Opportunity

SAM #75N98026Q00590

NIH OLAO Solicitation for Agilent NovoCyte Advanteon Flow Cytometer

Buyer

NIH Office of Logistics and Acquisition Operations

Posted

June 10, 2026

Respond By

June 22, 2026

Identifier

75N98026Q00590

NAICS

334516, 423490

The National Institutes of Health Office of Logistics and Acquisition Operations (NIH OLAO), under the Department of Health and Human Services, is seeking to acquire advanced laboratory equipment for cellular analysis. - Government Buyer: - Department of Health and Human Services (HHS) - National Institutes of Health (NIH) - Office of Logistics and Acquisition Operations (OLAO) - OEM Highlight: - Agilent is the specified Original Equipment Manufacturer (OEM) - Products/Services Requested: - Agilent NovoCyte Advanteon Flow Cytometer - Benchtop system for high-parameter cellular analysis - Designed for research and clinical laboratory use - Features flexible hardware configurations and automated data acquisition/analysis - No specific part number or quantity provided - Notable Requirements: - Instrument will support research on gene regulation and disease mechanisms - Emphasis on advanced capabilities to improve experimental throughput - No unique administrative or procedural requirements specified

Description

The NovoCyte Advanteon Flow Cytometer is a benchtop system designed for high-parameter cellular analysis in research and clinical laboratory settings. It is an advanced platform for multicolor flow cytometry that combines flexible hardware configurations with automated data acquisition and analysis capabilities.  The Section on Regulatory Ribonucleic Acids conducts research on the regulation of gene expression by ribonucleic acid binding proteins and micro ribonucleic acids. These studies are critical to understanding how gene regulation is disrupted in diseases such as cancer, hearing loss, and diabetes. Understanding these processes supports the development of new therapeutic approaches.  Acquisition of the NovoCyte Advanteon Flow Cytometer will significantly increase experimental throughput and improve the efficiency of research workflows supporting these projects.

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