Introduction:
This article discusses the advancements in artificial intelligence (AI) within the bioprocessing sector, particularly focusing on the growing maturity of AI-led manufacturing operations management (MOM) technologies. Highlighting insights from Quartic.ai, it emphasizes the integration of data systems and analytics that enhance operational efficiency and decision-making.
- The integration of data from various IT systems across the manufacturing enterprise is becoming more seamless, allowing for enhanced analytics and operational insights.
- Quartic.ai has observed an increase in mature use cases among its customers, demonstrating the scalability of its software across multiple manufacturing facilities.
- A case study is presented showcasing a customer that improved monoclonal antibody (mAb) yield through real-time monitoring and predictive analytics, showcasing the practical benefits of AI in bioprocessing.
- Clients are increasingly seeking to incorporate data from laboratory information management systems (LIMS) and enterprise resource planning (ERP) systems, extending the scope of data integration.
- Quartic.ai aims to facilitate the scaling of successful implementations from single sites to broader operational strategies across multiple plants.
Conclusion:
The advancements in AI and data integration in bioprocessing are indicative of an evolving landscape marked by enhanced efficiency and predictive capabilities. As companies like Quartic.ai continue to refine their technologies and expand their applications, the potential for significant improvements in operational performance and yield optimization across the industry will likely increase, paving the way for more informed decision-making and resource management in biomanufacturing.
