Soft sensor for real-time estimation of tablet potency in continuous direct compression manufacturing operation

被引:13
作者
Kamyar, Reza [1 ]
Pla, David Lauri [1 ]
Husain, Anas [2 ]
Cogoni, Giuseppe [3 ]
Wang, Zilong [1 ]
机构
[1] Pfizer Inc, Pfizer Global Supply, Peapack, NJ 07931 USA
[2] Pfizer Inc, Pfizer Global Supply, Freiburg, Germany
[3] Pfizer Inc, Worldwide Res & Dev, Groton, CT 06340 USA
关键词
Soft sensor; Continuous direct compression; Real-time potency estimation; Process control strategy; PHARMACEUTICAL TABLETS; GRANULATION PROCESS; MULTISCALE; FLOWSHEET; DESIGN; MODEL; PURIFICATION; BATCH; FLOW;
D O I
10.1016/j.ijpharm.2021.120624
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
One of the critical quality attributes of the solid oral dosage forms produced in continuous direct compression operations is the tablet potency. A novel soft sensor comprising of a combination of first principle-based and empirical models has been developed to enable real-time monitoring of blend and tablet potency, and concentrations of other excipients at various stream levels along the direct compression line. The soft sensor model has only three adjustable parameters, primarily associated with the equipment design and operation, so the model is product agnostic which is key to enable flexible manufacturing. The estimation accuracy of the soft sensor is demonstrated through a series of real time experiments which include steady state and dynamic transitions of potency during the runs, compared with offline analytically tested tablet cores. The results indicate that the proposed soft sensor can be utilized as a robust tool for real-time monitoring of potency, suggesting an extension of its utilization to higher levels of control. Two potential applications of the soft sensor are: 1. An element of a control strategy for product diversion; 2. A predictive model for advanced process control strategy to minimize the variability in tablet composition.
引用
收藏
页数:13
相关论文
共 44 条
[21]   PAT-tools for process control in pharmaceutical film coating applications [J].
Knop, Klaus ;
Kleinebudde, Peter .
INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2013, 457 (02) :527-536
[22]   RTD modeling of a continuous dry granulation process for process control and materials diversion [J].
Kruisz, Julia ;
Rehrl, Jakob ;
Sacher, Stephan ;
Aigner, Isabella ;
Horn, Martin ;
Khinast, Johannes G. .
INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2017, 528 (1-2) :334-344
[23]   Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production [J].
Lee, Sau L. ;
O'Connor, Thomas F. ;
Yang, Xiaochuan ;
Cruz, Celia N. ;
Chatterjee, Sharmista ;
Madurawe, Rapti D. ;
Moore, Christine M. V. ;
Yu, Lawrence X. ;
Woodcock, Janet .
JOURNAL OF PHARMACEUTICAL INNOVATION, 2015, 10 (03) :191-199
[24]   End-to-End Continuous Manufacturing of Pharmaceuticals: Integrated Synthesis, Purification, and Final Dosage Formation [J].
Mascia, Salvatore ;
Heider, Patrick L. ;
Zhang, Haitao ;
Lakerveld, Richard ;
Benyahia, Brahim ;
Barton, Paul I. ;
Braatz, Richard D. ;
Cooney, Charles L. ;
Evans, James M. B. ;
Jamison, Timothy F. ;
Jensen, Klavs F. ;
Myerson, Allan S. ;
Trout, Bernhardt L. .
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION, 2013, 52 (47) :12359-12363
[25]   The Evolving State of Continuous Processing in Pharmaceutical API Manufacturing: A Survey of Pharmaceutical Companies and Contract Manufacturing Organizations [J].
McWilliams, J. Christopher ;
Allian, Ayman D. ;
Opalka, Suzanne M. ;
May, Scott A. ;
Journet, Michel ;
Braden, Timothy M. .
ORGANIC PROCESS RESEARCH & DEVELOPMENT, 2018, 22 (09) :1143-1166
[26]   Dynamic Flowsheet Model Development and Sensitivity Analysis of a Continuous Pharmaceutical Tablet Manufacturing Process Using the Wet Granulation Route [J].
Metta, Nirupaplava ;
Ghijs, Michael ;
Schafer, Elisabeth ;
Kumar, Ashish ;
Cappuyns, Philippe ;
Van Assche, Ivo ;
Singh, Ravendra ;
Ramachandran, Rohit ;
De Beer, Thomas ;
Ierapetritou, Marianthi ;
Nopens, Ingmar .
PROCESSES, 2019, 7 (04)
[27]   A multiscale DEM-PBM approach for a continuous comilling process using a mechanistically developed breakage kernel [J].
Metta, Nirupaplava ;
Ierapetritou, Marianthi ;
Ramachandran, Rohit .
CHEMICAL ENGINEERING SCIENCE, 2018, 178 :211-221
[28]   Moisture soft sensor for batch fluid bed dryers: A practical approach [J].
Pla, D. Lauri ;
Kamyar, R. ;
Hashemian, N. ;
Mehdizadeh, H. ;
Moshgbar, M. .
POWDER TECHNOLOGY, 2018, 326 :69-77
[29]   Control of three different continuous pharmaceutical manufacturing processes: Use of soft sensors [J].
Rehrl, Jakob ;
Karttunen, Anssi-Pekka ;
Nicolai, Niels ;
Hoermann, Theresa ;
Horn, Martin ;
Korhonen, Ossi ;
Nopens, Ingmar ;
De Beer, Thomas ;
Khinast, Johannes G. .
INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2018, 543 (1-2) :60-72
[30]   Multi-scale flowsheet simulation of an integrated continuous purification-downstream pharmaceutical manufacturing process [J].
Sen, Maitraye ;
Chaudhury, Anwesha ;
Singh, Ravendra ;
John, Joyce ;
Ramachandran, Rohit .
INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2013, 445 (1-2) :29-38