NIR Fig. 1 Process profiles of manufacture units of Qingkailing injection international conference on harmonization of technical requir

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1 Vol. 40No. 14 July2015 NIR * * Real-time detection of quality of Chinese materia medica strategy of NIR model evaluation WU Zhi-sheng SHI Xin-yuan 1 3* XU Bing 1 2 DAI Xing-xing 1 3 QIAO Yan-jiang 1 3* 1. Beijing University of Chinese MedicineBeijing China 2. State Key Laboratory of Dao-di HerbsNational Resource Center for Chinese Materia Medica China Academy of Chinese Medical SciencesBeijing China 3. Key Laboratory of Traditional Chinese Medicine-Information Engineering of State Administration of Traditional Chinese MedicineBeijing China AbstractThe definition of critical quality attributes of Chinese materia medica CMMwas put forward based on the top-level design concept. Nowadayscoupled with the development of rapid analytical sciencerapid assessment of critical quality attributes of CMM was firstly carried outwhich was the secondary discipline branch of CMM. Taking near infrared NIRspectroscopy as an examplewhich is a rapid analytical technology in pharmaceutical process over the past decade systematic review is the chemometric parameters in NIR model evaluation. According to the characteristics of complexity of CMM and trace components analysisa multi-source information fusion strategy of NIR model was developed for assessment of critical quality attributes of CMM. The strategy has provided guideline for NIR reliable analysis in critical quality attributes of CMM. Key wordsnear infraredprocess analytical technologymodel evaluationaccuracy profilequality by design doi /cjcmm * Tel net * xyshi@ 126. com 2774 Tel 010

Beijing University of Chinese MedicineBeijing 100102China 2.

2 NIR Fig. 1 Process profiles of manufacture units of Qingkailing injection international conference on harmonization of technical requirements for registration of pharmaceuticals for human use ICHQ8 quality by design QbD 3 QbD critical quality attribute CQA critical process parameter CPP 2775

international conference on harmonization of technical requirements for

3 Vol. 40No. 14 July Food and Drug Administration FDA process analytical technology PAT cgmp FDA PAT 4 2 NIR Fig. 2 NIR quantitative analysis of critical quality attributes of process analytical chemistry PAC Chinese materia medica Analytical Chemistry NIR NIR infrared spectroscopy nearinfrared NIR imaging la- ser induced breakdown spectroscopy terahertz spectroscopy ultrasonic imaging - NIR Raman spectroscopy and Raman imaging magnetic resonance imaging NIR PAT NIR PAT C-H N-H O-H NIR 3 NIR NIR NIR NIR 2 1 NIR NIR NIR NIR NIR 21

2003 NIR NIR infrared spectroscopy nearinfrared NIR imaging la- ser induced breakdown spectroscopy terahertz spectroscopy ultrasonic imaging - NIR Raman

4 NIR NIR NIR NIR 1 1 Table 1 NIR NIR model evaluation of chemometrics parameters in critical quality attributes of Chinese materia medica R 2 RMSEP SEP Rg 1 Rb 1 HPLC PLS ANN % 0. 1% Rd % 0. 2% B Ⅱ A HPLC PLS HPLC PLS Rg 1 Rb 1 Rd 1 HPLC SVM % 7. 4% % 17. 2% PLS % PLS HPLC PLS % % LLE-PLS B HPLC PLS % HPLC PLS B HPLC PLS % % Ⅱ A % HPLCiPLS SiPLS HPLC PLS % HPLC PLS % % HPLC PLS % 0. 01% HPLC PLS % HPLC PLSiPLSSiPLS ppm 7 ppm BiPLS MWPLS A HPLC PLS ppm Ⅱ A HPLC PLS A HPLC PLS ppm 42 ppm B HPLC PLS % HPLC PLS B HPLC La % prlsr PLS HPLC PLS A B D ppm HPLC PLS ppm NIR NIR 10 NIR NIR root 3. 2 NIR mean square error of calibration RMSEC root mean square error of prediction RMSEP determination coefficient R 2 Bias J Mantanus NIR NIR NIR 2777

971 Rg 1 Rb 1 Rd 1 HPLC SVM 0. 9920. 984 5. 2% 7. 4% 0. 986 0. 898 6. 3% 17. 2% PLS 0. 974 0. 03% PLS 0. 902 HPLC PLS 0. 987 7 0. 983 8 0. 003% 0. 003% LLE-PLS B HPLC PLS 0. 995 2 0. 02% HPLC PLS 0.

5 Vol. 40No. 14 July NIR 0. 1% ~ 0. 3% P Hubert RPIQ 43 RMSEP DI accuracy profile NIR NIR partial least squares PLS NIR AlaProTyrValLeuPheTrp Lys NIR 49 P Hubert 4 total error conceptnir NIR NIR Talanta ipls RMSEP R 2 NIR mg L BiPLS RMSEP R 2 International Union of Pure and Applied Chemistry IUPAC International Or- BiPLS ipls mg L RMSEP R 2 ganization for Standardization ISO RPIQ mwpls RPIQ MDL34. 8BiPLS RPIQ mwpls MQL BiPLS PLS RPIQ 22. 1iPLS 44 Marcel Blanco RPIQ 4 PLS 2 NIR NIR NIR 20 ppm 45 Miren Ostra 95% β- 10% 5% 46 Manel PLS ipls BiPLS mwpls 4 Alcala Marcel Blanco 4PLS 1 ~ 4 g L % β g L g NIR L - 1 ipls NIR 95% β g L Marcel Blanco 4bBiPLS % β g L - 1 NIR NIR 1. 5 g L - 1 4cmwPLS 95% β NIR g L g L - 1 R 2 RMSEC RMSECV 4d RMSEP mwpls ipls RPD RPD = SD /SEP RPIQ DIRPIQ Veronique Bellon-Maurel Q1 25% 5 Q2 Q3 75% interquartile distance IQ 50% IQ SD 2778 AspGluSerGly 3 PLS ipls BiPLS mwpls NIR RPIQ PLS RPIQ ipls 1 g L g L - 1

2 ipls RMSEP R 2 NIR 261. 66 mg L - 1 0. 976 0BiPLS RMSEP R 2 International Union of Pure and Applied Chemistry IUPAC International Or- BiPLS ipls 122. 63 mg L - 1 0.

6 NIR 3 Fig. 3 4 HPLC Four NIR predictions versus the reference method results 95% β- a. PLS b. ipls c. bipls d. mwpls 4 Fig. 4 4 Accuracy profiles of four models 2779

7 Vol. 40No. 14 July2015 J NIR LLE-PLS J J NIR 19. NIR J NIR Ⅱ A J. NIR NIR J NIR 22. D J J J J U. S. Food Drug Administration. Guidance for industry PATa framework for innovative pharmaceutical development manufacturing and quality assuranceeb /OL Beebe K RBlaser W WBredeweg R Aet al. Progress analytical chemistry J. Anal Chem Blaser W WBredeweg R AHarner R Set al. Process analytical chemistry J. Anal Chem Workman J JVeltkamp D JDoherty Set al. Process analytical chemistry J. Anal Chem Workman J JCreasy K EDoherty Set al. Process analytical chemistry J. Anal Chem Workman J JKoch MVeltcamp D J. Process analytical chemistry J. Anal Chem Workman J JKoch MVeltkamp D J. Process analytical chemistry J. Anal Chem Workman J JKoch MVeltkamp D J. Process analytical chemistry J. Anal Chem Workman J JKoch MLavine Bet al. Process analytical chemistry J. Anal Chem Workman J JLavine BChrisman Ret al. Process analytical chemistry J. Anal Chem Li W LXing L HFang L Met al. Application of near infrared spectroscopy for rapid analysis of intermediates of Tanreqing injection J. J Pharm Biomed Li W LQu H B. Rapid quantification of phenolic acids in Radix Salvia Miltrorrhiza extract solutions by FT-NIR spectroscopy in transflective mode J. J Pharm Biomed J J J J J J AOTF- J J NIR J J J

Guidance for industry PATa framework for innovative pharmaceutical development manufacturing and quality assuranceeb /OL. 2014-09. 5Beebe K RBlaser W WBredeweg R Aet al.

8 NIR NIR kernel Isomap-PLS 48Wu Z SSui C LXu Bet al. Multivariate detection limits of on-line NIR model for extraction process of chlorogenic acid from J Wu Z SPeng Y FChen Wet al. NIR spectroscopy as a J process analytical technology PATtool for monitoring and understanding of a hydrolysis process J. Bioresour Technol 38Mantanus JZiemons ELebrun Pet al. Moisture content determination of pharmaceutical pellets by near infrared spectroscopy method development and validation J. Anal Chim Acta Mantanus JZiemons ERozet Eet al. Active content determination of non-coated pharmaceutical pellets by near infrared spectroscopymethod developmentvalidation and reliability evaluation J. Talanta Wu Z SDu MSui C Let al. Development and validation of a portable AOTF-NIR measurement method for the determination of Baicalin in Yinhuang oral solutionc. Xi'anInternational Conference on Biomedical Engineering and Biotechnology Wu Z SDu MSui C Let al. Validation of a NIR quantification method for the determination of chlorogenic acid in Lonicera japonica solution in ethanol precipitation process J. J Pharm Biomed Wu Z SDu MSui C Let al. Development and validation of PLS model using low-concentration calibration rangerapid analysis of solution from Lonicera japonica in ethanol precipitation process J. Anal Methods Boque RRius F X. Multivariate detection limits estimators J. Chemom Intell Lab Blanco MCastillo MPeinado Aet al. Determination of low analyte concentrations by near-infrared spectroscopyeffect influence of spectral pretreatments and estimation of multivariate detection limits J. Anal Chim Acta Ostra MUbide CVidal Met al. Detection limit estimator for multivariate calibration by an extension of the IUPAC recommendations for univariate methods J. Analyst Alcala MLeon JRopero Jet al. Analysis of low content drug 35. tablets by transmission near infrared spectroscopy. Selection of A J calibration ranges according to multivariate detection and quantitation limits of PLS models J. J Pharm Sci Lonicera japonica J. J Pharm Biomed Peng Y FShi X YZhou L Wet al. Multivariate detection limit of baicalin in Qingkailing injection based on four NIR technology types J. Spectrosc Spect Anal Wu Z SDu MXu Bet al. Absorption characteristics and quantitative contribution of overtones and combination of NIR Method development and validationj J Mol Struc Wu Z STao ODai X Xet al. Monitoring blending process of Yinhuang powder by near infrared chemical imaging J. Vib Spectrosc Wu Z SDu MSui C Let al. Feasibility analysis of lower limit 53Wu Z STao OCheng Wet al. Visualizing excipient composition and homogeneity of compound liquorice tablets by near-infra- of quantification of NIR for solvent in different hydrogen bonds environment using multivariate calibrationsc. Xi'anInternational Conference on Biomedical Engineering and Biotechnology 54Wu Z STao OCheng Wet al. Research on spatial distribution red chemical imaging J. Spectrochim Acta A and composition uniformity of Rukuaixiao tablets intermediate by spectral imaging J. Chin J Anal Chem Xu BWu Z SLin Z Zet al. NIR analysis for batch process of ethanol precipitation coupled with a new calibration model updating strategy J. Anal Chim Acta Xu BLin Z ZShi X Yet al. NIR determination of three critical quality attributes in alcohol precipitation process of Lonicerae japonicae with uncertainty analysisc. Xi' aninternational Conference on Biomedical Engineering and Biotechnology Sui C LLin Z ZWu Z Set al. A simulation study for the effect of particle size on on-line measurement sampling system of traditional Chinese medicine extraction process J. Chin J Anal Chem Sui C LWu Z SPeng Y Fet al. Validation of NIR model for on-line monitoring of Flos Lonicera Japonica extraction process with different batches of materials J. ijoe Wu Z SMa QLin Z Zet al. A novel model selection strategy using total error concept J. Talanta

Moisture content determination of pharmaceutical pellets by near infrared spectroscopy 2013137394. method development and validation J. Anal Chim Acta2009 642186. 39Mantanus JZiemons ERozet Eet al.

Fig. 2 Relationships among the design space knowledge space and control space 1 Fig. 1 Graphical abstract of the pharma

Fig. 2 Relationships among the design space knowledge space and control space 1 Fig. 1 Graphical abstract of the pharma 38 6 徐冰 1, 史新元 1,2*, 乔延江 1,2*, 吴志生 1 1, 林兆洲 ( 1. 北京中医药大学中药信息工程研究中心, 北京 100102; 2. 教育部中药制药与新药开发关键技术工程研究中心, 北京 100102) quality by design QbD QbD design space 2007 3 2006 2020 1 2010 FDA 2002 21 cgmp 6 2004