INTRODUCTION
The biomanufacturing landscape has transformed recently, impacting labor demand, causing supply chain disruptions, and leading to persistent inflation. Workforce adaptations have led to productivity disruption and increased health concerns for those unable to work remotely. To stay competitive, innovation is crucial to adapt to the new norm and to introduce new products. Expediting the introduction of new products requires an understanding of critical product quality attributes, safety, efficacy, manufacturing, and logistics. Reliable data is essential for rapid development and speedy delivery to patients. As remote work is now part of business continuity, proactive data collection and analysis are needed for faster insights and value creation. An innovative analytical strategy is vital for building resilience and managing risks in manufacturing quality, addressing labor demand, and securing a competitive edge.
Analytical testing is frequently the critical path in the entire product manufacturing life cycle, often causing delays in product release due to long testing result turnaround times. In next-generation process development and manufacturing, real-time or near real-time analytics are crucial to streamline QbD development through assay automation, data visualization, and predictive modeling. This approach enables attribute-focused development, robust manufacturing processes, and rapid, yet reliable, process control and product release.
In developing an analytical strategy, automated systems aim to enable routine and on-demand acquisition of key product quality and process performance attributes in laboratories and manufacturing facilities. The proposed autonomous PAT platform offers 24/7 monitoring, reliable performance, and resource agility, as opposed to traditional analytical approaches which require significant analyst intervention. Carefully designed fluidic conduits and strategically placed material handling mechanisms provide resource conservation, optimized assay efficiency, controlled conditions, reproducible results, and long-term system robustness. The system contains multiple functional unit operations, working together through programmable algorithms to manage sample and reagent logistics, direct processes, and reactions, and enable self-directed assay protocol selection with rule-based parameter adjustment for optimal output.
Drawing inspiration from next-generation manufacturing and the Industry 4.0 concept, analytical testing is being moved from laboratories to the manufacturing floor. This paradigm shift enables in-situ testing for faster results, improved process understanding, and greater cost-effectiveness in process development and manufacturing [Ref. 1]. Sample acquisition and preparation workflows are typically prone to errors due to manual operations. Meanwhile, liquid handlers require substantial initial investment, extensive development, and can be costly to adapt to new requirements. Chip-based fluidic miniaturization serves as another option, offering advantages such as low material consumption, design freedom, and rapid analysis [Ref. 2].
Portability is another advantage of chip-based analytical systems, allowing the co-location of the manufacturing process and analytical instrument. This eliminates delays related to sample logistics and laboratory testing. However, minimizing sample and reagent consumption to the nanoliter or lower range on a microfabricated scale can introduce sampling errors, analysis errors through evaporation, and assay errors due to the precipitation of solids.
Instead, designing a compact and robust instrument that reduces sample and reagent consumption to a few microliters is more advantageous. These factors have led to a practical level of miniaturization through the integrated µSI fluidic design. This design maintains short fluidic conduit geometry instead of narrow ones, decreasing sample and reagent consumption without the inherent issues of microfabricated fluidic channels [Ref. 3].