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Development and implementation of incident response near-infrared models for analyzing contaminated medicines containing diethylene glycol solvent

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Journal of Innovative Optical Health Sciences 2014年第6期7卷 97-104页

作者： lihui yin Xuebo Zhang Xiaodong Li Shaohong Jin National Institutes for Food and Drug Control No.2 Tiantan Xili BeijingP.R.China

Samples of preparations contaminated by diethylene glycol(DEG),diethylene glycol raw materials and laboratory prepared solutions were measured to get NIR *** the iden-tification models were developed using the collected spectra and the spectra of distilled water,propylene glyool and the preparations without diethylene ***,the quantification model was also established for determining the concentration of diethylene glyool in the pre-parations.V alidation results show the identification and quantification models have ideal pre-diction *** emergency NIR models are rapid,easy to use and accurate,and can be implemented for identifying diethylene glycol raw material,screening the preparations contam-inated by diethylene glycol in the markets and analyzing the concentrations of DEG.

关键词： Diethylene glycol near-infrared transmittance reflectance spectroscopy identification quantification

A strategy for population pharmaceutical quality assessment based on quality by design

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Journal of Pharmaceutical Analysis 2021年第5期11卷 588-595页

作者： Yu Zhao Changqin Hu Shangchen Yao lihui yin Xiaomei Ling NMPA Key Laboratory for Quality Research and Evaluation of Chemical Drugs National Institutes for Food and Drug ControlBeijing102629China Acedemy for Advanced Interdisciplinary Studies Peking UniversityBeijing100088China Peking University Health Science Center Peking UniversityBeijing100191China

From a regulatory perspective,drug quality consistency evaluation must concern different processes used for the same *** this study,an assessment strategy based on quality by design(QbD)was developed for population pharmaceutical quality evaluation.A descriptive analysis method based on QbD concept was first established to characterize the process by critical evaluation attributes(CEAs).Then quantitative analysis method based on an improved statistical process control(SPC)method was established to investigate the process indicators(PIs)in the process population,such as mean distribution,batch-to-batch difference and abnormal quality *** that rules for risk assessment were established based on the SPC limitations and *** the SPC parameters of the CEAs and the risk of PIs were visualized according to the interaction test results to obtain a better understanding of the population pharmaceutical ***,an assessment strategy was built and applied to generic drug consistency assessment,process risk assessment and quality trend *** strategy demonstrated in this study could help reveal quality consistency from the perspective of process control and process risk,and further show the recent development status of domestic pharmaceutical production *** addition,a process risk assessment and population quality trend tracking provide databased information for *** only can this information serve as a further basis for decisionmaking by the regulatory authority regarding early warnings,but it can also reduce some avoidable adverse *** continuous addition of data,dynamic population pharmaceutical quality is meaningful for emergencies and decision-making regarding drug regulation.

关键词： Population pharmaceutical quality Quality by design(QbD) Crucial evaluation attributes(CEAs) Process indicators(PIs) Improved statistical process control(SPC) Risk assessment

SpectraTr:A novel deep learning model for qualitative analysis of drug spectroscopy based on transformer structure

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Journal of Innovative Optical Health Sciences 2022年第3期15卷 107-117页

作者： Pengyou Fu Yue Wen Yuke Zhang Lingqiao Li Yanchun Feng lihui yin Huihua Yang School of Computer Science and Information Security Guilin University of Electronic Technology 1 Jinji Road Guilin 541004P.R.China School of Artīcial Intelligence Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing 100876P.R.China School of International Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing 100876P.R.China National Institutes for Food and Drug Control 10 Tiantanxili Road Beijing 100050P.R.China

The drug supervision methods based on near-infrared spectroscopy analysis are heavily dependent on the chemometrics model which characterizes the relationship between spectral data and drug *** preliminary application of convolution neural network in spectral analysis demonstrates excellent end-to-end prediction ability,but it is sensitive to the hyper-parameters of the *** transformer is a deep-learning model based on self-attention mechanism that compares convolutional neural networks(CNNs)in predictive performance and has an easy-todesign model ***,a novel calibration model named SpectraTr,based on the transformer structure,is proposed and used for the qualitative analysis of drug *** experimental results of seven classes of drug and 18 classes of drug show that the proposed SpectraTr model can automatically extract features from a huge number of spectra,is not dependent on pre-processing algorithms,and is insensitive to model *** the ratio of the training set to test set is 8:2,the prediction accuracy of the SpectraTr model reaches 100%and 99.52%,respectively,which outperforms PLS DA,SVM,SAE,and *** model is also tested on a public drug data set,and achieved classification accuracy of 96.97%without preprocessing algorithm,which is 34.85%,28.28%,5.05%,and 2.73%higher than PLS DA,SVM,SAE,and CNN,*** research shows that the SpectraTr model performs exceptionally well in spectral analysis and is expected to be a novel deep calibration model after Autoencoder networks(AEs)and CNN.

关键词： Near-infrared spectroscopy analysis drug supervision transformer structure deep learning chemometrics

Multi-manufacturer drug identification based on near infrared spectroscopy and deep transfer learning

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Journal of Innovative Optical Health Sciences 2020年第4期3卷 39-50页

作者： Lingqiao Li Xipeng Pan Wenli Chen Manman Wei Yanchun Feng lihui yin Changqin Hu Huihua Yang School of Automation Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing 100876P.R.China School of Computer Science and Information Security Guilin University of Electronic Technology 1 Jinji Road Guilin 541004P.R.China National Institutes for Food and Drug Control 10 Tiantanxili Road Beijing 100050 P.R.China

Near infrared(NIR)spectrum analysis technology has outstanding advantages such as rapid,nondestructive,pollution-free,and is widely used in food,pharmaceutical,petrochemical,agricultural products production and testing *** neural network(CNN)is one of the most successful methods in big data analysis because of its powerful feature ex-traction and abstraction ability,and it is especially suitable for solving multi-classification ***-based transfer learning is a machine learning technique,which migrates para-meters of trained model to the new one to improve the *** transfer learning strategy can speed up the learning efficiency of the model instead of learning from *** view of the difficulty in acquisition of drug NIR spectral data and high labeling cost,this paper proposes three simple but very effective transfer learning methods for multi-manufacturer identification of drugs based on one-dimensional *** with the original CNN,the transfer learning method can achieve better classification performance with fewer NIR spectral data,which greatly reduces the dependence on labeled NIR spectral *** the same time,this paper also compares and discusses three different transfer learning methods,and selects the most suitable transfer learning model for drug NIR spectral data *** with the current popular methods,such as SVM,BP,AE and ELM,the proposed method achieves higher classification accuracy and scalability in multi-variety and multi-manufacturer NIR spectrum classification experiments.

关键词： Near-infrared spectroscopy transfer learning drug identification multi-manufacturer

Deep belief network-based drug identification using near infrared spectroscopy

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Journal of Innovative Optical Health Sciences 2017年第2期10卷 1-10页

作者： Huihua Yang Baichao Hu Xipeng Pan Shengke Yan Yanchun Feng Xuebo Zhang lihui yin Changqin Hu College of Electronic Engineering and Automation Guilin University of Electronic Technology 1 Jinji Road Guilin 541004P.R.China A utomation School Beijing University of Posts 8 Telecommunications 10 Xitucheng Road Beijing 100876P.R.China National Institutes for Food and Drug Control 10 Tiantanxili Road Beijing 100050P.R.China

Near infrared spectroscopy(NIRS)analysis technology,combined with chemometrics,can be effectively used in quick and nondestructive analysis of quality and *** this paper,an effective drug identification method by using deep belief network(DBN)with dropout mecha-nism(dropout-DBN)to model NIRS is introduced,in which dropout is employed to overcome the overfitting problem coming from the small *** paper tests proposed method under datasets of different sizes with the example of near infrared diffuse refectance spectroscopy of erythromycin ethylsuccinate drugs and other drugs,aluminum and nonaluminum ***,it gives experiments to compare the proposed method's performance with back propagation(BP)neural network,support vector machines(SVMs)and sparse denoising auto-encoder(SDAE).The results show that for both binary classification and multi-classification,dropout mechanism can improve the classification accuracy,and dropout-DBN can achieve best classification accuracy in almost all *** is similar to dropout-DBN in the aspects of classification accuracy and algorithm stability,which are higher than that of BP neural network and SVM *** terms of training time,dropout-DBN model is superior to SDAE model,but inferior to BP neural network and SVM ***,dropout-DBN can be used as a modeling tool with effective binary and multi-class classification performance on a spectrum sample set of small size.

关键词： Deep belief networks near infrared spectroscopy drug classification dropout

Transition metal doped mesoporous titania with a crystalline framework as catalysts for oxidation of p-bromotoluene to pbromobenzaldehyde

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Frontiers of Chemical Science and Engineering 2008年第3期2卷 296-300页

作者： Zehui YANG lihui yin Encai OU Yunan WANG Li PENG Jiaqiang WANG Department of Applied Chemistry Key Laboratory of Medicinal Chemistry for Natural Resource(Yunnan University)Ministry of EducationYunnan UniversityKunming 650091China Yantai Shougang Dongxing(Group)Co. Yantai 264006China

Transition metal M(M=Mn,Fe,Co,Ni,Cu,and Zn)doped mesoporous titania with a crystalline framework was employed as catalysts for the oxidation of p-bromotoluene(PBT)to p-bromobenzaldehyde(BBD)in acetic acid using aqueous hydrogen peroxide as *** was found that mesoporous TiO_(2) doped with those metals(Fe,Co and Ni)whose atomic radii are relatively smaller exhibited higher conversion rate of *** these catalysts,the Co/meso-TiO_(2) exhibited high substrate conversion and good product(p-bromobenzaldehyde)selectivity plus it can be reused once with almost the same *** effect of different Ti/Co(molar)ratio on the activities of Co/meso-TiO_(2) was also investigated.

关键词： Oxidation p-Bromotoluene p-Bromobenzaldehyde Crystalline cobalt mesoporous titania

Study on a noninvasive method for rapid screening Human Serum albumin injectables by Raman spectroscopy

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Journal of Innovative Optical Health Sciences 2017年第1期10卷 34-42页

作者： Yu Zhao Nan Ji Xiuji Li Jifeng Hou Min Li Yongjian Yang Ping Tian Xinmei Sun Xinyue Xiao lihui yin National Institutes of Food and Drug Control(NIFDC)No.2 Tiantan Xi Li BeijingP.R.China tSichuan Vspec Technologies Co.Ltd.Beijing Office No.2 BeiTaiPingZhuang RoadBeijingP.R.China Shanghai Institute for Food and Drug Control(SIFDC)No.1500 Zhangheng Road ShanghaiP.R.China

Human serum albumin(HSA)injectable product is a severely afflicted area on drug safety due to its high price and restricted *** spectroscopy performances high specificity on HSA detection and it is even possible to determine HSA injectable products *** this study,we developed a noninvasive rapid screening method for of HSA injectable products by using portable Raman *** models were established by using principal component analysis combined with classical least squares(PCA-CLS)algorithm,while quanti-tative model was established by using partial least squares(PLS)*** transfer in different instruments of both the same and different apparatus modules was further discussed in this paper.A total of 34 HSA injectable samples collected from markets were used for *** identification results showed 100%accuracy and the predicted concentrations of those identified as true HSA were consistent with their labeled *** quantitative results also indicated that model transfer was excellent in the same apparatus modules of Raman spectrometer at all concentration levels,and still good enough in the different apparatus modules although the relative standard deviation(RSD)value showed a little increasing trend at low HSA concentration *** conclusion,the method was proved to be feasible and efficient for screening HSA injections,especially on its screening speed and the consideration of glass ***,with inspiring results on the model transfer,the method could be used as a universal screening mean to different Raman instruments.

关键词： Human serum albumin Raman noninvasive rapid screening method principal component analysis combined with classical least squares partial least squares model transfer.

环境规制与长江经济带污染密集型产业生态效率

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中国软科学 2021年第8期 181-192页

作者：尹礼汇吴传清武汉大学经济与管理学院湖北武汉430072 武汉大学中国发展战略与规划研究院湖北武汉430072 武汉大学区域经济研究中心湖北武汉430072

基于2003-2016年长江经济带沿线11省份污染密集型产业数据,采用超效率SBM模型、STIRPAT模型、工具变量法和空间杜宾模型,研判环境规制对长江经济带污染密集型产业生态效率的影响及其空间溢出效应。研究结果显示:政府管制型、公众参与型... 详细信息

基于2003-2016年长江经济带沿线11省份污染密集型产业数据,采用超效率SBM模型、STIRPAT模型、工具变量法和空间杜宾模型,研判环境规制对长江经济带污染密集型产业生态效率的影响及其空间溢出效应。研究结果显示:政府管制型、公众参与型环境规制均能提升长江经济带污染密集型产业生态效率,具有正向的空间溢出效应;滞后两期政府管制型环境规制对生态效率的影响遵循"合规成本假说",滞后两期公众参与型环境规制遵循"波特假说";对长江经济带上中下游地区而言,环境规制的影响存在区域差异性;长江经济带以外地区政府管制型环境规制对长江经济带污染密集型产业生态效率的影响显著为负。为促进长江经济带污染密集型产业生态化发展,应加快创新驱动产业转型升级,制定科学合理环境规制,引导产业有序转移。

关键词：长江经济带污染密集型产业环境规制生态效率空间杜宾模型

增加土地储备能提升房地产开发企业的绩效吗?——基于114家房地产上市公司面板数据的实证分析

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经济与管理评论 2019年第2期35卷 56-68页

作者：赵伟尹礼汇武汉大学经济与管理学院湖北武汉430072

将土地储备行为纳入到房地产开发企业绩效研究的框架中,构建了一个土地储备决策模型,并以114家房地产上市公司为样本,运用DEA-Tobit两步法实证分析了土地储备行为对房地产开发企业绩效的影响,进一步解释了不同所有权性质和企业规模的房... 详细信息

将土地储备行为纳入到房地产开发企业绩效研究的框架中,构建了一个土地储备决策模型,并以114家房地产上市公司为样本,运用DEA-Tobit两步法实证分析了土地储备行为对房地产开发企业绩效的影响,进一步解释了不同所有权性质和企业规模的房企在土地储备行为上的差异性。研究发现:土地总储备面积对房地产开发企业绩效增长有显著的正效应;当年土地储备面积和绩效之间则呈"倒U型"关系;相对于民营、小型房企而言,国有以及大型房企增加土地储备更能促进企业绩效的提升;房地产开发企业应合理规划土地储备规模,政府需加强对土地市场的监督和管理。

关键词：土地储备企业绩效所有权性质企业规模