Secure Single-Use Consumables Emphasized for Bioprocessing
Secure, single-use consumables are gaining importance in automated and closed-system biomanufacturing, as shown in a recent FAQ on the Redipor® TwistLock system. The focus is on tamper-evident connections to minimize contamination risks in cell and gene therapy production. There is also an emerging demand for barcode or RFID-enabled consumables to allow for automatic tracking in electronic batch records.
- The aoption of single-use systems has seen significant growth, with an adoption rate of over 85% at the pre-commercial scale in the US; however, stainless steel bioreactors still dominate large-scale commercial manufacturing, accounting for 92% of bioreactors over 2,000L globally. - Electronic Batch Record (EBR) systems are critical for maintaining data integrity in GMP environments, as they provide automated audit trails, enforce contemporaneous data entry, and control access, addressing common FDA warning letter deficiencies related to batch records. - Digital twins are being implemented in bioprocessing to create virtual replicas of manufacturing processes, enabling in-silico process optimization and simulation which can de-risk technology transfer and predict the impact of process deviations on final product quality. - The global cell and gene therapy Contract Development and Manufacturing Organization (CDMO) market is projected to expand significantly, with forecasts predicting growth from approximately USD 6.31 billion in 2024 to over USD 74 billion by 2034, driven by the rising demand for specialized manufacturing expertise. - While single-use systems reduce capital costs and cleaning validation efforts, they introduce challenges related to leachables and extractables, supply chain reliability for consumables, and waste management that require careful consideration and validation. - Artificial intelligence and machine learning are being leveraged to accelerate the development of viral vectors by optimizing capsid design and manufacturing processes; for instance, machine learning models trained on GMP batch data have led to productivity increases of up to 50% by optimizing parameters like seeding densities. - Integrating the vast amounts of data from disparate sources in biomanufacturing presents significant challenges, including data fragmentation across different systems, lack of standardization, and the need for real-time processing to enable effective process monitoring and control. - The shift to single-use technologies can significantly shorten the timeline for building and validating new manufacturing facilities compared to traditional stainless-steel setups, which can take up to four years to become fully operational.
