Researchers pioneer a new way to detect microbial contamination in cell cultures | MIT News

Researchers from the Critical analytics for the production of personalized medicine (CAMP) interdisciplinary research group at the Singapore-MIT Alliance for Research and Technology (SMART), the research firm of MIT in Singapore, has developed a new method for detecting adventitious microbial contamination in mesenchymal stromal cell cultures (MSC), enabling rapid and accurate testing of cell therapy products intended for use in patients. By using machine learning to predict in near real time whether a culture is clean or contaminated, this groundbreaking method can be used during the cell production process, compared to less efficient endpoint tests.

Cell therapy has become an essential treatment option for a variety of illnesses, injuries and illnesses in recent years. By transferring healthy human cells into a patient’s body to heal or replace damaged cells, cell therapy has shown promise in effectively treating cancers, autoimmune diseases, spinal cord injuries and neurological disorders, among others. As cell therapies advance and have the potential to save more lives, researchers continue to refine cell culture production methods and processes to ensure the safety, efficiency and sterility of these products for use by patients.

The anomaly detection model developed by CAMP is a fast, label-free process analysis technology for detecting microbial contamination in cell cultures. The team’s research is explained in an oral summary”Process development and production: anomaly detection for microbial contamination in mesenchymal stromal cell culture“, recently published in the magazine Cytotherapy

The machine learning model was developed by first collecting sterile cell culture media samples from a series of MSC cultures with different culture conditions. Some of the collected samples were spiked with different bacterial strains in different colony forming units, a measurement of the estimated concentration of microorganisms in a test sample. The absorbance spectra of the sterile, non-speckled and bacteria-enriched samples were obtained by ultraviolet-visible spectrometry, and the spectra of the sterile samples were used to train the machine learning model. Testing the model with a mixture of sterile and bacteria-enriched samples demonstrated the performance of the model in accurately predicting sterility.

“The practical application of this discovery is enormous. Combined with ‘at-line’ technologies, the model can be used to continuously monitor cultures grown in bioreactors in Good Manufacturing Practice (GMP) facilities in-process,” said Shruthi Pandi Chelvam, lead author and research engineer at SMART CAMP who collaborated with Derrick Yong and Stacy Springs, principal investigators at SMART CAMP, to develop this method. “As a result, GMP facilities can perform sterility testing for bacteria in spent culture media faster with less manpower in closed loop operations. Finally, patients receiving cell therapy as part of their treatment can rest assured that products have been thoroughly evaluated for safety and sterility.”

During the cell therapy fabrication process, this anomaly detection model can be used to detect the presence of adventitious microbial contamination in cell cultures within minutes. This in-process method can help save time and resources, as contaminated cultures can be immediately discarded and reconstructed. This method provides a quick alternative to conventional sterility testing and other microbiological detection methods for bacteria, which often take several days to complete and are almost always performed on finished products.

“Our increased adoption of machine learning in microbial anomaly detection has enabled us to develop a unique assay that rapidly performs in-process contamination monitoring, marking a huge step forward in further streamlining the cell therapy manufacturing process. of the safety and sterility of cell products prior to infusion in patients, this method also provides cost and resource effectiveness for manufacturers, as it allows for a decisive batch restart and shutdown if the culture is contaminated,” adds Yie Hou Lee, scientific researcher director of SMART CAMP.

In the future, CAMP aims to develop an in-process monitoring pipeline in which this anomaly detection model can be integrated with some of the in-house at-line technologies being developed, which would enable periodic culture analysis using a bioreactor. This would open up the possibilities for further, long-term experimental studies in continuous culture monitoring.

Lead author Shruthi Pandi Chelvam also won the Early Stage Professionals Abstract Award, which is presented to three outstanding scientists, and abstracts are scored through a blinded peer-review process. The research was also accepted for oral presentation at the 2022 International Society for Cell and Gene Therapy (ISCT) conference, a prestigious event in the field of cell and gene therapies.

“This team-based, interdisciplinary approach to technology development that addresses critical bottlenecks in cell therapy manufacturing including rapid safety assessment enabling intermittent or at-line monitoring of plausible adventitious agent contamination is a hallmark of SMART CAMP’s research objectives,” added Krystyn Van Vliet of MIT, who is associate vice president for research, associate provost, professor of materials science and engineering, and co-lead of SMART CAMP with Hanry Yu, professor at the National University of Singapore.

The research is conducted by SMART and supported by the National Research Foundation (NRF) Singapore as part of its Campus for Research Excellence And Technological Enterprise (CREATE) program. The study collaborated with a team from the Integrated Manufacturing Program for Autologous Cell Therapy, one of its sister programs in the Singapore Cell Therapy Advanced Manufacturing Program, of which CAMP is a part, to help develop an automated sampling system. This technology would be integrated into the anomaly detection model.

CAMP is an interdisciplinary SMART research group launched in June 2019. It focuses on better ways of producing living cells as medicines, or cellular therapies, to give more patients access to promising and approved therapies. The CAMP researchers address two key bottlenecks in the production of a range of potential cell therapies: critical quality attributes (CQA) and process analysis technologies (PAT). Leveraging deep collaborations within Singapore and MIT in the United States, CAMP finds and demonstrates CQA/PAT capabilities from stem cells to immune cells. Her work focuses on conditions ranging from cancer to tissue degeneration, targeting adherent and floating cells, with and without genetic engineering.

CAMP is the R&D core of a comprehensive national cell therapy manufacturing effort in Singapore.

SMART was founded in 2007 by MIT in partnership with the NRF. SMART is the first entity in CREATE developed by NRF. SMART serves as an intellectual and innovation center for groundbreaking research interactions of interest to both MIT and Singapore. SMART currently consists of an Innovation Center and five IRGs: Antimicrobial Resistance (AMR), CAMP, Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP), Future Urban Mobility (FM) and Low Energy Electronic Systems (LEES).

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