Santosh Dhule , Eric Corriveau , Christopher Lepsy , Sophie Tourdot
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引用次数: 0
Abstract
Despite significant advances in instrumentation and robotics, the automation of cell staining in flow cytometry remains largely unaddressed. While sample acquisition in flow cytometry has been fully automated, sample staining continues to be a predominantly manual process—requiring substantial time, labor, and cost. Additionally, the repetitive nature of manual staining introduces monotony and increases the likelihood of human error. The Staining Triad presented here achieves full automation of the staining process, requiring only the input of samples and reagents, with no manual intervention. Staining performed using the Staining Triad showed a comparable biomarker profile to that of conventional manual staining. The modular and adaptable system design enables the flexibility to tailor throughput and accommodate assay-specific requirements, thereby extending its applicability to plate-based ligand binding assays. Moreover, the system eliminates the need for pipette tips, exemplifying a sophisticated and sustainable solution that enhances laboratory efficiency while reducing human error and the primary source of plastic waste in flow cytometry staining. Although 3R initiatives (Reduce, Reuse, Recycle) have helped decrease laboratory plastic waste volumes, substantial amounts are still incinerated or end up in landfills, where they persist in the environment for decades. This limitation underscores the need to incorporate a fourth R—"Remove/Replace"—into sustainability strategies. As flow cytometry becomes increasingly integral across various biotechnology disciplines, it is imperative to streamline associated workflows to accelerate drug discovery while preserving the environment that sustains life.
期刊介绍:
SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.