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Development of Process Analytical Technology (PAT) for Total Quality Innovation on Pharmaceutical Processes

의약품 제조공정에서의 전사적 품질혁신을 위한 공정분석기술 개발

  • Shin, Sang-Mun (Department of Systems Management & Engineering, Inje University) ;
  • Park, Kyung-Jin (Department of Systems Management & Engineering, Inje University) ;
  • Choi, Yong-Sun (Department of Systems Management & Engineering, Inje University) ;
  • Lee, Sang-Kil (Department of Pharmaceutical Engineering, Inje University) ;
  • Choi, Guang-Jin (Department of Pharmaceutical Engineering, Inje University) ;
  • Kwon, Byung-Soo (Department of Pharmaceutical Engineering, Inje University) ;
  • Cho, Byung-Rae (Department of Industrial Engineering, Clemson University)
  • 신상문 (인제대학교 시스템경영공학과) ;
  • 박경진 (인제대학교 시스템경영공학과) ;
  • 최용선 (인제대학교 시스템경영공학과) ;
  • 이상길 (인제대학교 제약공학과) ;
  • 최광진 (인제대학교 제약공학과) ;
  • 권병수 (인제대학교 제약공학과) ;
  • Published : 2007.12.21

Abstract

The quality assurance issue of drug products is more important than the general product because it is highly related to the human health and life. In this reason, the regulatory guide lines have continuously been intensified all around the world. In order to achieve effective quality assurance and real-time product release (RTPR) of drug products, process analytical technology (PAT), which can analyze and control a manufacturing process, has been proposed from the United States. With the PAT process, we can obtain significant process features of materials, quality characteristics and product capabilities from a raw material to the final product in the real-time procedure. PAT can also be utilized to process validation using information system that can analyze the risk of drug products through out an entire product life-cycle. In this paper, we first offered a new concept for the off-line process design methods to prepare the improved quality assurance restrictions and a real-time control method by establishing an information system. We also introduced an automatic inspection system by obtaining surrogate variables based on drug product formulations. Finally, we proposed an advanced PAT concept using validation and feedback principles through out the entire life-cycle of drug product manufacturing processes.

Keywords

References

  1. U.S. Food and Drug Administration, 'Innovation and Continuous Improvement in Pharmaceutical Manufacturing Pharmaceutical cGMPs for the 21st Century', http://www.fda.gov/cder/gmp/gmp2004/manufSciWP.pdf. (2004)
  2. D. Radspinner, 'Implementation of PAT: An Industry Perspective', Sanofi-aventis. RPS/FDA/Meeting, London. http://www.fda.gov/cder/OPS/Radspinner.pdf. (2004)
  3. FDA. PAT-A Framework for Innovative Manufactming and Quality Assurance, Draft Guidance; 2003
  4. R.S. Benson and D.J. MacCabe, From good manufacturing practice to good manufacturing performance, Pharm. Eng., 24, 26-34 (2004)
  5. 식품의약품안정청, 대통령업무보고-2007년도 주요업무계획 (2007)
  6. S. Shin, B.R. Cho, M.I. Zelaya and Y. Choi, 'Experimental Design Aspects for Nanoparticle Pharmaceutical Formulations', IERC, Nashville, TN. (2007)
  7. R.P. Cogdill, C.A. Anderson, M.D-Lopez, D. Molseed, R. Chisholm, R. Bolton, T. Herkert, A.M. Afnan and J.K. Drennen III, Process Analytical Technology Case Study Part 1: Feasibility Studies for Quantitative Near-Infrared Method Development, AAPS PharmSciTech, 6, E262-E272 (2005) https://doi.org/10.1208/pt060237
  8. R.P. Cogdill, C.A. Anderson, M.D-Lopez, D. Molseed, R. Chisholm, R. Bolton, T. Herkert, A.M. Afnan and J.K. Drennen III, Process Analytical Technology Case Study: Part II. Development and Validation of Quantitative NearInfrared Calibrations in Support of a Process Analytical Technology Application for Real-Time Release, AAPS PharmSciTech, 6, E273-E283 (2005) https://doi.org/10.1208/pt060238
  9. R.P. Cogdill, C.A. Anderson and J.K. Drennen III, Process Analytical Technology Case Study, Part III: Calibration Monitoring and Transfer, AAPS PharmSciTech, 6, E284-E297 (2005) https://doi.org/10.1208/pt060239
  10. S. Airaksinen, M. Karjalainen, N. Kivikero, S. Westermarck, A. Shevchenko, J. Rantanen and J. Yliruusi, Excipient Selection Can Significantly Affect Solid-State Phase Transformation in Formulation During Wet Granulation, AAPS PharmSciTech, 6, E311-E322 (2005) https://doi.org/10.1208/pt060241
  11. N. Sandler, J. Rantanen, J. Heinaamaki, M. Romer, M. Marvola and J. Yliruusi, Pellet Manufacturing by ExtrusionSpheronization Using Process Analytical Technology, AAPS PharmSciTech, 6, E174-E183 (2005) https://doi.org/10.1208/pt060226
  12. R.B. Shah, M.A. Tawakkul and M.A. Khan, Process analytical technology: chemometric analysis of Raman and near infra-red spectroscopic data for predicting physical properties of extended release matrix tablets, J. Pharm. Sci., 96, 1356-65 (2007) https://doi.org/10.1002/jps.20931
  13. M. Kim, H. Chung, Y. Woo and M.S. Kemper, A new noninvasive, quantitative Raman technique for the determination of an active ingredient in pharmaceutical liquids by direct measurement through a plastic bottle, Anal. Chim. Acta., 587, 200-207 (2007) https://doi.org/10.1016/j.aca.2007.01.062
  14. S. Matero, J. Pajander, A.M. Soikkeli, S.P. Reinikainen, M. Lahtela-Kakkonen, O. Korhonen J. Ketolainen and A. Poso, Predicting the drug concentration in starch acetate matrix tablets from ATR-FTIR spectra using multi-way methods. Anal. Chim. Acta., 595, 190-197 (2007) https://doi.org/10.1016/j.aca.2007.02.008
  15. 윤춘희, 국내 원료의약품 제조공정에의 공정분석기술 도입에 관한 연구, 중앙대학교 의약식품대학원 석사학위 논문 (2005)
  16. S. Barthe and R.W. Rousseau, Utilization of Focused Beam Reflectance Measurement in the Control of Crystal Size Distribution in a Batch Cooled Crystallizer, Chem. Eng. Tech., 29, 206-211 (2006) https://doi.org/10.1002/ceat.200500364
  17. L. Ehrl, M. Soos and M. Morbidelli, Sizing Polydisperse Dispersions by Focused Beam Reflectance and Small Angle Static Light Scattering, Particle & Particle Sys. Charact., 23, 438-447 (2007)
  18. B.R. Cho, Y.J. Kim, D.L. Kimber and M.D. Phillips, An integrated joint optimization procedure for robust and tolerance design, Int. J. Produc. Res., 38, 2309-2325 (2000) https://doi.org/10.1080/00207540050028115
  19. H. Scheffe, The Simplex-Centroid Design for Experiments with Mixture, J. Royal Statist. Soc. B, 25, 235-263 (1963)
  20. J.A. Cornell, Experiments with Mixtures: Designs, Models, and The Analysis of Mixture Data, John Wiley and Sons, New York, (1981)
  21. D.C. Montgomery, Design and Analysis of Experiments, 5th Edition, John Wiley and Sons, New York, (2001)
  22. R.H. Myers and D.C. Montgomery, Response Surface Methodology, John Wiley and Sons, New York, (1995)
  23. G.G. Vining and R.H. Myers, Combining Taguchi and response surface philosophies: A dual response approach, J. Quality Tech., 22, 38-45 (1990) https://doi.org/10.1080/00224065.1990.11979204
  24. S. Shin and B.R. Cho, A Bias-Specified Robust Design Model and an Analytical Solution, Comput. Ind. Eng., 48, 129-140 (2005) https://doi.org/10.1016/j.cie.2004.07.011
  25. I.T. Jolliffe, Principal Component Analysis, 2nd Edition, Springer-Verlag, New York, 199-228 (2002)
  26. D.C. Montgomery, Introduction to statistical quality control, 5th Edition, John Wiley and Sons, New York, 385-416 (2004)
  27. T. Hou, L. Lin and C.G. Drury, An empirical study of hybrid inspection systems and allocation of inspection functions, Int. J. Human Factors in Manufac., 3, 351-367 (1993) https://doi.org/10.1002/hfm.4530030404
  28. R.J. Poppi and A. Borin, Multivariate quality control of lubricating oils using Fourier transform infrared spectroscopy, J. Braz. Chem. Soc., 15, 570-576 (2004) https://doi.org/10.1590/S0103-50532004000400020