0.734; 0.9303,0.880; 0.9777,0.0495. conclusion the near infrared diffuse reflectance spectroscopy combined with chemometrics can quickly detect Amlodipine Besylate Tablets, Glipizide Tablets, and Valsartan Capsules. And the content of Domperidone Tablets auxiliary materials, by selecting 6 groups of samples not participating in modeling, confirming the validity of the model and analyzing the results of near infrared by paired t test, there is no significant difference between the results and the measured values. The analysis method is simple, fast, green, reliable, repeatable, intermediate precision, linear and accurate. Good sex can be used for reference for the rapid detection of other medicinal excipients. In practical applications, the application and reliability of the model can be improved continuously through the increase of the sample volume of the correction set and the prediction set, and the model is further optimized and verified. It is of great guiding significance for on-line detection. At the same time, it will further expand the application of near infrared spectroscopy analysis, which is expected to contribute to the consistency evaluation of generic drugs.

【學(xué)位授予單位】：佳木斯大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R927;O657.33

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