Process analytical technology case study, part III: Calibration monitoring and transfer

AAPS PharmSciTech

Volumn 6, Issue 2, 2005, Pages

  Cogdill, Robert P ^a   Anderson, Carl A ^a   Drennen III, James K ^a  

^a DUQUESNE UNIVERSITY   (United States)

Author keywords

Calibration transfer; Near infrared spectroscopy (NIR); Pharmaceutical analysis; Process analytical technology (PAT); Tablet analysis

Indexed keywords

DRUG;

ACCURACY; ALGORITHM; ANALYTIC METHOD; ANALYTICAL ERROR; ARTICLE; CALIBRATION; CASE STUDY; CONTROLLED STUDY; DRUG STABILITY; DRUG STORAGE; INTERMETHOD COMPARISON; MONITORING; NEAR INFRARED SPECTROSCOPY; PERFORMANCE; PREDICTION; PROCESS DEVELOPMENT; REGRESSION ANALYSIS; STANDARDIZATION; TABLET HARDNESS; TABLET PROPERTY;

EID: 27744466385     PISSN: 15309932     EISSN: 15309932     Source Type: Journal    
DOI: 10.1208/pt060239     Document Type: Article

References (27)

1. Cogdill RP, Anderson CA, Delgado-Lopez M. Process Analytical Technology Case Study, Part I: Feasibility Studies for Quantitative NIR Method Development. AAPS PharmSciTech. 2005:E262-E272.
2. Cogdill RP, Anderson CA, Delgado-Lopez M. Process Analytical Technology Case Study, Part II: Development and Validation of Quantitative for Tablet API Content and Hardness, AAPS PharmSciTech. 2005:E273-E283.
3. Food and Drug Administration. PAT - A Framework for Innovative Manufacturing and Quality Assurance, Draft Guidance. Rockville, MD: 2003.
4. Box GEP, Jenkins GM, Reinsel G. Time Series Analysis Englewood Cliffs, NJ: Prentice Hall; 1994.
5. Jackson JE, Mudholkar GS. Control procedures for residuals associated with principal components analysis. Technometrics. 1979;21:341-349.
6. Williams P, Norris K. Near-Infrared Technology in the Agricultural and Food Industries St. Paul, MN: American Association of Cereal Chemists; 2001.
7. Greensill CV, Wolfs PJ, Speigelman CH, Walsh KB. Calibration transfer between PDA-based spectrometers in the NIR assessment of melon soluble solids content. J Appl Spectrosc. 2001;55:647-653.
8. Fearn T. Standardisation and calibration transfer for near ilnfrared instruments: a review. J Near Infrared Spectrosc. 2001;9:229-244.
9. Zeaiter M, Roger JM, Bellon-Maurel V, Rutledge DN. Robustness of models developed by multivariate calibration. Part I: the assessment of robustness. Trends Analyt Chem. 2004;23:157-170.
10. Fearn T. On orthogonal signal correction. Chemom Intell Lab Syst. 2000;50:47-52.
11. Sjöblom J, Svensson O, Josefson M, Kullberg H, Wold S. An evaluation of orthogonal signal correction applied to calibration transfer of near infrared spectra. Chemom Intell Lab Syst. 1998;44:229-244.
12. Wold S, Antti H, Lindgren F, Öhman J. Orthogonal signal correction of near-infrared spectra. Chemom Intell Lab Syst. 1998;44:175-185.
13. Andersson CA. Direct orthogonalization. Chemom Intell Lab Syst. 1999;47:51-63.
14. Haaland DM, Melgaard DK. New prediction-augmented classical least squares (PACLS) methods: Application to unmodeled interferents. J Appl Spectrosc. 2000;54:1303-1312.
15. Wise BM, Martens H, Hoy M. Calibration transfer by generalized least squares. Eigenvector Research Incorporated Report. Available at: http:// www.eigenvector.com/Docs/. Accessed February 4, 2005.
16. Bouveresse E, Massart D, Dardenne P. Calibration transfer across near-infrared spectrometric instruments using Shenk's algorithm: effects of different standardisation samples. Anal Chim Acta. 1994;297:405-416.
17. Dardenne P. Standardisation of near-infrared instruments, influence of the calibration methods and the size of the cloning set. In: Davies AMC, Cho RK, eds. Near Infrared Spectroscopy: Proceedings of the 10th International Conference. Chichester, West Sussex, UK: NIR Publications; 2002:23-28.
18. Shenk J. Standardizing NIR instruments. In: Biston R, Bartiaux-Thill N, eds. Third International Conference on Near-Infrared Spectroscopy. Gembloux, Belgium: Agricultural Research Centre Publishing; 1991:649-654.
19. Welle R, Greten W, Bernhard R, et al. Near-infrared spectroscopy on chopper to measure maize forage quality parameters online. Crop Sci. 2003;43:1407-1413.
20. Wang Y, Veltkamp D, Kowalski BR. Multivariate instrument standardization. Anal Chem. 1991:63:2750-2756.
21. Wang Y, Kowalski BR. Temperature-compensating calibration transfer for near-infrared filter instruments. Anal Chem. 1993;65:1301-1303.
22. Wang Z, Dean T, Kowalski BR. Additive Background Correction in Multivariate Instrument Standardization. Anal Chem. 1995;67:2379-2385.
23. Gallagher NB. Development and benchmarking of multivariate statistical process control tools for a semiconductor etch process: improving robustness through model updating. IFAC ADCHEM '97 1997; Available at: www.eigenvector.com/About/NBGcv.html. Accessed February 4, 2005.
24. Wise BM, Ricker NL. Identification of finite impulse response models with principal components regression: frequency-response properties. Process Contr Qual. 1992;4:77-86.
25. Funk DB. New methods for wavelength standardisation for near-infrared spectrophotometers, Part 1: review of current standardisation methodology. J Near Infrared Spectrosc. 1996;4:101-106.
26. Manning CJ, Griffiths PR. Noise sources in step-scan FT-IR spectrometry. J Appl Spectrosc. 1997;51:1092-1101.
27. Martens H, Næs T. Multivariate Calibration. New York, NY: John Wiley and Sons; 1989.