TY - JOUR
T1 - Optimization of key energy and performance metrics for drug product manufacturing
AU - Chen, Yingjie
AU - Kotamarthy, Lalith
AU - Dan, Ashley
AU - Sampat, Chaitanya
AU - Bhalode, Pooja
AU - Singh, Ravendra
AU - Glasser, Benjamin J.
AU - Ramachandran, Rohit
AU - Ierapetritou, Marianthi
N1 - Funding Information:
The authors would like to acknowledge funding support from the Department of Energy (DOE) through the University of California Los Angeles (UCLA) and the Clean Energy Smart Manufacturing Innovation Institute (CESMII) via sub-award No. 4550GYA102.
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2023/1/25
Y1 - 2023/1/25
N2 - During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors (Sampat et al., 2022), this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. The results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.
AB - During the development of pharmaceutical manufacturing processes, detailed systems-based analysis and optimization are required to control and regulate critical quality attributes within specific ranges, to maintain product performance. As discussions on carbon footprint, sustainability, and energy efficiency are gaining prominence, the development and utilization of these concepts in pharmaceutical manufacturing are seldom reported, which limits the potential of pharmaceutical industry in maximizing key energy and performance metrics. Based on an integrated modeling and techno-economic analysis framework previously developed by the authors (Sampat et al., 2022), this study presents the development of a combined sensitivity analysis and optimization approach to minimize energy consumption while maintaining product quality and meeting operational constraints in a pharmaceutical process. The optimal input process conditions identified were validated against experiments and good agreement resulted between simulated and experimental data. The results also allowed for a comparison of the capital and operational costs for batch and continuous manufacturing schemes under nominal and optimized conditions. Using the nominal batch operations as a basis, the optimized batch operation results in a 71.7% reduction of energy consumption, whereas the optimized continuous case results in an energy saving of 83.3%.
KW - Energy-efficient manufacturing
KW - Optimization in pharmaceutical manufacturing
KW - Pharmaceutical industry carbon net-zero
KW - Sensitivity analysis of drug product processing
KW - Wet granulation flowsheet model
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U2 - 10.1016/j.ijpharm.2022.122487
DO - 10.1016/j.ijpharm.2022.122487
M3 - Article
C2 - 36521636
AN - SCOPUS:85144514897
SN - 0378-5173
VL - 631
JO - International Journal of Pharmaceutics
JF - International Journal of Pharmaceutics
M1 - 122487
ER -