基于神经网络理论的难溶性药物渗透泵处方设计专家系统的研究
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摘要
本文以提高新药研发效率、缩短新药开发周期为主体思路,以计算机模拟药物释放为切入点,建立了以神经网络理论和产生式规则为核心技术的难溶性药物推拉式渗透泵处方设计专家系统。目的在于推广普及渗透泵控释技术,加快国内渗透泵制剂产业化进程;也希望起到抛砖引玉的作用,促进学科融合,有更多高、精、尖的科技融入药剂学科;以期为我国药剂学乃至药学科学和技术向更快、更好、更强的发展贡献一份力量。
本文选择了剂量相差悬殊的难溶性药物吲达帕胺、格列齐特和双嘧达莫为前期模型药物,根据已有经验进行了全方位、大跨度的因素考察。在1.5～200mg药物剂量范围内,在六千多个原始数据、八百多条溶出曲线和二百五十多组处方的基础上,总结了包括高分子、促渗剂、粘合剂、致孔剂、包衣膜厚度及释药孔径大小处方工艺因素对释放行为影响的规律。以此为基础并总结前人经验建立了专家系统的规则库,同时也根据上述原始数据建立了数据库。
专家系统是人工智能应用研究中最活跃,研究得最广泛的课题之一。目前已见报道的专家系统未见适用于缓控释制剂,而国内外关于渗透泵控释制剂的研究已逐渐成熟,现在开展有关渗透泵控释制剂专家系统的研究,具有非常重要的意义。专家系统主要包括人-机界面、知识库和推理机。本文使用SQL Server管理数据库和知识库。BP神经网络具有学习功能和高度非线性映射功能,基于这一特点,本文利用BP神经网络建立了处方释药行为预测模型,进行目标处方搜索,并将其作为推理机的核心。通过人-机友好界面的设计,最终用VB.NET完成了一个可以充当专家或部分代替人类专家的难溶性药物推拉式渗透泵处方设计计算机系统。
本文另选取了法莫替丁等难溶性药物,利用所建立的专家系统设计处方,通过实验验证对系统进行了评价,结果证明所建立的系统具有良好的实用性。
The purpose of this thesis was to build an expert system(ES)that was mainly based on network control and production rule.The system was for the formulation design of push-pull osmotic pump tablets(PPOP)so that the efficiency of push-pull osmotic pump tablets development could be improved,the development cycle could be shorten,and the industrialization situation of osmotic pump dosage forms in China could be improved.This study was also expected to throw out a minnow to catch a whale,promote the anastomosis of disciplines,inhalans more high technology into pharmaceutics,and dedicate our strength to a faster,better and greater development of pharmaceutics and pharmacy.
Water insoluble drug with extremly different dosage(1.5mg～200mg),indapamide, gliclazide and dipyridamole was employed as models.Single factor study was carried out in every dose of each drug in a large range.Over six thousand original data,eight hundred dissolution profiles and two hundred and fifty formulations were obtained through the study.The regularity of polymer,osmotic agent,binder,pore former,coat weight gain,orifice and manufacture procedure was summarized based on the data and then the database was built.Rule base of the system was built mainly based on the original data and the experiences obtained by other people before.
ES is one of the most popular and active subject in artificial intelligence.No expert system available could be used for extended release dosage form design.It is gradually consummate of osmotic pump technology(OPT)no matter at home or abord. It is meaningfull to combine OPT and ES at this time.ES mainly includs man-machine interface,knowledge base(database)and inference engine.SQL Server was employed as database manage system(DBMS).Release behavior prediction model was built based on BP neural network which is good at high nonlinear mapping with learning function.Formulation design model was built based on release behavior prediction model,which was the nucleus of the inference engine.Man-machine interface was designed using VB.NET,and a computer program that could design PPOP formulation totally or partly as a professional person was come out.
Finally,water insoluble drug famotidine was chosed and ES built in the study was used to design the PPOP formulations.It was considered that the ES was practicable.
本文选择了剂量相差悬殊的难溶性药物吲达帕胺、格列齐特和双嘧达莫为前期模型药物,根据已有经验进行了全方位、大跨度的因素考察。在1.5～200mg药物剂量范围内,在六千多个原始数据、八百多条溶出曲线和二百五十多组处方的基础上,总结了包括高分子、促渗剂、粘合剂、致孔剂、包衣膜厚度及释药孔径大小处方工艺因素对释放行为影响的规律。以此为基础并总结前人经验建立了专家系统的规则库,同时也根据上述原始数据建立了数据库。
专家系统是人工智能应用研究中最活跃,研究得最广泛的课题之一。目前已见报道的专家系统未见适用于缓控释制剂,而国内外关于渗透泵控释制剂的研究已逐渐成熟,现在开展有关渗透泵控释制剂专家系统的研究,具有非常重要的意义。专家系统主要包括人-机界面、知识库和推理机。本文使用SQL Server管理数据库和知识库。BP神经网络具有学习功能和高度非线性映射功能,基于这一特点,本文利用BP神经网络建立了处方释药行为预测模型,进行目标处方搜索,并将其作为推理机的核心。通过人-机友好界面的设计,最终用VB.NET完成了一个可以充当专家或部分代替人类专家的难溶性药物推拉式渗透泵处方设计计算机系统。
本文另选取了法莫替丁等难溶性药物,利用所建立的专家系统设计处方,通过实验验证对系统进行了评价,结果证明所建立的系统具有良好的实用性。
The purpose of this thesis was to build an expert system(ES)that was mainly based on network control and production rule.The system was for the formulation design of push-pull osmotic pump tablets(PPOP)so that the efficiency of push-pull osmotic pump tablets development could be improved,the development cycle could be shorten,and the industrialization situation of osmotic pump dosage forms in China could be improved.This study was also expected to throw out a minnow to catch a whale,promote the anastomosis of disciplines,inhalans more high technology into pharmaceutics,and dedicate our strength to a faster,better and greater development of pharmaceutics and pharmacy.
Water insoluble drug with extremly different dosage(1.5mg～200mg),indapamide, gliclazide and dipyridamole was employed as models.Single factor study was carried out in every dose of each drug in a large range.Over six thousand original data,eight hundred dissolution profiles and two hundred and fifty formulations were obtained through the study.The regularity of polymer,osmotic agent,binder,pore former,coat weight gain,orifice and manufacture procedure was summarized based on the data and then the database was built.Rule base of the system was built mainly based on the original data and the experiences obtained by other people before.
ES is one of the most popular and active subject in artificial intelligence.No expert system available could be used for extended release dosage form design.It is gradually consummate of osmotic pump technology(OPT)no matter at home or abord. It is meaningfull to combine OPT and ES at this time.ES mainly includs man-machine interface,knowledge base(database)and inference engine.SQL Server was employed as database manage system(DBMS).Release behavior prediction model was built based on BP neural network which is good at high nonlinear mapping with learning function.Formulation design model was built based on release behavior prediction model,which was the nucleus of the inference engine.Man-machine interface was designed using VB.NET,and a computer program that could design PPOP formulation totally or partly as a professional person was come out.
Finally,water insoluble drug famotidine was chosed and ES built in the study was used to design the PPOP formulations.It was considered that the ES was practicable.
引文
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[4]刘有才,刘增良.模糊专家系统原理与设计.北京:北京航空航天大学出版社,1995.
[5]马少平,朱晓燕著.人工智能.北京:清华大学出版社,2004.
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