Optimization of key energy and performance metrics for drug product manufacturing

Yingjie Chen, Lalith Kotamarthy, Ashley Dan, Chaitanya Sampat, Pooja Bhalode, Ravendra Singh, Benjamin J. Glasser, Rohit Ramachandran

Research output: Contribution to journalArticlepeer-review


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%.

Original languageAmerican English
Article number122487
JournalInternational Journal of Pharmaceutics
StatePublished - Jan 25 2023

ASJC Scopus subject areas

  • Pharmaceutical Science


  • Energy-efficient manufacturing
  • Optimization in pharmaceutical manufacturing
  • Pharmaceutical industry carbon net-zero
  • Sensitivity analysis of drug product processing
  • Wet granulation flowsheet model


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