2025 AIChE Annual Meeting

(559g) An Automated Platform for Manufacturing Nanoparticles for Drug Delivery Applications

Authors

Joy Ren, Massachusetts Institute of Technology
Sofiya Chubich, Massachusetts Institute of Technology
Andy Liu, The University of Texas at Austin
Dylan Nguyen, Massachusetts Institute of Technology
Richard D. Braatz, Massachusetts Institute of Technology
Allan Myerson, Massachusetts Institute of Technology
The development of a manufacturing process for nanoparticle synthesis for drug delivery applications requires rapid and precise identification of the critical process parameters, the degree of reproducibility, and the ability for regulatory compliance. Given the use of costly reagents, material-efficient approaches are essential. Despite these requirements, traditional screening methodologies—often resource-intensive—remain common practice. These methods typically involve sampling under steady-state conditions, consuming significant amounts of reagents, solvents, and time, followed by offline particle characterization.

We will present our progress in developing an automated platform for nanoparticle manufacturing for drug delivery applications. This platform enables rapid and resource-efficient screening across a large parameter space and will be further enhanced with Bayesian optimization algorithms and automated Design of Experiments (DoE) to accelerate process optimization. The system consists of an impinging jet mixer (IJM)—a mixing technology well-suited for nanoparticle synthesis with the purpose of drug delivery1—integrated with a spatially resolved dynamic light scattering (DLS) instrument for real-time particle characterization. Advanced control software manages communication protocols (OPC UA) to synchronize pumps, valves, and analytical instruments, ensuring precise and efficient operation. Additionally, an SQLite database is implemented for structured data management, complemented by an intuitive graphical user interface (GUI) for real-time monitoring and control.

To demonstrate the platform’s effectiveness, we will showcase its application using one or more model drug delivery mimic systems.

Acknowledgement: This research was supported by the U.S. Food and Drug Administration under the FDA BAA-22-00123 program, Award Number 75F40122C00200.

(1) Devos, C.; Mukherjee, S.; Inguva, P.; Singh, S.; Wei, Y.; Mondal, S.; Yu, H.; Barbastathis, G.; Stelzer, T.; Braatz, R. D.; Myerson, A. S. Impinging Jet Mixers: A Review of Their Mixing Characteristics, Performance Considerations, and Applications. AIChE J. 2024, e18595. https://doi.org/10.1002/aic.18595.