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Real-Time Process Management Strategy for Dropwise Additive Manufacturing of Pharmaceutical Products

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Abstract

Purpose

This paper presents a real-time process management (RTPM) strategy for Dropwise Additive Manufacturing of Pharmaceutical Products (DAMPP), a mini-manufacturing method for pharmaceutical dosage forms. The semicontinuous, small-scale nature of DAMPP allows for more automation and control than traditional large-scale batch pharmaceutical manufacturing processes and can be used to manufacturing drug products with precise amounts of active pharmaceutical ingredients (API), suitable for production of high-potency drug products or individualized medicine.

Methods

The RTPM strategy for DAMPP consists of advanced process control to ensure that every dosage unit meets quality specifications. We use temperature control systems and an imaging system linked to a LabVIEW automation program.

Results

The system is successful in controlling deposition of both solvent-based and melt-based dosage forms. It controls process and product temperature and monitors each drop visually. It records data pertinent to each deposited drop, determines the drop volume and thus API amount deposited, and automatically detects and diagnoses process faults.

Conclusions

With a proper automation, control, and monitoring strategy, DAMPP is a viable manufacturing method for pharmaceutical dosage forms.

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Acknowledgments

This work was completed with the support from the National Science Foundation Engineering Research Center for Structured Organic Particulate Systems (EEC-0540855). We would like to thank Indiana Next Generation Manufacturing Competitiveness Center (IN-MaC) for the financial support provided to E.I. We are grateful for the advice and counsel of Fritz Fiesser of GlaxoSmithKline on a range of technical implementation issues.

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Correspondence to Laura Hirshfield.

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Hirshfield, L., Içten, E., Giridhar, A. et al. Real-Time Process Management Strategy for Dropwise Additive Manufacturing of Pharmaceutical Products. J Pharm Innov 10, 140–155 (2015). https://doi.org/10.1007/s12247-015-9218-5

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  • DOI: https://doi.org/10.1007/s12247-015-9218-5

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