AI-Driven UV Technique Provides Rapid Contamination Checks for Cell Cultures Researchers have developed a new artificial intelligence (AI)-based ultraviolet (UV) technology that can detect and monitor microbial contamination in cell therapy products (CTPs) quickly and automatically during the production process. This advance significantly enhances the efficiency of contamination checks, which are crucial for maintaining the quality and safety of these products. Traditional contamination detection methods are often time-consuming and require manual intervention, potentially leading to delays and quality issues. The new AI-driven UV technique, however, offers a faster and more automated alternative, reducing the risk of human error and improving overall process reliability. The technology works by using UV light to illuminate cell cultures. AI algorithms then analyze the images captured under UV illumination, distinguishing between contaminants and normal cells. This entire process can be completed in just a few minutes, compared to the several days or more that traditional methods typically require. According to the research team, this innovative approach can detect contamination at an early stage, providing timely alerts to production and quality control personnel. By identifying issues early, the technology helps prevent the spread of contamination, saving both time and resources. Additionally, the enhanced accuracy and reliability of the detection method contribute to the safety and efficacy of cell therapy products. The team is currently conducting further tests and optimizations to ensure the technology's readiness for practical application in production environments. They aim to integrate this method into the manufacturing process as soon as possible to improve the quality of cell therapy products. This breakthrough has the potential to revolutionize the cell therapy industry by boosting production efficiency and ensuring patient safety.