The reliability and interpretability of flow cytometry data depend heavily on pre-analytical workflows, which remain largely manual in many labs. The variability introduced can delay results, limit standardization and scalability, drive up labor and reagent costs through repeat work, and compromise regulatory compliance. These challenges are especially pronounced with complex samples. Whole blood, for example, contains a diverse range of cell types and interfering substances, such as red blood cells, that can obscure signals and distort results.
Standardizing these workflows is essential for generating reproducible, high-quality data. Right-sized automation, which tailors solutions to the lab’s specific needs, offers a practical way to reduce variability while improving throughput and cost efficiency. By supporting scalability, standardization, and flexibility, these approaches help labs meet the growing demands of biomarker research. This resource guide outlines key strategies for implementing automation, optimizing both pre-analytical and analytical workflows, and aligning flow cytometry assays with regulatory expectations.
Download this resource guide to explore:
How pre-analytical variability affects the reliability of immune monitoring assays
Where and how automation can improve biomarker assay validation, including reproducibility, compliance, and throughput
The value of right-sized automation for resolving workflow bottlenecks across translational and clinical lab settings
Tips for mitigating spillover and carryover artifacts in spectral flow cytometry
How automated sample preparation and modular panel design support scalability, standardization, and CLIA and CAP certification
