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化学计量学方法在制剂提取工艺与处方优化中的应用

王丽丽 石森林

王丽丽, 石森林. 化学计量学方法在制剂提取工艺与处方优化中的应用[J]. 药学实践与服务, 2011, 29(4): 241-246,255.
引用本文: 王丽丽, 石森林. 化学计量学方法在制剂提取工艺与处方优化中的应用[J]. 药学实践与服务, 2011, 29(4): 241-246,255.
WANG Li-li, SHI Sen-lin. Application of chemometrics in the optimization of extraction conditions and prescription formulations in pharmaceutical preparations[J]. Journal of Pharmaceutical Practice and Service, 2011, 29(4): 241-246,255.
Citation: WANG Li-li, SHI Sen-lin. Application of chemometrics in the optimization of extraction conditions and prescription formulations in pharmaceutical preparations[J]. Journal of Pharmaceutical Practice and Service, 2011, 29(4): 241-246,255.

化学计量学方法在制剂提取工艺与处方优化中的应用

Application of chemometrics in the optimization of extraction conditions and prescription formulations in pharmaceutical preparations

  • 摘要: 目的 介绍试验设计-建模与优化方法在制剂研究中的重要作用。 方法 通过对国内外发表的关于制剂提取工艺及处方优化方面的诸多文献进行归纳、总结,明确试验设计-建模与优化方法在制剂研究中的重要作用,并简评其最新应用进展。 结果 对制剂研究中面临的一些复杂优化问题,试验设计-建模与优化方法能够依据试验设计方法,科学合理地安排试验点,并通过建模,将试验结果与影响因素之间隐藏的内在规律用数学模型抽象化地表达出来,进而通过对数学模型的优化研究,找到最优的结果及条件以解决这些复杂优化问题。 结论 随着研究水平的不断提高以及多学科交叉的日益深入,制剂研究中将面临着更多的多因素、多水平的复杂的优化问题,而试验设计-建模与优化方法也必将在制剂研究中得到更为广泛的应用。
  • [1] Montgomery DC. Design and analysis of experiments [M]. 7th edition. New York: John Wiley & Sons. 2008: 1.
    [2] William RM.Response Surface Methodology [M]. 2nd edition. London: Informa Healthcare. 2007: 858.
    [3] Stephen G. Nonlinear neural networks: Principles, mechanisms, and architectures[J]. Neural Networks, 1988, 1 (1): 17.
    [4] Vapnik VN.Statistical learning theory [M]. 1st edition. New York: John Wiley and Johns. 1998: 1.
    [5] 邢文训, 谢金星. 现代优化计算方法[M]. 第2版. 北京: 清华大学出版社. 2005: 1.
    [6] Jalali-Heravi M, Parastar H, Ebrahimi-Najafabadi H. Characterization of volatile components of Iranian saffron using factorial-based response surface modeling of ultrasonic extraction combined with gas chromatography-mass spectrometry analysis[J]. J Chromatogr A, 2009, 1216 (33): 6088.
    [7] Chang Y, Liu B, Shen B. Orthogonal array design for the optimization of supercritical fluid extraction of baicalin from roots of Scutellaria baicalensis Georgi[J]. J Sep Sci, 2007, 30 (10): 1568.
    [8] Fang Q, Yeung HW, Leung HW, et al. Micelle-mediated extraction and preconcentration of ginsenosides from Chinese herbal medicine[J]. J Chromatogr A, 2000, 904 (1): 47.
    [9] Cha K H, Lee HJ, Koo SY, et al. Optimization of pressurized liquid extraction of carotenoids and chlorophylls from Chlorella vulgaris[J]. J Agric Food Chem, 2010, 58 (2): 793.
    [10] 杨 铭, 余敏英, 史秀峰, 等. BP神经网络结合遗传算法多目标优化秦皮提取工艺的研究[J]. 中国中药杂志, 2008, 33 (22): 2622.
    [11] 陈 雯, 杜守颖, 陆 洋. 多指标正交试验优选仙灵骨葆胶囊中丹参、补骨脂提取工艺[J]. 中国中药杂志, 2009, 34 (14): 1792.
    [12] 黄春青, 林亚平, 靳凤云, 等. 均匀设计法结合药效学指标优选金铁锁提取工艺[J]. 中国中药杂志, 2008, 33 (15): 1817.
    [13] Pasqualoto K F, Teofilo R F, Guterres M, et al. A study of physicochemical and biopharmaceutical properties of amoxicillin tablets using full factorial design and PCA biplot[J]. Anal Chim Acta, 2007, 595 (1-2): 216.
    [14] Khanvilkar K H, Huang Y, Moore A D. Influence of hydroxypropyl methylcellulose mixture, apparent viscosity, and tablet hardness on drug release using a 2(3) full factorial design[J]. Drug Dev Ind Pharm, 2002, 28 (5): 601.
    [15] Weon KY, Lee KT, Seo SH. Optimization study on the formulation of roxithromycin dispersible tablet using experimental design[J]. Arch Pharm Res, 2000, 23 (5): 507.
    [16] Huang YB, Tsai YH, Yang WC, et al. Once-daily propranolol extended-release tablet dosage form: formulation design and in vitro/in vivo investigation[J]. Eur J Pharm Biopharm, 2004, 58 (3): 607.
    [17] Ibric S, Jovanovic M, Djuric Z, et al. The application of generalized regression neural network in the modeling and optimization of aspirin extended release tablets with Eudragit RS PO as matrix substance[J]. J Control Release, 2002, 82 (2-3): 213.
    [18] Mandal U, Gowda V, Ghosh A, et al. Optimization of metformin HCl 500 mg sustained release matrix tablets using Artificial Neural Network (ANN) based on Multilayer Perceptrons (MLP) model[J]. Chem Pharm Bull (Tokyo), 2008, 56 (2): 150.
    [19] Tiwari S, Singh S, Rawat M, et al. L(9) orthogonal design assisted formulation and evaluation of chitosan-based buccoadhesive films of miconazole nitrate[J]. Curr Drug Deliv, 2009, 6 (3): 305.
    [20] Gohel MC, Parikh RK, Aghara PY, et al. Application of simplex lattice design and desirability function for the formulation development of mouth dissolving film of salbutamol sulphate[J]. Curr Drug Deliv, 2009, 6 (5): 486.
    [21] Subramanian N, Yajnik A, Murthy RS. Artificial neural network as an alternative to multiple regression analysis in optimizing formulation parameters of cytarabine liposomes[J]. AAPS PharmSciTech, 2004, 5 (1): E4.
    [22] Xiong Y, Guo D, Wang L, et al. Development of nobiliside A loaded liposomal formulation using response surface methodology[J]. Int J Pharm, 2009, 371 (1-2): 197.
    [23] Arulsudar N, Subramanian N, Muthy RS. Comparison of artificial neural network and multiple linear regression in the optimization of formulation parameters of leuprolide acetate loaded liposomes[J]. J Pharm Sci, 2005, 8 (2): 243.
    [24] Varshosaz J, GhaffariS, Khoshayand MR, et al. Development and optimization of solid lipid nanoparticles of amikacin by central composite design[J]. J Liposome Res, 2010, 20 (2): 97.
    [25] Shah M, Pathak K. Development and Statistical Optimization of Solid Lipid Nanoparticles of Simvastatin by Using 2(3) Full-Factorial Design[J]. AAPS Pharm Sci Tech, 2010, 11(2): 489.
    [26] Boldhane SP, Kuchekar BS. Gastroretentive drug delivery of metformin hydrochloride: formulation and in vitro evaluation using 3(2) full factorial design[J]. Curr Drug Deliv, 2009, 6 (5): 477.
    [27] Swain K, Pattnaik S, Mallick S, et al. Influence of hydroxypropyl methylcellulose on drug release pattern of a gastroretentive floating drug delivery system using a 3(2) full factorial design [J]. Pharm Dev Technol, 2009, 14 (2): 193.
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  • 收稿日期:  2010-12-27
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化学计量学方法在制剂提取工艺与处方优化中的应用

摘要: 目的 介绍试验设计-建模与优化方法在制剂研究中的重要作用。 方法 通过对国内外发表的关于制剂提取工艺及处方优化方面的诸多文献进行归纳、总结,明确试验设计-建模与优化方法在制剂研究中的重要作用,并简评其最新应用进展。 结果 对制剂研究中面临的一些复杂优化问题,试验设计-建模与优化方法能够依据试验设计方法,科学合理地安排试验点,并通过建模,将试验结果与影响因素之间隐藏的内在规律用数学模型抽象化地表达出来,进而通过对数学模型的优化研究,找到最优的结果及条件以解决这些复杂优化问题。 结论 随着研究水平的不断提高以及多学科交叉的日益深入,制剂研究中将面临着更多的多因素、多水平的复杂的优化问题,而试验设计-建模与优化方法也必将在制剂研究中得到更为广泛的应用。

English Abstract

王丽丽, 石森林. 化学计量学方法在制剂提取工艺与处方优化中的应用[J]. 药学实践与服务, 2011, 29(4): 241-246,255.
引用本文: 王丽丽, 石森林. 化学计量学方法在制剂提取工艺与处方优化中的应用[J]. 药学实践与服务, 2011, 29(4): 241-246,255.
WANG Li-li, SHI Sen-lin. Application of chemometrics in the optimization of extraction conditions and prescription formulations in pharmaceutical preparations[J]. Journal of Pharmaceutical Practice and Service, 2011, 29(4): 241-246,255.
Citation: WANG Li-li, SHI Sen-lin. Application of chemometrics in the optimization of extraction conditions and prescription formulations in pharmaceutical preparations[J]. Journal of Pharmaceutical Practice and Service, 2011, 29(4): 241-246,255.
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