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].