Flow cytometry is one of the most advanced tools for cellular analysis, capable of delivering detailed quantitative measurements of cell number, fluorescence, and light scatter. But in most laboratories, its quantitative potential remains untapped.
Virginia Litwin, Ph.D., Director of Flow Cytometry at Eurofins Clinical Trial Solutions and President-elect of the International Society for the Advancement of Cytometry (ISAC), has a clear view of the problem: “In most cases the only thing we quantify is the number of cells.” Despite decades of progress—calibration beads, standardized dyes, and Systeme International (SI)-traceable reference fluorophores—results are still too often reported in arbitrary units.
In her presentation Flow Cytometry: A Quantitative Science! at the 2025 AAPS Summer Scientific Forum, Litwin outlined both the technical path forward and the cultural changes needed to make quantitative flow cytometry a reality.
Why Best Practices Lag Behind
Asked why many labs still resist implementing calibration and standardization, Litwin points to a fundamental cause: education. When flow cytometry shifted from analog to digital, the instrumentation gained capabilities for more precise, quantitative work. But users didn’t follow suit.
“People didn’t change their practices to fit the new technologies,” advises Litwin. Many researchers focus on their experimental goals without developing a deep understanding of the technology itself. In core facilities, she adds, staff may not always prioritize educating users on what’s necessary for optimal data quality. As a result, “people continue to do things the old way, although it may not be appropriate for newer instruments.”
Misconceptions About Quantitation
A key misconception is that quantitative rigor is only necessary in regulated environments, such as clinical trials. In reality, most contexts of use would benefit from quantitation. Litwin highlights longitudinal studies and multicenter trials, where instrument-to-instrument variation can undermine comparability.
Some researchers assume that because they operate in a “closed system” with one instrument, calibration is less critical. But Litwin emphasizes that science is not static. “I want my research findings in human biology to translate to a cure,” she remarks. “We want other people to be able to leverage that and take it to the next step.”
Litwin also recalls how differences in technology can change answers to scientific questions. Early in her career, she found her results refuted published work—not because the published results were flawed, but because the systems used to generate the original data were less sensitive than the system she was using, thus the results were not directly comparable.
Understanding the Data Spectrum
One of Litwin’s core messages is that bioanalytical data fall into clear categories:
- Definitive Quantitative – Continuous numerical data with a standard curve and reference standards.
- Relative Quantitative – Continuous numerical data with a standard curve but no reference standard.
- Quasi-Quantitative – Continuous numerical data without a standard curve.
- Qualitative – Categorical, non-numeric data.
Currently most flow cytometric assays report quasi-quantitative or qualitative data. While these data types have their place, reporting fluorescence intensity without calibration limits reproducibility and translatability.
Technical Pathways to Standardization
During her presentation, Litwin described multiple strategies for improving quantitative accuracy:
Instrument Standardization and Calibration
- Employing commercially available multi-intensity beads with Equivalent Reference Fluorophore (ERF) assigned SI-traceable values provided by the National Institute for Standards and Technology (NIST), for instrument and routine performance checks.
Antigen Quantitation
- Applying BD QuantiBrite PE beads with monoclonal antibodies conjugated at a 1:1 fluorophore-to-protein ratio for absolute quantitation.
- Recognizing that off-the-shelf antibodies can provide reproducible estimates, but definitive measurements require custom unimolar preparations.
- Avoiding direct comparison of medianfluorescence intensity (MdFI) across instruments without proper normalization, as MdFI values can vary widely.
Normalization for Assay Transfer
- Using ERF-based calibration, Litwin and collaborators have successfully transferred assays between different platforms while maintaining consistent expression levels.
Global Efforts Driving Change
Several major initiatives are tackling flow cytometry standardization from different angles:
- ISAC Quantitative Flow Cytometry Interest Group: Runs tutorials and workshops, publishes consensus recommendations, and fosters collaboration between academic, clinical, and industrial labs.
- NIST Flow Cytometry Standards Consortium: Develops calibration materials, reference standards, and interlaboratory studies to assess variability and refine best practices.
- CLSI Expert Panels: Produces consensus documents that guide assay validation, instrument performance, and cell enumeration.
- SOULCAP: A multinational collaboration to unify cell population nomenclature and standardize automated gating accuracy.
From Culture Shift to Routine Practice
Litwin believes that the shift to quantitative flow cytometry is as much cultural as it is technical. Researchers must see calibration and standardization not as regulatory burdens, but as essential steps in generating data that can be trusted, compared, and built upon.
“It’s not witchcraft. It’s not art. It’s science,” she says. “It needs to be standardized and quantitative.”