SMART Researchers Develop Novel Method for Rapid Microbial Contamination Detection in Cell Cultures
Singapore – Researchers at the Critical Analytics for Manufacturing Personalized-Medicine (CAMP) interdisciplinary research group of the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, have announced a groundbreaking method for the swift detection of microbial contamination in cell therapy products (CTPs). This innovation, developed in collaboration with MIT, A*STAR Skin Research Labs, and the National University of Singapore, promises to significantly reduce the time required for sterility testing, potentially saving lives through faster treatment delivery.
Cell therapy is revolutionizing medicine, offering new treatments for cancers, inflammatory diseases, and chronic degenerative disorders. However, ensuring these cell therapies are free from contamination before administration has been a major hurdle.
Existing sterility testing methods can take up to 14 days, a delay that can be detrimental for critically ill patients. While rapid microbiological methods (RMMs) can shorten this period to seven days, they require complex processes and skilled labor. This necessitates faster, simpler methods without compromising CTP quality.
Published in Scientific Reports, their paper, “Machine learning aided UV absorbance spectroscopy for microbial contamination in cell therapy products,” details how the team combined UV absorbance spectroscopy with machine learning to achieve label-free, noninvasive, and real-time contamination detection.
The new method measures ultraviolet light absorbance of cell culture fluids and uses machine learning to recognize patterns associated with microbial contamination, providing rapid “yes/no” contamination assessment in under half an hour. This eliminates the need for cell staining and extraction and allows for automated cell culture sampling with a simple workflow, reducing costs and complexity, and offers significant advantages over traditional methods by delivering results in under half-an-hour.
Shruthi Pandi Chelvam, senior research engineer at SMART CAMP and first author of the paper, emphasizes that this method serves as a preliminary safety test, enabling early detection and timely corrective actions. “This rapid, label-free method is designed to be a preliminary step in the CTP manufacturing process as a form of continuous safety testing… This approach saves costs, optimizes resource allocation, and ultimately accelerates the overall manufacturing timeline,” she stated.
Rajeev Ram, the Clarence J. LeBel Professor at MIT and a principal investigator at SMART CAMP, added, “By introducing automation and machine learning, we hope to streamline cell therapy manufacturing and reduce the risk of contamination… This enables cell cultures to be monitored continuously and contamination to be detected at early stages.”
Future research will focus on expanding the method’s application to a wider range of microbial contaminants and testing its robustness across more cell types. The researchers also suggest potential applications beyond cell therapy, including microbial quality control testing in the food and beverage industry.
