Digital biomanufacturing harnesses various advancements, such as real-time monitoring, data analytics, automation, modelling, process optimization and other digital tools to transform the available information into actionable insights.
This is expected to help in the creation of a uniform process, which is capable of decreasing the deviation in quality of each batch. Other key benefits of digital biomanufacturing include improved efficiency, higher product yield, better product quality, data integrity, reduced manual intervention and limited risk of contamination. It is worth noting that digitalization in biopharmaceutical manufacturing is becoming an essential requirement, given its potential to develop enhanced quality products, with high speed, agility and sustainability. Most of the PAT-based platforms engaged in digital biomanufacturing are capable of performing process automation (90%), followed by bioprocess optimization and controls (86%) and process connectivity solutions (81%).
The modernization of the biomanufacturing process has been more visible and successful as a result of the recent breakthroughs in the data analytics and data science. Innovative technologies, such as AI and digital twins, have become part of an important strategy for biopharmaceutical companies to future-proof their business operations and address various issues, including growing expenses, stringent regulatory guidelines and deteriorating profit margins. Considering the current market trends and innovation landscape, we anticipate that the next generation of machine learning technologies will be integrated with advanced data analytics, and process and equipment modeling to form comprehensive systems, for the purpose of real-time monitoring and predictive analysis. Further, digital bioprocessing is believed to have transformed manufacturing principles in areas, such as process development, operational activities, logistics and supply chain management, when used in combination with advanced technologies, including artificial intelligence (AI), machine learning and internet of things (IoT). Further, it is important to highlight that the digital biomanufacturing market for cell and gene therapies is anticipated to grow at a relatively faster pace.
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