Program

Navigating SRL Recognition: How to Prepare Your Application

Grand Ballroom

Jessica Prieto-Chavez, MSc, Co-Coordinator of the Cytometry Network of the Health Research Coordination, Mexican Social Security Institute (IMSS)
Orla Maguire, PhD, Assistant Director, Flow and Immune Analysis Shared Resource, Roswell Park Comprehensive Cancer Center
Matilda Moström, PhD, Assistant Director, Flow Cytometry Core, Tulane National Primate Research Center
Eva Orlowski-Oliver, SCYM, Research Flow Core Manager, Peter McCallum Cancer Centre

The ISAC SRL Recognition Program is a cornerstone initiative to promote quality, reproducibility, and sustainability in shared resource laboratories (SRLs). As participation grows worldwide, many applicants seek clearer guidance on how to prepare strong, well-documented submissions.

This tutorial provides practical, evidence-based insights drawn from real applicant experiences and reviewer feedback. Presenters will highlight common challenges encountered during the Recognition process, typical strengths and weaknesses observed in evaluation reports, and concrete strategies that have helped SRLs achieve success.

Through presentations and an interactive discussion, participants will learn how to:
Interpret ISAC’s expectations at each application stage.
Identify internal documentation and quality practices most valued by reviewers.
Avoid frequent pitfalls that delay or weaken submissions.
Apply lessons learned from recognized SRLs of different sizes and organizational structures.
Recognize the tangible and long-term benefits of applying for SRL Recognition — including improved documentation, standardized procedures, and enhanced visibility within the community.

Ultimately, attendees will leave with a clearer understanding of how to plan, structure, and execute their SRL Recognition applications—while also strengthening their lab’s internal processes and culture of continuous improvement.

Learning Objectives:
Describe the structure and evaluation criteria of the ISAC SRL Recognition process.
Recognize common challenges and recurring feedback themes from reviewer reports.
Apply proven strategies and documentation practices that strengthen an SRL Recognition application.
Evaluate their own lab’s readiness and identify steps for sustained quality development beyond application submission.

Panel Gains Without the Pains: Smarter Re-Optimization for High-Parameter Flow

Ballroom A

Diana L. Bonilla Escobar, PhD, Scientific Director, Cytek Biosciences
Kamila Czechowska, PhD, Chief Diagnostic Product Development Officer, Metafora Biosystems
Megan McCausland, BSc, Scientific Advisor, Flow Cytometry, IQVIA Laboratories
Veronica Nash, PhD, Director of Flow Cytometry (Cellular Biomarkers), GSK

Assay optimization is essential for achieving reproducible and accurate results in multicolor flow cytometry. Recent advancements in cytometer hardware and fluorochrome chemistries, coupled with the ability to use an expanded number of fluorophores simultaneously, have enabled highly multiparametric assays. These capabilities create opportunities to re-optimize existing panels by adding new markers to gain deeper insights, without compromising resolution or data quality. However, expanding an optimized and/or validated panel is often challenging. Issues such as reagent availability, clone specificity, titer adjustments, and performance variability must be addressed, alongside technical problems like steric hindrance, reagent interactions, and increased spillover spreading. These challenges underscore the need for clear guidance when modifying complex panels. This tutorial will outline a structured approach for re-optimizing previously optimized and/or validated assays, including strategies for selecting optimal fluorochrome replacements or additions, evaluating reagent compatibility, and maintaining optimal resolution across all parameters in an expanded panel. We will walk through real case examples showing how updated panels were revalidated to ensure comparable marker performance, consistent population resolution, and robust identification of all relevant cell subsets after adding new markers. In these examples, careful panel redesign and iterative testing preserved data integrity even as dimensionality increased. Based on these findings, we will propose a practical workflow and a set of best-practice guidelines for panel expansion and re-optimization. This “panel expansion” workflow will serve as a template that participants can apply in their own labs – an increasingly important skill as new fluorochromes and next-generation instruments continue to push the boundaries of high-dimensional flow cytometry.

Current tools for cross-platform flow cytometry standardization utilizing quantitative units

Ballroom B

Vera Tang, PhD, Facility Manager & Adjunct Professor, University of Ottawa
Joshua Welsh, PhD, Staff Scientist, BD Biosciences

Problem Focus/Summary: Standardization of flow cytometry data reporting is necessary for reproducibility irrespective of the sample type across flow cytometry platforms. Cross-platform standardization as a topic is becoming increasingly important in both clinical and academic research settings. Fluorescence quantification is a method used to standardize reporting of flow cytometry data, making intra- and inter-platform comparisons possible. These are published methods, but there are currently a multitude of tools available for fluorescence standardization. In this tutorial we will identify the different tiers of standardization and then provide practical guidance on the tools necessary to achieve these different levels of standardization.

Goals: The purpose of this tutorial is to provide insight and guidance towards selecting methods and materials for fluorescence quantification, aiming to address specific standardization goals, and provide options to achieve concordance in standardized data reporting.

What this Tutorial will not do: Cover pre-acquisition variables – sample isolation/processing, staining optimization, panel design.

Learning Objectives:
To understand the different tiers of flow cytometer assay standardization from longitudinal single instrument studies to cross-platform comparison studies.
To understand the nuance in definitions for fluorescence quantification, calibration, normalization, and standardization.
To understand the practical differences between each of the fluorescence calibration units available, including cost, consistency, and ergonomics.
To demonstrate the impact of different fluorescence units on concordance in comparing cross-platform data, i.e. ERF, MESF, and ABC.

Meta Logical: Structuring Your Cytometry Data for Cleaner Models and Clearer Insights

Ballroom C

Arielle Ginsberg, MSc, SCYM, CEO, terraFlow
Ryan Duggan, BS, Principal Research Scientist, Abbvie

With the increasing volume and complexity of data in cytometry and related research fields, metadata has become essential for ensuring data quality, reproducibility, and utility across studies and modalities. Additionally, well annotated metadata is crucial for single-cell based large language models (LLMs) as it provides an AI-ready structure to the data, enhances data organization, and improves the model’s ability to interpret. In parallel, well annotated data allows it to provide maximal impact by being FAIR (Findable, Accessible, Interoperable, and Reusable)—principles that maximize data’s scientific value by ensuring it can be efficiently shared, understood, and repurposed across studies.

However, current practices for metadata management often fall short due to lack of standardization, inadequate tools, and limited awareness of best practices. This tutorial will provide participants with practical guidance for improving metadata organization, standardization, and documentation to support FAIR and AI-ready data practices. Drawing from established frameworks such as MIFlowCyt, SOULCAP, and data-sharing resources like ImmPort, the session will illustrate how cytometry researchers can align with broader community standards while enhancing reproducibility and downstream analytical potential.

Through a primarily didactic format with opportunities for open discussion and Q&A, participants will gain actionable strategies to improve metadata quality and foster a culture of data interoperability and long-term reusability within their research environments as well as opportunities to share successful strategies for overcoming challenges to implementation of FAIR data practices.

By the end of this tutorial, participants will be able to:
Define the principles of AI-ready and FAIR metadata in the context of cytometry data management.
Identify common challenges and barriers to implementing standardized metadata practices.
Apply FAIR and MIFlowCyt-aligned strategies to enhance data discoverability, reproducibility, and interoperability. Evaluate current metadata workflows for compliance with FAIR principles and opportunities for improvement.
Formulate an actionable plan to integrate AI-ready and FAIR-compliant metadata practices within their research or core facility.

Session Format (55 Minutes Total)
5 min: Introduction – Why Metadata Matters in Cytometry
Overview of metadata types and their role in data quality, reproducibility, and AI model performance.
15 min: Building AI-Ready and FAIR Metadata
ey principles of FAIR data; aligning metadata with existing cytometry standards (MIFlowCyt, SOULCAP); examples from genomics and imaging.
15 min: Practical Implementation and Case Studies
eal-world examples of metadata templates, data integration workflows, and successful FAIR applications in cytometry.
5 min: Overcoming Barriers
Addressing organizational and technical challenges to FAIR adoption; resources and tools.
15 min: Q&A and Discussion
Open discussion for participants to reflect on challenges and opportunities within their institutions.

Expected Outcomes
Participants will leave with a clear understanding of how to structure metadata to support FAIR data principles and AI-ready analyses, along with practical strategies to promote data standardization and interoperability within their research environment

Decoding CAR T Dynamics: Flow Cytometry–Driven Insights from Autologous and Allogeneic Trials

Meeting Room 2F

Nithianandan Selliah, PhD, Global Director Flow cytometry, Cerba Research

Chimeric Antigen Receptor T-cell (CAR T) therapy has revolutionized the treatment of hematologic malignancies and is showing increasing promise in solid tumors. Both autologous and allogeneic CAR T-cell products are now advancing through clinical trials and therapeutic use. CAR T cells are genetically engineered T cells that express a chimeric antigen receptor (CAR), which recognizes a specific antigen on tumor cells, thereby redirecting immune specificity and enhancing cytotoxicity. This tutorial provides a foundational overview of CAR T trial design, emphasizing the critical role of flow cytometry in monitoring CAR T-cell kinetics, persistence, and immunophenotypic changes in patients.

Autologous CAR T cells are patient-derived genetically modified T cells, whereas allogeneic CAR T cells are healthy donor-derived genetically modified T cells. While autologous CAR T cells minimize immune rejection, they face challenges in manufacturing time, product variability, and cell quality in heavily pretreated patients. Conversely, allogeneic CAR T cells offer “off-the-shelf” scalability without treatment delay, but pose risks of graft-versus-host disease (GvHD) and host immune rejection. These differences necessitate distinct flow cytometric strategies for product validation and patient monitoring.

Flow cytometry remains the gold standard for tracking CAR T-cell expansion, persistence, and phenotype during clinical evaluation. The tutorial outlines essential gating strategies for accurate identification of CAR T populations. In autologous trials, CAR⁺CD3⁺ cells are identified within the patient’s T-cell compartment using CAR-specific antibodies. However, in allogeneic CAR T trials, where TCRαβ is knocked out and CD3 expression is absent, CAR⁺ cells must be detected within the CD3⁻ compartment, requiring alternative gating and additional markers. Initial gating involves selecting singlets and viable lymphocytes via forward and side scatter, excluding dead cells with viability dyes, and identifying CD3⁺ and CD3⁻ populations. CAR expression is confirmed using reagents such as fluorochrome-labeled anti-idiotype antibodies, Protein L, or construct-incorporated tags (e.g., EGFRt, truncated CD19). In allogeneic trials, correctly distinguishing CAR⁺CD3⁻ cells from host immune cells is critical.

A unique challenge in allogeneic CAR T studies is the standard TBNK (T-cell, B-cell, NK-cell) assay’s limitation in accurately enumerating NK cells. In these patients, the CD3⁻ compartment includes CD19⁺ B cells, CD16/56⁺ NK cells, and CAR⁺ T cells. We present alternative panel design and a modified gating strategy to properly distinguish host NK cells from CD3- CAR T-cells that possibly express CD56 upon activation.

Flow cytometry’s strengths—high sensitivity, multiparametric resolution, and simultaneous assessment of activation, exhaustion, and memory phenotypes—make it indispensable in CAR T trials. This tutorial equips researchers and clinical scientists with practical, technology-focused guidance for standardized flow cytometric analysis, enabling accurate immune monitoring, data harmonization, and informed therapeutic assessment.

By the end of the session, participants will gain actionable insights into assay design, gating logic, and troubleshooting for both autologous and allogeneic CAR-T trials, enhancing precision in immune monitoring and data interpretation across clinical and research settings.

Learning Objectives By the end of this tutorial, participants will be able to:
1. Differentiate between autologous and allogeneic CAR T-cell products and understand how their biological and manufacturing differences influence flow cytometry–based monitoring strategies.
2. Design and optimize flow cytometry panels for the detection and characterization of CAR T cells in patients with autologous and allogenic trials, including appropriate marker selection and reagent use (e.g., Protein L, anti-idiotype antibodies, tag-based detection).
3. Apply appropriate gating strategies to accurately identify CAR T-cell populations in both CD3⁺ (autologous) and CD3⁻ (allogeneic, TCR-knockout) compartments while minimizing misclassification and background signal.
4. Recognize challenges in standard immunophenotyping assays (e.g., TBNK panels) when analyzing samples from patients treated with allogeneic CAR T and implement modified gating and marker strategies to improve NK-cell enumeration.
5. Interpret CAR T-cell flow cytometry data to assess expansion, persistence, activation, and exhaustion phenotypes, supporting standardized immune monitoring and harmonized data analysis in clinical trials.

Approaches to Spectral Unmixing Challenges, journey of a detective

Grand Ballroom

Sara Garcia-Garcia, MSc, Technical Director, Microscopy and Flow Cytometry Facility, Amsterdam UMC
Laura Ferrer Font, PhD, Scientific Solutions Manager, BD Biosciences

Spectral flow cytometry has revolutionized multiparametric cellular analysis by enabling the simultaneous detection of a large number of fluorochromes. However, the complexity of spectral data introduces unique challenges, particularly in the unmixing process. Accurate spectral unmixing is critical to distinguish overlapping emission spectra and ensure reliable data interpretation. Common issues include autofluorescence interference, spillover between fluorochromes, and suboptimal reference controls. This session will address practical troubleshooting strategies, highlight common pitfalls, and provide guidance on optimizing panel design and unmixing workflows to enhance data quality and reproducibility.

We suggest presenting a dynamic tutorial focused on spectral flow cytometry most common panel design and unmixing challenges. Our approach involves four case studies, each based on real-world data collected from different spectral instruments.

Suggested Tutorial Abstract:
Do you have what it takes to become a spectral detective? Are you tired of those unresolvable unmixing mysteries that keep haunting your plots? Grab your trench coat and magnifying glass, because two seasoned investigators are on the case, and they want you on the team. Each case hides clues about spectral unmixing challenges, and your mission is to uncover the truth.

Which will be your role? Analyze evidence, apply your unmixing skills, and solve the cases step by step. By the end, you’ll have the tools and confidence to tackle even the most stubborn spectral mysteries.

With a mix of hard-boiled humor and cytometric wisdom, we’ll expose the good, the bad, and the ugly of spectral unmixing. Because in spectral cytometry, every photon leaves a trace, and every bad design leaves a body (of messy data). Join us on an investigative adventure where science meets mystery!

Learning Objectives:
- Recognize common pitfalls in spectral panel design and why some fluorochrome choices can never be 'resolved'.
- Understand how single-stain control errors (e.g., spectral signatures mismatch or AF mismatches) impact unmixing quality.
- Learn strategies for dealing with autofluorescence.
- Develop practical troubleshooting skills to spot, diagnose, and solve spectral unmixing issues.
- Recognise best practices to make unmixing reproducible across experiments.

Challenging Sample Types in SRL Cores: From Biomedical to Environmental Cytometry

Ballroom A

Nicole Poulton, PhD, Senior Research Scientist, Bigelow Laboratory for Ocean Sciences
Attila Bebes, PhD, Experimental Officer, University of Exeter
Raif Yuecel, PhD, Director, Centre for Life Sciences Technologies (CLST) and Research Director, Exeter Centre for Cytomics (EXCC), University of Exeter

In Shared Resource Laboratories (SRLs) we are often faced with challenging samples that can be difficult to prepare and analyze. In a biomedical research setting these could be fragile subcellular organelles, such as nuclei, mitochondria or peroxisomes, as well as debris-rich suspensions ranging from tissue digests to insect hemolymph. Environmental samples can vary from aquatic sources containing plankton, bacteria and viruses to complex sediment samples or snail mucin. Each of these samples presents unique challenges to the SRL cytometrist.

In this tutorial, we will share practical workflows and lessons learned from working with both biomedical and environmental samples within our respective SRLs. The session will offer general strategies, step-by-step guidance, and case studies covering examples such as tissue dissociation (mechanical and enzymatic), planktonic community profiling and genomic sizing of amphipods to help participants approach challenging samples with confidence and reproducibility.

This tutorial fits the Scientific Track on SRL Practices and Applications and is designed to provide attendees with evidence-based, didactic guidance on handling non-standard samples, combining best practices from clinical, research, and environmental cytometry.

Learning objectives:
Sample preparation strategies spanning organelles to sediments.
Instrument selection and setup to achieve optimal data quality.
Common artifacts and how to prevent or recognize them.

After attending this tutorial, participants should be able to:
Recognize the major physical and biological challenges associated with complex biomedical (e.g., tissue-derived, organelle, or primary cell) and environmental (e.g., aquatic, sedimentary, or microbial) samples.
Apply evidence-based preparation methods to minimize debris and aggregation, and to handle autofluorescence that may compromise cytometry data quality.
Optimize instrument configuration and quality control for non-standard particle sizes and signal ranges across cytometers (both conventional and spectral).
Implement validated workflows and safety practices to ensure reproducible results in SRL environments that deal with heterogeneous or high-risk samples.
Integrate lessons learned from biomedical and environmental workflows to expand SRL support capabilities and cross-disciplinary collaboration.

From tissue to single cells: A hands-on guide in tissue dissociation and single-cell preparation for clinical and experimental flow cytometry research applications

Ballroom B

Charunya Nanayakkara, PhD, Senior Lecturer (Grade II), University of Sri Jayewardenepura, Nugegoda, Sri Lanka

A critical step in using flow cytometry for phenotypic and functional profiling of immune, stromal, and parenchymal cells from solid organs is converting intact tissue into viable single-cell suspensions while preserving key surface markers and avoiding artefactual activation. This tutorial, based on validated and published protocols, offers a comprehensive guide for flow cytometry users of all levels to select and implement evidence-based approaches compatible with high-parameter flow cytometry and related single-cell analyses across a wide range of tissues, including heart, lung, liver, spleen, lymph nodes, bone marrow, thymus, kidney, colon, skin, brain, adipose tissue, placenta/foetal tissue, and solid tumours. By the end of the tutorial, participants will understand the fundamental principles of tissue dissociation, tissue-specific methodological adaptations, and essential quality control considerations in both experimental and clinical contexts.

Learning Objectives
· Understand the biochemical and mechanical principles underlying tissue dissociation for flow cytometry.
· Differentiate between experimental (animal) and clinical (human) tissue processing workflows.
· Identify representative published protocols for major organs and match them to their research question and cell‑type target.
· Recognize technical variables that influence viability, antigen preservation, and reproducibility in single‑cell suspensions.
· Integrate tissue‑processing decisions into downstream multiparameter flow cytometric or single‑cell workflows.

Key Steps for Assay Standardization across Cytometer Platforms

Ballroom C

Lili Wang, PhD, Senior Scientist, National Institute of Standards and Technology (NIST)
Huan-Yu (Ray) Chen, PhD, post-doctoral researcher, National Tsing Hua University
Paul DeRose, PhD, physical/analytical chemist, NIST
Yu-Fen (Andrea) Wang, MS, cofounder and CEO, AHEAD Medicine Corporation

This tutorial will address the critical need for comparable and standardized data in flow cytometry, a challenge that the NIST Flow Cytometry Standards Consortium (FCSC) Working Group 2 (WG2) tackled with its first Interlaboratory Study (ILS). The study focused on a 10-marker, 8-color T/B/Monocyte/Natural Killer (TBMNK) cell assay—to establish measurement confidence across diverse instruments. The ILS involved 21 sites and 42 different cytometer platforms (including conventional, spectral, and imaging types) from 7 instrument companies, utilizing cryopreserved peripheral blood mononuclear cells (PBMC) and TruCytes TBMNK synthetic cells serving as QC samples.

In this tutorial, we will detail the study's framework by walking through the four SOPs developed for the ILS:
WG2 SOP-01: Designated for instrument set up, calibration and characterization
WG2 SOP-02: Preparation and acquisition of three compensation matrices with one cell-based and two bead-based matrices
WG2 SOP-03: Preparation and acquisition of study samples as well as various assay controls, including fluorescence minus one (FMO) controls
WG2 SOP-04: Data analysis and result reporting

Finally, we will present the study data quality control criteria and the key summary of data analysis from manual analysis by participants and centralized automated analysis pipeline. The tutorial will conclude with practical instructions on how to navigate the interactive site that provides all the results from this comprehensive ILS study.

Excellence and Integrity in Cytometry Publishing: A Guide for Authors, Reviewers, and Associate Editors

Meeting Room 2C

Bartek Rajwa, PhD, Editor-in-Chief, Cytometry Part A

For over 40 years, Cytometry Part A – The Journal of Quantitative Cell Science has been the home for innovative research in single-cell analysis, publishing peer-reviewed studies on measurement, separation, manipulation, engineering, and modeling of cells. The journal also covers high-content screening and the molecular mechanisms underlying cellular function. As the field continues to evolve, Cytometry A remains committed to advancing quantitative cell biology and supporting the development of cutting-edge methods for cellular systems analysis.

At the same time, scientific publishing is undergoing rapid changes. The rise of open access, the growth of semi-predatory publishers, the demand for faster review cycles, and the popularity of preprints are reshaping how we share scientific knowledge. These shifts present both challenges and opportunities for Cytometry A. In response, we are expanding our editorial board, strengthening peer review, and broadening our scope to encompass emerging areas such as high-content screening and single-cell omics.

By participating in this tutorial, attendees will be able to:
· Understand and navigate the peer review process for Cytometry Part A, including the workflow from submission to decision, time expectations for reviewers and Associate Editors, and how to craft constructive reviews that strengthen manuscripts.
· Apply statistical rigor and data quality standards expected for publication, including proper analysis of cytometry data, avoiding common statistical pitfalls, and implementing FAIR data principles with appropriate use of RRIDs and data sharing practices.
· Evaluate manuscript quality and publication readiness, understanding what distinguishes strong submissions from those likely to be rejected, technical requirements for figures and supplementary data, and how to assess scientific impact, novelty, and significance.
· Recognize the role and value of OMIP (Optimized Multicolor Immunofluorescence Panel) publications, understanding how these standardized, validated panel descriptions advance reproducibility and serve as community resources for researchers designing multi-parameter cytometry experiments.

Content
· This tutorial will reintroduce Cytometry A to the ISAC community and explain how members can contribute as reviewers and Associate Editors. We'll examine the practical mechanics of peer review: manuscript evaluation workflow, timelines, time commitments, and how to write constructive, actionable reviews. We'll provide guidance on what distinguishes strong submissions from desk rejections, technical requirements for figures and data files, and when manuscripts are appropriate for Cytometry Part Aversus Part B.
· A special focus will be placed on OMIP papers, which document fully validated, ready-to-use multi-parameter panels complete with reagent details, compensation strategies, and gating schemes. OMIPs serve as essential community resources that promote standardization, reproducibility, and facilitate the adoption of complex cytometry approaches. We'll discuss the criteria for OMIP submissions and how these papers differ from standard research articles.
· We'll address critical research ethics issues: identifying and managing conflicts of interest, authorship disputes, image manipulation policies, and recognizing red flags for paper mills and data fraud that threaten the peer review system.
· We'll also discuss the professional development benefits of serving as a reviewer or Associate Editor: career enhancement, networking opportunities, staying current with emerging methods, and contributing to the scientific community.
· Statistical analysis and data representation remain critical areas where submissions often fall short. We'll review common statistical mistakes in cytometry data, including understanding of spectral unmixing, compositional data analysis issues, multiple testing corrections, and appropriate controls. We'll cover standards for reporting statistical methods, data visualization best practices, high-dimensional data representation, validation approaches for computational analyses, and transparency in parameter selection.
· Finally, we'll explain how the journal supports FAIR data principles through policies on Research Resource Identifiers (RRIDs), code availability, and data deposition. Throughout the tutorial, we'll emphasize the journal's commitment to scientific impact, novelty, and significance, and welcome questions about any aspect of the submission, review, or editorial process.

How to develop and implement a biosafety plan for a cytometry lab

Meeting Room 2F

Sherry Thornton, PhD, Professor, Cincinnati Children's Hospital
Evan Jellison, PhD, Associate Professor & Director of Flow Cytometry, UCONN School of Medicine
Jessica Back, PhD, Director of Research Cores and Director, Microscopy, Imaging and Cytometry Resources (MICR) Core, Karmanos Cancer Institute/Wayne State University
Kristen Reifel, PhD, Independent Consultant, KMR Scientific

Purpose: This tutorial will provide guidance on how to develop and implement a biosafety plan with an in-depth focus on risk assessment.

Summary: The biosafety plan contains essential information regarding the risks of working with biological samples, including the use of specific instrumentation, and the steps that should be taken to mitigate these risks. Risk assessment is a critical component of biosafety where the likelihood of occurrence of an undesirable incident (e.g., exposure to infectious samples) and the consequences if that incident were to occur (e.g., infection or disease) are determined. Establishment of a biosafety plan for a cytometry lab, especially a flow cytometry shared resource laboratory (SRL), can be a daunting task as projects often involve a diverse variety of pathogens that may change over time. The biosafety plan should integrate and synthesize information necessary to safely handle these pathogens determined through a risk assessment. Having a plan that can adapt to a variety of pathogens will provide a framework for addressing concerns and educating personnel and users with variable experience levels on biosafety practices. Key to generating an effective biosafety plan is identifying and using available resources, as well as developing a robust relationship with health and safety personnel at your institution. In this tutorial we will provide the basic underlying structure of a biosafety plan and discuss how the risk assessment process is incorporated into the biosafety plan.

Learning objectives:
· How to develop a biosafety plan using the risk assessment process that can accommodate changing pathogens.
· How to assess biological risks related to cytometric evaluation.
· How to implement an effective biosafety plan and address potential changing variables.

Crimes Against Data Analysis

Grand Ballroom

Sarah Bonte, PhD, Postdoctoral Researcher, VIB-Ghent University
Geoffrey Kraker, BSc, Senior Application Specialist, Dotmatics
Givanna Putri, PhD, Postdoctoral Researcher, Walter Eliza Hall Institute of Medical Research
Nicolas Loof, MSc, Informatics Solution Leader, BD/FlowJo

High parameter cytometry technologies enable simultaneous characterization of many cellular markers, offering unprecendented insights into complex biological systems. As panel sizes and complexities continue to expand with advances in instruments and reagents, our capacity to analyze data has not kept pace, making high-dimensional data increasingly challenging to interpret. While data analysis tools are becoming more sophisticated and accessible, whether through programming platforms or commercial software plugins, longstanding issues with data quality remain a significant barrier. These are further compounded by artifacts introduced during data processing, which can lead to erroneous interpretations. Yet, clear guidance on how to recognize, diagnose, and mitigate them is still lacking.

This tutorial will provide strategic and tactical approaches for identifying and troubleshooting common data quality issues and artifacts in cytometry data, showing both their causes and effects. Most commonly used algorithms for high-dimensional data analysis will be covered, along with guidelines for parameter settings for each.

Learning objectives:
Having an idea of the output of computational algorithms when there are no/minimal problems with data quality and no artifacts introduced during data analysis ("What it should look like")
Recognizing artifacts introduced by data analysis and/or data quality issues ("What it looks like if you don't do it right")
Knowing what to do to prevent these artifacts from occurring
Understanding parameter choices in commonly used computational algorithms for high-dimensional data analysis
Guidelines on how to pick the most optimal parameters for your data, and diagnose when you have picked the wrong ones

Minimum standards and best practices to ensure reproducibility in longitudinal flow cytometry studies

Ballroom A

Kathryn Hally, PhD, Senior Lecturer, University of Otago Wellington (Ōtākou Whakaihu Waka ki Pōneke)
Ana Longhini, PhD, Global Scientific Affairs Senior Manager, Sony Biotechnology Inc
Laura Ferrer Font, PhD, Scientific Solutions Manager, BD Biosciences
Megan McCausland, BSc, Scientific Advisor, Flow Cytometry, IQVIA Laboratories
Sam Small, Other, Senior Specialist, Flow Cytometry, Malaghan Institute of Medical Research

Highly reproducible flow cytometry assays are essential for generating robust data in longitudinal studies. These studies offer powerful insights into disease progression, treatment response, and immune dynamics. Their inherent complexity, however, demands meticulous planning and execution to ensure consistency across timepoints, instruments, operators and sites. Other critical factors - including accounting for batch effects, reagent performance, and sample handling and storage - also require tight control to reduce their impact on the integrity of cells or markers of interest. Further, as cytometry technologies continue to evolve, researchers are designing higher dimensional panels, integrating data from multiple instruments and sites, and using sophisticated analytical approaches; while promising, these advancements introduce new challenges for reproducibility. Notably, longitudinal study design is not one-size-fits-all; these must be tailored to the users’ expertise, resources, and the assay’s intended use.

To better address the challenges of executing longitudinal flow cytometry studies, we conducted two community surveys and organized two workshops at CYTO2024 and CYTO2025. Our objective was to gather diverse perspectives from the cytometry community and collaboratively define, in alignment with published guidance, a set of minimum requirements and best practices to support reproducibility in longitudinal studies. We explored critical elements such as assay validation, antibody and reagent lot control, ensuring consistent instrument performance, the necessity of an assay-specific quality control, and considerations for data analysis. In this tutorial, we will present this framework and highlight how adherence can significantly enhance assay reliability and interpretability in longitudinal flow cytometry studies.

Learning objectives:
Identify the key challenges involved in planning and executing a longitudinal flow cytometry study within the attendee’s own research context.
Detect common sources of variability within these studies, and select strategies to minimise their impact.
Apply the community-informed minimum requirements for conducting these studies, informed by practical examples of their implementation.
Develop and support complex longitudinal study designs involving multiple instruments, operators, and sites.

Solutions to SICS --Techniques and Technologies to mitigate Sorter Induced Cellular Stress

Ballroom B

Peter Lopez, BS, Research Associate Professor, NYU Grossman School of Medicine

Purification of cell populations has been an important technique used in biological research since the early 1900's. Various purification techniques provide different levels of specificity and purification, ranging from filtration to purify cells based on size, to flow cytometric techniques delivering high purity of populations differentiated using dozens of phenotypic markers. The advent of FACS , a flow cytometric purification technique, provided a mainstay purification technique which arguably changed the playing field for cellular purification and facilitated many critical discoveries in biological research. FACS, based on electrostatic droplet deflection, provides highly purified cell populations,. In some cases cells purified by FACS have downstream functional deficits, and depending on cell type may have issues with viability or proliferative capacity. The perturbed performance of purified cells has been described as SICS. This tutorial will review the various forms of SICS, and will then present methods and technologies including optimization of traditional FACS as well as alternative flow cytometric approaches that can help mitigate SICS.

Learning Objectives:
1-- Learn the history of cell purification technologies, their strengths and weaknesses.
2-- Understand the definition of SICS-- metrics and manifestations.
3– Understand the specific SICS outcomes observed using FACS.
4-- Learn the latest techniques and new purification technologies that help mitigate SICS.

Precision by Design: Building Best Practices for Automated Flow Cytometry

Ballroom C

Lili Wang, PhD, Senior Scientist, National Institute of Standards and Technology (NIST)
Chyan Ying Ke, PhD, Director, Bioapplications, Curiox Biosystems
John Ferbas, PhD, Senior Director, Cytometry & Imaging Sciences, Amgen
Raffaello Cimbro, PhD, Director of Flow Cytometry, AstraZeneca

Standardization and reproducibility remain the cornerstone challenges in translating high-dimensional flow cytometry data into clinically meaningful outcomes. Recent multi-institutional efforts led by the NIST Flow Cytometry Consortium have accelerated consensus-building on pre-analytical variables, assay standardization and validation frameworks, and data quality benchmarks.

This tutorial will explore how automation and standards are converging to address these challenges—from sample handling to antibody cocktailing and washing—by minimizing operator-driven variability and enabling traceable, reproducible workflows.

This tutorial will explore:
- Define and Apply Reference Process Standards
- Integrate Automation into Standardized Workflows
- Evaluate Cross-Site Validation Strategies

Practical guide to small particle flow cytometry

Meeting Room 2C

Vera Tang, PhD, Facility Manager & Adjunct Professor, University of Ottawa
Joshua Welsh, PhD, Staff Scientist, BD Biosciences

Problem Focus/Summary: When selecting a flow cytometer for small particle (EVs / Viruses) analysis, it is important to determine the sensitivity and resolution of the instrument. This tutorial walks through a published workflow for optimization, validation, and instrument maintenance that can be applied to flow cytometers designed to detect cells and small particles alike.

Goals: To provide attendees with practical guidance on how to:
Optimize an instrument for small particle analysis.
Quantify and compare instrument performance.
Track & maintain performance and implement calibration with minimal controls.
Perform advanced characterization: epitope number, diameter, refractive index.
Reagent selection based on instrument detection capabilities.

Learning Objectives:
Provide attendees with background knowledge in the subject area of small particle flow cytometry.
Provide attendees with the knowledge of parameters to tweak to improve instrument optimization for small particle analysis.
Provide attendees with a workflow and understanding of commercially available tools and reagents.
Provide attendees with the tools to make cross-platform data comparisons, e.g. new vs. old instrumentation.
Provide attendees with the resources available to perform instrument calibration.
Provide attendees with an understanding of the factors involved in deriving advanced characterization metrics and their limitations.

Business Intelligence for Flow Cytometry

Meeting Room 2F

Antonio Cosma, PhD, Head of the National Cytometry Platform, Luxembourg Institute of Health

The vast amount of data produced by cytometry, along with its accompanying metadata, necessitates the deployment of advanced and innovative tools. These tools must be adapted to manage data sourced from a multitude of origins. They must also be capable of generating visualizations that are specifically tailored for effective data analysis and sharing. Business Intelligence (BI) addresses all these needs, but it is usually used in the business sector and not in a scientific environment. A critical, not fully recognized aspect of BI is the capability to transfer analytical capabilities to domain experts (i.e., cytometrists) rather than relying on generalized analysts who lack specialized knowledge of the data and the scientific context.

In this tutorial, I will initially lay the basis of data management with a special focus on cytometry. I will show how to organize files for instrument acquisition and introduce the concept of enriched FCS. I will then introduce the concepts of aggregation, joining, filtering, and levels of detail. Once the basis is established, I will proceed to the data preparation and visualization steps. At the end of the tutorial, I will showcase some well-known examples of data sharing already widely used by the cytometry community: (1) the OMIP Cytometry A database, (2) CPHEN Comprehensive Phenotypic Reports, and (3) HCDM CDmap database.

Attendees will learn the principles of BI applied to flow cytometry, enabling them to prepare data and create simple visualizations. The learning curve for BI software is relatively flat, and this introduction will allow participants to get started quickly with their own data.

Building an effective panel design service in a flow cytometry shared resource laboratory

Grand Ballroom

Matthew Cochran, MS - Technical Director, University of Rochester
Kate Pilkington, MSc - Head of Flow Cytometry, Malaghan Institute of Medical Research
Stacie Woolard, PhD - Clinical Cytometrist, St. Jude Children's Research Hospital

Topic Overview and Key Questions:
Panel development should be considered an integral part of all flow cytometry projects, but the process remains a challenging one. Additionally, as instrumentation becomes more capable and research questions become more complicated the process is only getting more critical. While much has been shared over the years here at Cyto and in other venues regarding the best practices for designing panels, relatively little has been said about effectively creating a service in an SRL that utilizes those best practices to develop panels for our research community. To that end, this workshop will focus on methodologies used and challenges faced when building a panel design and development service within a flow cytometry shared resource laboratory.

What steps are involved in effective panel development?
What tools are available for both design and evaluation of panels in development?
As a service provider, can we effectively balance the desire to reduce costs (time and money) with the need for proper design and evaluation?
When performing panel development as a service for a researcher, what are some expected challenges that SRL staff will encounter?
What strategies employed have had a positive impact with this process?

PBMC Working Group Updates and Best Practice Guideline Recommendations

Ballroom A

Thomas Beadnell, PhD - Scientific Advisor, Eurofins Clinical Trial Solutions
Karen Quadrini, PhD - Director, Clinical Biomarkers, Prothena Biosciences
Sylvia Janetzki, MD - President, Zellnet Consulting, Inc

For any study involving PBMC, sample processing is a critical parameter that impacts assay performance.

During drug development and clinical trials, significant logistical hurdles exist that make it a challenge to harmonize this variable across studies. This workshop will provide a needed discussion around the processes and procedures employed to decrease variability and improve quality within PBMC processing and functional assays.

At CYTO 2025, the PBMC organizing committee led a tutorial on best practices for PBMC collection, and a workshop aimed at community engagement and discussion around significant challenges faced by scientists working with PBMC. Despite preparation to discuss many parameters surrounding PBMC processing, it was quickly realized, due to enthusiastic engagement from the audience and lengthy discussion, that one hour would not be sufficient to align the field on all topics. As a result, only one issue was discussed in detail (How to interpret delayed PBMC Isolations) and discussion surrounding the many other processes had to be skipped.

Realizing the number of consensus gaps within the field and considering the suggestions of the Cyto workshop attendees, the organizers of the workshop have established a PBMC Consortium with the objective of harmonizing all PBMC processing steps. The goal is to provide consensus guidance recommendations to the field to help advance the quality, reproducibility, and scientific value of ethically responsible research involving PBMCs. The distinctive strategy is the assignment dedicated working groups with representation from the different fields engaged in PBMC work to review and drive consensus for each stage of the PBMC process, with the larger consortium providing internal peer review and final agreement.

Standardization of Spatial-Omics Experiments

Ballroom B

Orla Maguire, PhD - Assistant Director, Flow and Immune Analysis Shared Resource, Roswell Park Comprehensive Cancer Center
Pratip Chattopadhyay, PhD - Founder, CEO, Talon Biomarkers
Jessica Back, PhD - Director, Microscopy, Imaging, and Cytometry Resources Core, Wayne State University
Hans Minderman, PhD - Co-Director, Flow and Immune Analysis Shared Resource, Roswell Park Comprehensive Cancer Center

Spatial profiling of tissue architecture has advanced rapidly in the last decade with the emergence of spatial-omics technologies. Digital spatial profiling may find its way to genomics shared resource laboratories, but the image-based spatial profiling instruments are dropping into flow and image cytometry shared resources, likely due to the technical and analytical expertise already in these SRLs for high-parameter proteomic profiling. While there has been an explosion of publications using these technologies, there are not yet any guidelines on the standardization of experimental pipelines. The goal of this workshop will be to define the areas where standardization is possible and provide shared resource laboratories transitioning from flow cytometry to imaging with key recommendations for use of these platforms from panel design to publication. Discussion points will include 1) tissue preparation, 2) reagent validation and quality control, 3) image cleanup and the importance of working with a pathologist 4) data analysis, and 5) managing the cost. The workshop will include brief presentations and discussion groups.

Strategic Collaboration Building: Network Science Approaches to Identifying and Engaging Influencers in Cytometry

Ballroom C

Lucas Black, PhD - Founder, CytoLogic Solutions (UK)
Fabienne Lucas, MD, PhD - Assistant Professor, University of Washington

This workshop introduces network science, framing key concepts around understanding one's network position as the first step in shaping collaborations in flow cytometry. We will demonstrate how researchers can systematically analyse and visualise their collaboration networks to guide strategic partnerships. Through anonymised network examples, we will examine structural features that define influence, opportunity, and visibility in the global cytometry research network. Attendees will learn tools to identify their own network position and recognise three strategic collaborator types: hub connectors, emerging leaders, and brokers. We will also address how structural inequities—including gender and geographic disparities—influence collaborative access, providing practical strategies and tools to build more equitable and intentional research networks.

Problem Focus/ Key Questions:
- What structural features define influence, opportunity, and visibility in the global cytometry research network?
- How can cytometrists systematically analyze and visualize their collaboration networks to guide future partnerships?
- How can individuals identify and engage three strategic collaborator types: hub connectors, emerging leaders, and brokers?
- How do structural inequities (e.g., gender or geographic disparities) influence collaborative access, and how can this awareness support more inclusive and intentional community building?

Building Trust in Science: Public Engagement and Advocacy for an International Biomedical Research Community

Meeting Room 2C

Dawn Beraud, PhD - Executive Director, AIMBE
Jason Marvin, PhD - Director of Outreach and Engagement, AIMBE

Evidence-based decisions by policymakers are crucial in governing the scientific enterprise. These activities, often conducted without considering the voices of scientists, crucially shape research and funding decisions across the world. The political administration in some countries, such as the U.S., have imposed recent policies that have significantly delayed grant review processes, proposed cuts to government-supported biomedical research, and resulted in disruptions across a global biotechnology ecosystem. These changes critically threaten scientific innovation, the livelihood of the biomedical workforce, and patient care. Now more than ever as we navigate these uncertainties, it is imperative that scientists bridge this gap between policy and research by collectively speaking out, engaging in advocacy efforts, and effectively communicating with diverse stakeholders (e.g., the general public and their country’s elected lawmakers). There are several impactful ways for biomedical researchers to contribute to these conversations to benefit the field and society. In this workshop, attendees will learn about the importance of advocacy and best practices for public engagement (e.g., storytelling, communicating with non-scientists, explaining your work without jargon, etc.) that are applicable across an international context. AIMBE staff, Fellows, and/or Emerging Leaders will share their experiences highlighting different ways in which they have engaged in these efforts, including their professional experiences with getting involved, personal anecdotes, and the impact that these activities have had on the biomedical research community.

From Big Data to Good Data: How High-Performance Imaging Drives Biomedical Breakthroughs

Keisuke Goda, PhD, Professor, University of Tokyo - Read Bio

AI has rapidly advanced in biology and medicine, demonstrating value in areas such as drug discovery, patient monitoring, and personalized healthcare. Yet, the performance and reliability of AI ultimately depend on the underlying data. Regardless of how sophisticated an algorithm may be, practical clinical implementation is impossible without training datasets of sufficient quality and scale. In this talk, I will introduce a suite of innovative volumetric imaging technologies developed to generate high-quality, high-volume biological data. Through these technologies, I will highlight how high-performance imaging enables data-driven discovery and discuss its central role in realizing clinically deployable AI in biology and medicine.

Hematopoietic stem cells across the human lifespan: functional heterogeneity decoded by flow cytometry

Stephanie Xie, PhD, Scientist, Princess Margaret Cancer Centre, UHN - Read Bio

Hematopoietic stem cells (HSC) have enormous regeneration capacity (~10E11 cells daily in the human). Adult humans are estimated to have 50,000 to 200,000 HSC contributing to hematopoiesis at any one time. Understanding the functional diversity of human HSC across a lifetime is crucial for promoting healthy aging, advancing medicine, and improving therapeutic strategies for hematological disorders. Flow cytometry has long been a cornerstone for defining HSC populations, yet few immunophenotypic stem cell markers have been identified to link molecular signatures and functional outcomes. In this lecture, we present an integrated workflow that combines single-cell index sorting with downstream functional assays to systematically interrogate human HSC across ontogeny. We present a refined marker set—ATP2B1 and CD49f— to characterize long-term HSC from fetal liver, neonatal, and adult sources. ATP2B1 is a calcium exporter that enabled isolation of the most functionally superior population of human HSC described to date. ATP2B1⁺CD49f⁺ cells exhibit superior long-term repopulation and enrichment for endo-lysosomal pathways. We will discuss the workflow, key technical considerations, data integration strategies, and insights gained into the hierarchical organization and mechanistic regulation of human HSC function gained from multi-dimensional flow cytometry coupled to single cell differentiation assays and xenotransplantation. This platform provides a powerful framework for dissecting stem cell biology at unprecedented resolution and uncovering novel biomarkers and therapeutic targets in normal and malignant human hematopoiesis.

Parallel: Standardization and Validation 1

Ballroom A

Standardizing A Human T/B/Monocyte/NK Cell Assay Across Instrument Platforms: An Interlaboratory Study of the Flow Cytometry Standards Consortium
Lili Wang, PhD - NIST Fellow, National Institute of Standards and Technology (NIST)

Automated Antibody Cocktailing for High-Parameter Flow Cytometry: Standardizing Reagent Preparation Using the Pluto Workstation
Chyan Ying Ke, PhD - Director of Bioapplications, Curiox Biosystems

Spectral Flow Cytometry Without Borders: Standardizing Panels and System Templates Across Sites
Gert Van Isterdael, BSc - Head of Flow Core, VIB - Ghent University

Beyond PBMCs: Polymer-Based Cell Mimics for Robust TBNK Immunophenotyping Assay Validation
Swetha Pratyusha Gunturu, MS - Scientist 3, Flow Cytometry, Slingshot Biosciences

Parallel: Autofluorescence and Label-Free Cytomery 1

Ballroom B

Advancing Label-Free Detection and Isolation of Senescent Cells Using Imaging and Spectral Flow Cytometry
Vidjaya Letchoumy (Viji) Premkumar, PhD - Senior Scientist, AstraZeneca

Raman Vibrational Imaging to Characterize the Biochemical Morphology of Colorectal Cancer Progression
Julia Gala de Pablo, PhD - Lecturer in Biophysical Approaches for Healthcare, University of Leeds

Correlating NAD(P)H lifetime shifts to chemotherapeutic treatment in breast cancer: a metabolic screening study with time-resolved flow cytometry in breast cancer cells continually treated with tamoxifen
Samantha Escamilla, PhD Candidate - Research Assistant, New Mexico State University

Label-Free Analysis and Sorting of Mycobacterium tuberculosis-Infected Macrophages Using Spectral Autofluorescence and Image-Derived Morphological Parameters
Ioannis Panetas, PhD - Senior Scientific advisor, Becton Dickinson GmbH

Parallel: Biomarkers & Drug Discovery 1

Ballroom C

Imaging Flow Cytometry Detection of Cytogenetic Abnormalities in Circulating CD34+ cells in Myelofibrosis
Ruby Hamilton, PhD Student - Student, The University of Western Australia

Isolation and measurement of single mitochondria with microfluidic cytometers
Gregory Cooksey, PhD - Project Leader, National Institute of Standards and Technology

An international collaborative validation of a 34-color full spectrum flow cytometry panel for characterizing G-CSF mobilized peripheral blood stem cell donor allograft products
Orla Maguire, PhD - Assistant Director, Flow and Immune Analysis Shared Resource, Roswell Park Comprehensive Cancer Center

A validated 29-color Treg-centric spectral flow cytometry assay with cross-platform algorithm-assisted analysis for autoimmune studies
Calin Marian, PhD - Principal Scientist, Merck & Co., Inc., Rahway, NJ, USA

Parallel: SRL and Education 1

Grand Ballroom

Being Everything, Everywhere, All at Once: Open-Source Automation for Situational Awareness in SRLs
David Rach, PhD - Post-Doctoral Staff, Flow Cytometry Shared Resource, University of Maryland Greenebaum Comprehensive Cancer Center

The Make Your Own Flow Cytometer: Continued evolution of a unique educational resource
William Telford, PhD - Senior Associate Scientist, NCI-NIH

Optimized toolset for evaluating single-color controls in spectral flow cytometry
Jayanth Narayanan, PhD - Scientist, R&D, ThermoFisher Scientific

Restore-in-Place and Sustain-in-Place: Expanding the role of ISAC Instruments for Science in global cytometry support
William Telford, PhD - Senior Associate Scientist, NCI-NIH

Parallel: Brazilian Symposium

Room 2DEF

Real-Time Cytometric Analysis of ATP-Dependent Calcium Oscillations Governing Neural Stem Cell Fate in Huntington’s Disease
Henning Ulrich, PhD - Professor, University of São Paulo

Purinergic Receptor P2X7: from characterization to function in the immune system during infection by intracellular pathogens
Robson Coutinho-Silva, PhD - Professor of Immunology, Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro

Cytometric Approaches to characterize molecular and cellular parameters in the skin and adipose tissue during wound healing in aging
Claudia Benjamim, PhD - Assistant Professor, Federal University of Rio de Janeiro

Flow Cytometer-Enabled Multiplex SuperRCA Mutation Assay in a Single Portion of Circulating Tumor DNA (ctDNA) Sample
Lei Chen, PhD - CTO, Rarity Bioscience AB

Autofluorescence lifetime flow cytometry of immune cells

Melissa Skala, PhD, Professor, Morgridge Institute for Research - Read Bio

The autofluorescence lifetimes of the metabolic co-enzymes NAD(P)H provide a label-free, functional readout of single-cell metabolism, which is sensitive to cell activation states and drug-induced metabolic changes. We developed a microfluidic flow cytometer that measures NAD(P)H autofluorescence decays from individual cells using time-correlated single-photon counting (TCSPC), with picosecond resolution and real-time phasor-based classification. This system combines a cost-effective pulsed UV diode laser excitation (50 MHz pulse repetition rate with short pulses ≤90ps), alkali photomultiplier tubes, and an FPGA-based time tagger for real-time analysis. We report continuous acquisition with a 100% duty cycle using on-chip decay histogramming, throughput of up to 100 cells per second with an average of 10,000 emission photons from each cell while receiving a safe excitation light dose (2.65 J/cm2 at 375nm), and microfluidic chip designs featuring vertical and horizontal sheath flow for cell focusing. We incorporate a second detection channel for far-red antibody markers to relate cell function on a single-cell level with NAD(P)H lifetime shifts. We characterize single cell metabolic heterogeneity in primary human immune cells. We further explore downstream applications including single-cell deposition for integration with single-cell sequencing, and bioreactor integration for long-term, label-free, closed-loop monitoring of cell manufacturing. These capabilities improve the throughput and automation of autofluorescence lifetime measurements of single cell metabolism for applications including immunophenotyping, metabolic screening, and bioprocess monitoring.

Seeing Cells in 3D: Stain-Free Tomographic Flow Cytometry for Deep Live-Cell Phenotyping

Dr. Pietro Ferraro, Director of Research, CNR - ISASI Institute of Applied Sciences and Intelligent Systems - Read Bio

Traditional flow cytometry (IFC) has revolutionized single-cell analysis by combining the statistical power of flow with the spatial information of microscopy. However, standard IFC remains largely limited to 2D projections and often relies on exogenous labels that can alter cell physiology or limit longitudinal study. This presentation introduces a breakthrough in high-throughput analysis: dye-free tomographic flow cytometry. By integrating holographic optical diffraction tomography (ODT) with controlled microfluidics, we demonstrate the ability to reconstruct the 3D refractive index (RI) distribution of cells in flow. Unlike traditional methods, this approach provides intrinsic quantitative contrast based on the physical properties of cellular organelles without the need for fluorescent labeling. Biomedical case studies will be presented to illustrate the platform's diagnostic and research potential.

Integrating Raman Spectroscopy and Microfluidic Deformation Cytometry for Single-Cell Staging of Barrett’s Oesophagus Progression

Stephen D Evans, PhD, Professor, University of Leeds - Read Bio

Early detection of oesophageal adenocarcinoma (OAC), which often develops from Barrett’s oesophagus (BO), remains a major clinical challenge due to the lack of sensitive, non-invasive diagnostic tools. This study introduces a multi-modal, label-free approach combining Raman spectroscopy and microfluidic deformation cytometry to characterise biochemical and biomechanical changes in live single cells across disease stages—from healthy oesophageal epithelium to dysplastic BO and OAC. Raman spectroscopy revealed distinct spectral signatures associated with nucleic acids, lipids, and proteins, enabling accurate classification of disease progression using PCA-LDA. Complementary mechano-phenotyping demonstrated increased cellular stiffness in dysplastic and cancerous cells, reflecting cytoskeletal remodelling. Acidic bile salt exposure experiments further highlighted stress-induced biochemical and morphological changes in BO cells, providing insights into microenvironmental influences on disease evolution. By integrating these modalities with machine learning, we hope to establish a high-throughput, non-destructive platform for single-cell staging, offering significant potential for early cancer detection and personalised diagnostics.

How the physical sciences can empower biology : Applications of single molecule fluorescence to the biosciences

Prof Sir David Klenerman, Royal Society GSK Professor, Molecular Medicine, University of Cambridge - Read Bio

The capability to image single molecules has revolutionised biology. I will explain how these methods work and how we are currently applying them to study the molecular basis of neurodegenerative disease. Lastly I will describe how our early single molecule work on DNA polymerase led to the development of next generation DNA sequencing, now widely used, and the lessons that can be learnt from this experience.

Microfluidic cytometry for precision cell engineering

Abraham Lee, PhD, Chancellor's Professor, University of California, Irvine - Read Bio

Microfluidic cytometry processors capable of cell sorting, cell engineering, and cell characterization form the “cell processing units” (CPUs) for bioengineering (bio-CPUs). This is analogous to the CPU (central processing unit) for computer engineering. The current cell engineering paradigm typically focuses on a singular target or pathway, by adding, subtracting or replacing a single genetic code to program cells for targeted diagnosis or therapeutic functions. In reality, the complexity of constantly evolving diseases (cancer, autoimmune diseases, etc.) involves abnormalities that affect the mutated expression of tens of thousands of genes. The ability to sort and engineer cells precisely to program multiple cell functions is critical for the future development of cell therapies. In this talk I will introduce two bio-CPU microfluidic platforms in my lab. 1. Acoustic electric shear orbiting poration (AESOP) device to uniformly deliver genetic cargos into a large population of cells simultaneously. We demonstrate high quality transfected cells with controlled dosage delivery as well as serial delivery of different genetic cargos. These capabilities can be used to optimize the therapeutic efficacy of the engineered cells and also combine it with promising gene editing tools to further condition the cells for more specific in vivo targeting. 2. Arrayed-droplet optical projection tomography (ADOPT) method that relies on flow-controlled, linear cell rotation of live, suspended cells (e.g. immune cells), to allow 360°-imaging of suspension cells with high lateral resolution using simple epifluorescence microscopy. ADOPT is akin to a “bio-GPU” (graphics processing unit) by rapidly producing 3D morphologies of single cells powered by the bio-CPUs. As the AI revolution was accelerated by the advent of the GPUs, it is projected that the bio-GPUs will serve a similar role for the BI (biological intelligence) revolution. A prime application for the bio-CPU and bio-GPUs is immunoengineering that involves the “reprogramming” of the immune system to overcome limitations of the innate or adaptive immune responses that the body naturally produces.

Single-Molecule Sensitive Digital Flow Cytometry

Daniel T. Chiu, PhD, Professor, University Of Washington - Read Bio

We have developed a multi-parametric high-throughput and high-sensitivity flow-based method for counting single molecules, and applied this method to the analysis of individual extracelluar vesicles and particles (EVPs). EVPs are promising biomarkers but they are highly heterogeneous and comprise a diverse set of surface proteins as well as intra-vesicular cargoes. Yet, current approaches to the study of EVPs lack the necessary sensitivity and precision to fully characterize and understand the make-up and the distribution of various EVP subpopulations that may be present. Digital flow cytometry (dFC) provides single-fluorophore sensitivity and enables multiparameter characterization of EVPs, including single-EVP phenotyping, the absolute quantitation of EVP concentrations, and biomarker copy numbers. dFC has a broad range of applications, from analysis of single EVPs such as exosomes or RNA-binding proteins to the characterization of therapeutic lipid nano¬particles, viruses, and proteins. dFC also provides absolute quantitation of non-EVP samples such as for the quality control of antibodies (Ab), including the concentration of individual and aggregated Ab-dye conjugates and the Ab-to-dye ratio.

Parallel: Standardization and Validation 2

Ballroom A

Instrument Platform Standardization for Producing AI/ML-ready Datasets
Yu "Max" Qian, PhD - Associate Professor, J. Craig Venter Professor

Calibration and Reference Materials support reliable analysis of breast cancer extracellular vesicles in biofluids across flow cytometers
Estefanía Lozano-Andrés, PhD - Assistant professor, flow core director, Utrecht University

SOULCAP Template-Guided Label Transfer for Standardized Cytometry Population Annotation
Gert Van IstLeon Li, PhD Student - PhD Student, Computer Science, McGill Universityerdael, BSc - Head of Flow Core, VIB - Ghent University

Harmonizing Flow Cytometry: The SOULCAP Effort
Kelly Lundsten, BS - Founder and Consultant, Luminous Bioanalytical Consulting

Go Big or Go Home: Practical Calibration for High-Recovery Large-Particle Sorting
Joseph De Rutte, PhD - CEO, Partillion Bioscience

Parallel: Autofluorescence and Label-Free Cytomery 2

Ballroom B

Label-Free Immunophenotyping and Cancer Status Detection Based on High-Throughput Flow-mode Raman-activated Cell Sorting (FlowRACS)
Wenjie Zhao, PhD - Assistant Researcher, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences

Profiling estrogen-receptor-positive cell types using autofluorescence optical redox measurements and fluorescence lifetime imaging microscopy
Lina Khiyara, MS - Research Assistant, MS chemical engineering student, New Mexico State University

Pseudodynamic Ghost Cytometry Enables Label-Free Tracking and Sorting of Live-Cell State Transitions
Hiroko Nomaru, PhD - Senior Scientist, ThinkCyte KK

Undersea Flow: Label-Free Morphometric Cytometry Enables Cellular Diversity Assessment and Sorting in the Marine Chordate Botryllus schlosseri
Ayelet Voskoboynik, PhD - Assistant Professor of Biology, Stanford University

Mapping Tumor-Driven Autofluorescence Changes with Excitation-scanning Hyperspectral Imaging in a Murine Colorectal Cancer Model
Rebecca Tang-Holmes, PhD - Candidate Student, University of South Alabama

Parallel: Biomarkers & Drug Discovery 2

Ballroom C

Detection of Adverse Cytogenetics in Acute Myeloid Leukemia by Imaging Flow Cytometry using “Immuno-flowFISH”
Kathy Fuller, PhD - Associate Professor of Translational Oncology, The University of Western Australia

A single-cell immunogenicity assay using Time-lapse flow cytometry
Sheldon Kwok, PhD - CEO and Co-founder, LASE Innovation Inc.

Solving Immune Marker Degradation: Two-Year Whole Blood Stabilization Preserves Blood Samples for Multiparameter Cytometry
Li-Chun Cheng, PhD - Chief Scientific Officer, Teiko

Prognostic value of integrating leukemia stem cell into measurable residual disease evaluation of acute myeloid leukemia
Hongyan Liao, PhD - Associate Professor, Department of Laboratory Medicine, West China Hospital, Sichuan University

CellSurf ELISA: A High-Throughput Assay for Sorting Immune Cells Based on Cytokine Secretion
Zongjie (Daniel) Wang, PhD - Group Leader, Chan Zuckerberg Biohub Chicago

Parallel: Immunology

Grand Ballroom

High-Throughput, Image-Activated Dissection of Natural Killer Cell–Tumor Interactions by Cell-Cell-seq
Jesse Liang, PhD - Associate Director of R&D, Partillion Bioscience

Morphometry Enables Label-Free Tracking of Myeloid Cell Differentiation and Phagocytic Function
Romain Ballet, PhD - Head of Research, ThinkCyte Inc.

A High-Throughput Nanovial Platform for Needle-in-a-Haystack Antibody Discovery Against Cell-Surface Targets
Jesse Liang, PhD - Associate Director of R&D, Partillion Bioscience

Beta-2 adrenergic regulation of the aged immune system
Dennis Affram, PhD Candidate - PhD candidate in Immunology, University of Surrey, UK

Self-assembling sealable microcompartments for large-scale functional cell screening
Yuta Nakagawa, PhD - Postdoctoral Fellow, University of California Los Angeles

Parallel: Imaging Flow Cytometry Technology Development

Room 2DEF

Intelligent image-activated large cell sorting using elasto-inertial focusing
Yuzuki Nagasaka, PhD Candidate - Graduate student, The University of Tokyo

In-plane Hydrodynamic Focusing of Nanoparticles to Estimate Particle Size and Velocity in Microfluidic Devices
Brandon Stacks, PhD - Postdoctoral Researcher, National Institute of Standards and Technology

High-Throughput Full-Spectrum Imaging Flow Cytometer Based on Dual-Laser Linear Array Spot Excitation
Yong Han, PhD - Cofounder, tech lead, Fairy Life Sciences (WuHan) Co., Ltd.

Linking Mitochondrial Ultrastructure to T Cell Metabolism and Function Using Imaging Flow Cytometry
Nicola Milne, BSc - Undergraduate Student, The University of Edinburgh

Neglected morphological features of circulating tumor cells revealed using imaging flow cytometry and their clinical relevance
Natalia Bednarz-Knoll, PhD - Professor Assistant, Medical University of Gdańsk

Rapid-Fire Presentation

Virginia Litwin, PhD, Director, Scientific Affairs, Eurofins Clinical Trial Solutions - Read Bio

Rapid-Fire Presentation
CLSI H43 Guideline: Clinical Flow Cytometric Analysis of Neoplastic Hematolymphoid Cells

Prof. Dr. med. Wolfgang Kern, Executive Management, Internist, Hematologist and Oncologist, Head of business unit Strategy & Business Development, MLL MVZ GmbH - Read Bio

CLSI H43 Guideline has been finally drafted by an international expert panel and is undergoing review. Targeted time of publication is end of 2026/early 2027. The scope of H43 covers all hematologic neoplasms focusing on differences in flow cytometrically assessible characteristics between these diseases and their normal cell couterparts. Diagnostic and follow-up approaches both will be addressed. General flow cytometric aspects will be discussed using CLSI H62 guideline as the basis. This third edition of CLSI H43 guideline will provide laboratories worldwide applying flow cytometry for hematologic neoplasms with comprehensive, detailed, and ready to use information augmented by educative examples. The draft will benefit from comments provided during the public review period: everyone active in the field is welcome to provide feedback.

Beyond Positive and Negative: Quantitative Flow Cytometry in Predicting CART Therapy Responsein B-Cell Lymphomas

Jean Oak, MD, PhD, Clinical Associate Professo, Department of Pathology, Stanford University - Read Bio

Chimeric Antigen Receptor T cell (CAR T) therapies have become standard treatment options for a growing number of hematologic neoplasms. In patients with large B-cell lymphoma, approximately 30% of relapsed patients exhibit significant antigen downregulation. While the impact of target antigen downregulation at relapse has been extensively studied, the role of pre-treatment antigen density remains inadequately characterized. Current clinical reporting practices vary widely, often relying on qualitative, binary assessments of antigen expression or percentage positivity using internal or external controls.

In this study, we describe the implementation of quantitative flow cytometry to evaluate CD19, CD20, and CD22 antigen density in patients considered for CAR T therapy. In a cohort of 74 patients undergoing CD19 CAR T therapy, our findings reveal that patients with a median pre-CART antigen density below 3000 CD19 molecules/cell exhibit significantly lower progression-free survival (p < 0.007). Additionally, the percentage of very low antigen expressors (less than 1000 molecules/cell) is significantly increased among patients with low median antigen density, suggesting that selective pressure favoring the expansion of low antigen expressors may contribute to relapse.

The use of quantitative flow cytometry demonstrates the potential utility of this technology in predicting therapy response and informing treatment strategies. While integrating quantitative flow cytometry into routine clinical workflows presents several technical and operational challenges, this work highlights the evolving role of flow cytometry in the era of immunotherapy.

Beyond Positive and Negative: Quantitative Flow Cytometry in Predicting CART Therapy Responsein B-Cell Lymphomas

Sa Wang, MD, Professor of Pathology, Section Chief of Flow Cytometry, The University of Texas MD Anderson Cancer Center - Read Bio

Accurate quantification of chimeric antigen receptor (CAR) T cells is essential for monitoring post-infusion CART expansion and persistence and for informing real-time clinical decision-making. Multiparameter flow cytometry (MFC) enables rapid, live-cell detection with absolute quantification and concurrent immunophenotypic characterization. This talk focuses on the practical and technical aspects of flow cytometry–based CAR T-cell monitoring, including selection of CAR detection reagents (target-specific, construct-specific, and target-agnostic strategies), assay optimization, purpose-driven panel design, and matrix-appropriate validation for peripheral blood and other clinically relevant specimens. Assay considerations unique to gene-edited allogeneic CAR T-cell products, including the use of surrogate immunophenotypic approaches when construct-specific reagents are unavailable, will be addressed. The role of MFC in identifying CAR T-cell clonal expansions and in evaluating suspected secondary hematolymphoid neoplasms in the post-CAR T setting will be discussed.

Ingredients Matter: How Input Features Can Make or Ruin Your Cytometry Analysis

Grand Ballroom

Serena Di Cecilia, PhD - Software Solutions Manager, BDB
Ioannis Panetas, PhD - Senior Scientific advisor, FlowJo Informatics, BD Biosciences
Jonathan Irish, PhD - Professor, Department of Pediatrics-Neurology, University of Colorado
Katrien Quintelier, PhD - Postdoctoral Researcher, VIB-Ghent University
Sarah Bonte, PhD - Postdoctoral Researcher, VIB-Ghent University

Problem Focus/Key Questions:
A high-dimensional analysis workflow typically involves the use of dimensionality reduction and/or clustering algorithms. Features used as input for these algorithms are derived from cytometry or imaging cytometry data, either in coding environments such as Python and R, or in commercially available platforms with graphical user interfaces. However, controversial opinions and concerns are emerging within the field, on which parameters should (or should not be) used and how preprocessing steps affect the final outcome. The goal of this workshop is to come up with guidelines on when to use which input features to obtain meaningful insights and reliable results.

Main points to discuss are listed below and key questions are:
Which parameters to use as input for dimensionality reduction and clustering?
Do we always need compensated/unmixed data, or are there also cases where uncompensated/raw data makes more sense?
What are interesting image-derived parameters?
Do we use only fluorescence channels, or also include scatter channels?
Can it make sense to also use width and/or height for fluorescence channels, instead of just area?
Lineage markers vs functional markers
Type of transformation to use, with which parameters?

Beyond assay development: how flow cytometry should be used outside of the research laboratory setting

Ballroom A

Ruud Hulspas, PhD - Director of Research and Development, Cell Manipulation Core Facility, Dana-Farber Cancer Institute
Peter Lopez, BS - Research Associate Professor, NYU Grossman School of Medicine

The field has made tremendous progress in sensitivity, accuracy and the ability to measure and analyze a large number of cell parameters simultaneously. Flow cytometry assays are still very much performed as a research assay designed to develop and optimize flow cytometry applications. Industrial cell manufacturing demands non-expert operation and consistent, standardized output that is clear, traceable and reproducible. The workshop will address these industry requirements within the context of reagents, sample preparation, instrument and data analysis. The ISAC community holds a significant level of expertise in engineering. Although this workshop will address all four aspects, it is expected to spend more time on the instrument aspect of flow cytometry.

Key questions that would be answered through discussion groups include the following:
1. What calibration/normalization method is best to standardize instrument output ?
2. What are best practices for sample preparation in QC of cell therapy manufacturing ?
3. What are the main challenges in reagents ?
3. What current data analysis methods lie on the path of expert-free, reliable end results ?

SRL in the age of AI

Ballroom B

Paul Wallace, PhD - Professor Emeritus at Roswell Park and Educator in Chief of ISAC

Intended Audience:
Flow Cytometry users and SRL staff interested in incorporating AI tools into their daily workflows. This includes researchers, core facility staff, and companies offering panel design, experimental setup guidance, and data analysis platforms.

Topic Overview:
Artificial Intelligence (AI) has become an integral part of our daily lives. From early tools like Siri, Alexa, and Google Assistant to more advanced platforms such as ChatGPT, Copilot, and Google Gemini, AI now supports a wide range of everyday tasks. And Shared Resource Labs (SRL) are not immune to this change.

In recent years, increasingly sophisticated AI tools have emerged, offering specialized assistance across various sectors, including biomedical research and flow cytometry.

However, opinions on AI’s usefulness vary. Some users embrace it fully, relying on tools like ChatGPT for even minor tasks, while others remain cautious, concerned about ethical and environmental implications. As with any technology, the key lies in finding a balanced approach: using AI as a powerful tool to enhance and not replace human expertise.

This workshop will explore how AI can be effectively and responsibly integrated into Flow Cytometry workflows, particularly in the context of an SRL. We will discuss which tools are currently available, which are already commonly in use, and how to leverage them to improve efficiency and decision-making without compromising human oversight.

Learning Objectives:
By the end of this session, participants will be able to:
1) Identify AI tools relevant to Flow Cytometry and SRL operations, which are commonly used and their impact.
2) Explore new AI tools that could enhance SRL workflows.
3) Learn practical strategies for integrating AI into SRL management, experimental planning, panel design, and data analysis.
4) Discuss ethical considerations and best practices for responsible AI use in core facilities.
5) Insights gained in discussion and the results gathered during polling will be compiled into a report that will be made available."

Sustaining Quality in Small or One-Person SRLs

Ballroom C

Jessica L. Prieto-Chavez, MS - Co-Coordinator of the Cytometry Network, Mexican Social Security Institute (IMSS)
Gabrielle Siegers, PhD - Flow Cytometry Facility Manager, University of Alberta
Estefanía Lozano-Andrés, PhD - Assistant Professor, Utrecht University
Michael Solga, MS - SCYM, Director, Flow Cytometry Core, University of Virginia

Shared Resource Laboratories (SRLs) vary widely in size and resources, with many operating as small or even one-person facilities. While these labs play an essential role in supporting research, they often face unique challenges in maintaining quality, implementing best practices, and ensuring operational sustainability with limited staff and infrastructure.

Despite these constraints, many small SRLs continue to deliver high-quality services through creative problem-solving, resource-sharing, and community engagement. However, current guidelines and best practices are often written from the perspective of larger facilities, leaving a gap in practical recommendations tailored to smaller operations.

This workshop, developed in response to feedback from the 2025 CYTO SRL Forum, will address the challenges reported by small and single-person SRLs in adhering to existing Best Practices. It will provide a forum for discussing how such labs can effectively sustain quality and adopt best practices under constrained conditions. Participants will explore real-world strategies, share experiences, and identify collective solutions that can inform future updates to existing publications or the creation of new guidelines.

Key questions to guide the discussion:
Are some Best Practices more important than others in SRLs with limited personnel and resources?
Can smaller SRLs focus their efforts on more feasible elements, and turn their attention to potentially less critical areas as time and resources allow?
What practical tools, workflows, and management strategies can help maintain quality in small or single-person SRLs?
What challenges do smaller facilities face in achieving recognition, visibility and ongoing professional development?
How can ISAC and the broader community better support small SRLs to ensure long-term sustainability and quality alignment?

Addressing hidden challenges when organizing cytometry training activities from and for the Associated Societies

Meeting Room 2C

Lourdes Arriaga-Pizano, MD, PhD - Professor, IMSS

For many years the relationship between the associated societies (AS) and ISAC has included collaboration in carrying out training activities. While some of these activities are directly organized by ISAC, many others are organized by these local/regional groups with or without ISAC involvement. In a relationship of equals between ISAC and AS, the ideal is that these types of activities be organized jointly. For this reason, it is important that ISAC understands and recognizes the specific characteristics of the area in order to organize these training activities. And for the AS it is of utmost importance to know, beyond the pursuit of academic excellence, some logistical issues that allow them to both ensure successful attendance and seek effective support from ISAC.

Recently the relationship among ISAC and the Associated Societies have being update with the sign of a Memorandum of Understanding. This document recognizes the independence and value that AS have for ISAC's global reach. However, not always is easy to recognize the challenges that the AS have to face for organizing this training activitiesin different regions of the world. And sometimes it is not also clear for the AS what other issues that the academic ones should be adressed for a succesful traning event in cytometry. Having clear guidelines and recommendations on how AS can organize events with the collaboration or support of ISAC will be very useful in order to operationalize some of the points included in this MOU.

For this reason, we propose to explore, in an open round table, what are the challenges and opportunities that must be taken into account to Improve the performance of training activities from and for the Associated Societies of ISAC.

Flow Forward: Unlocking Careers in Cytometry for Pharma and Drug Development

Meeting Room 2F

Tony Chadderton, MSc - Principal Research Expert, Incyte Research Institute
Christele Gonneau, PhD - Global Scientific Director, Flow Cytometry, Labcorp
Laura Prickett, BS - Associate Principal Scientist, Astra Zeneca
Steven Eck, PhD - Group Director, Flow Cytometry, Astra Zeneca
Veronica Nash, PhD - Director, Flow Cytometry US, GSK

Problem Focus/Key Questions: The workshop focuses on bridging the gap between core technical cytometry expertise and its application in pharmaceutical careers, drug discovery and drug development/clinical trials. The workshop will address issues and offer solutions around integrating high quality flow cytometry into early discovery and translational research. Key topics include implementation of internal training programs across expertise levels, standardization of protocols and data analysis, and regulatory alignment in industry settings. The workshop will highlight the evolving skillsets required for various industry roles.

Key questions include:
● How does flow cytometry contribute to investigative research, translational medicine, and drug development?
● What cytometry skill sets are currently in demand within industry settings?
● What collaborative models could support innovation and career development across and between academia and pharma, and between drug development companies and flow cytometry products/instruments manufacturers?