SMART researchers pioneer novel way to detect microbial contamination in cell cultures

Over the years, cell therapy has become an essential treatment method for many incurable diseases, illnesses and injuries such as cancers, autoimmune diseases, spinal cord injuries, and neurological conditions. In order to create cell therapies that can benefit more people, researchers have continually refined manufacturing methods and processes for cell cultures to ensure safety, efficiency, and sterility.

Against this background, researchers from the Critical Analytics for Manufacturing Personalized-Medicines (CAMP), an Interdisciplinary Research Group (IRG) at the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, have developed a new method of utilizing machine learning to detect the presence of microbial contamination in mesenchymal stromal cell (MSC) cultures within a few minutes. The anomaly detection model is able to predict if a culture is clean or contaminated and can be used during the cell manufacturing process, compared to less efficient end-point testing, thus ensuring rapid and accurate testing of cell therapy products (CTP) intended for use in patients.

Significant step forward