THE SPEAKER

Fabienne Lucas, MD, PhD - Assistant Professor, University of Washington

Fabienne Lucas is a hematopathologist and laboratory medicine researcher at the University of Washington, Seattle, where she serves as Assistant Professor in Hematopathology and Co-Director of the Clinical Flow Cytometry Laboratory. She helps lead a high-volume academic reference laboratory that processes 20,000–30,000 samples annually, including extensive measurable residual disease (MRD) testing. Dr. Lucas completed pathology and hematopathology training at Mass General Brigham, earned a PhD in hematology and immunology from Barts Cancer Institute in London, and previously trained in hematology/oncology in Germany. She is a former recipient of the ISAC Marylou Ingram Scholarship and currently serves in leadership roles within the International Clinical Cytometry Society (ICCS) and the College of American Pathologists (CAP). Her work focuses on flow cytometry, laboratory operations, diagnostic stewardship, and emerging technologies in pathology and laboratory medicine. Her current research includes one of the first efforts to systematically benchmark emissions, energy use, transportation, consumables, and waste generation in a large clinical flow cytometry laboratory. Through this work, she explores how sustainability can support laboratory quality, workflow efficiency, operational resilience, and responsible resource utilization.

WEBINAR SUMMARY
Flow cytometry laboratories are resource-intensive environments, yet their environmental footprint is rarely measured. This webinar explores practical, metrics-driven approaches to sustainability using ongoing research from a large U.S. academic clinical flow cytometry laboratory as a real-world example. Topics will include energy consumption, specimen transport, packaging waste, consumables, data infrastructure, and workflow optimization, along with strategies that can support both environmental stewardship and operational efficiency. Although grounded in clinical laboratory practice, the session is designed for research laboratories, shared resource laboratories (SRLs), and core facilities seeking practical and adaptable approaches to sustainability. Participants will gain actionable ideas for evaluating their own workflows, identifying measurable opportunities for improvement, and building greener laboratory practices without compromising scientific or clinical quality.

Learning Objectives:

By the end of this webinar, participants will be able to: 
- Identify major sources of environmental impact in flow cytometry and laboratory operations, including equipment energy use, specimen transport, consumables, packaging, refrigeration, and data-intensive workflows 
- Describe practical approaches for measuring laboratory sustainability metrics such as carbon emissions, waste generation, resource utilization, and workflow-related environmental costs 
- Recognize opportunities to improve operational efficiency and reduce environmental impact through workflow optimization, packaging and shipping changes, equipment practices, and reduction of unnecessary resource use 
- Compare sustainability considerations across clinical, research, and shared resource laboratory settings, including the differing operational constraints and regulatory requirements that shape implementation strategies 
- Discuss how emerging technologies such as spectral flow cytometry and panel consolidation may reduce reagent consumption, specimen requirements, and workflow redundancy while supporting high-quality laboratory operations

Who Should Attend:
Clinical Cytometrists, Educators/Trainers, Industry Scientists (vendor-agnostic; tool developers, method innovators), Outreach Groups, Research Scientists, Shared Resource Laboratory (SRL) Managers, Shared Resource Laboratory (SRL) Staff, Trainees (Graduate students, postdocs, early-career researchers)

Keywords: laboratory sustainability, flow cytometry, environmental stewardship, laboratory operations and workflow optimization, metrics-driven resource utilization

CMLE Credit: 1.0

THE SPEAKERS 

Martin Poinsinet de Sivry, PhD, Postdoctoral Researcher - Amsterdam UMC
President's Award for Excellence, 2026

Dr. Martin Poinsinet de Sivry is a postdoctoral researcher in biomedical optics at Amsterdam UMC. He holds a PhD in Engineering Physics from Polytechnique Montréal, where he specialized in optical modelling, numerical simulation, and light scattering. His research focuses on flow cytometry, biomedical imaging, fibre optics, and particle characterization. He develops high-performance scientific software in Python and C++ and is the lead developer of several open-source projects, including PyMieSim, SuPyMode, and FlowCyPy. His current work explores new signal processing technique for flow-cytometry systems.

Ruby Hamilton, PhD Student - The University of Western Australia
Exceptional Student Award, 2026

Ruby Hamilton is a third-year PhD student in the Translational Cancer Pathology Laboratory at the University of Western Australia. Her research focuses on investigating the genetic changes associated with disease progression from myelofibrosis to acute myeloid leukemia through cell-free DNA sequencing and imaging flow cytometry techniques. By integrating novel and highly sensitive blood-based disease monitoring methods, her work aims to detect early molecular changes in patients at high-risk of leukaemic transformation. 

         
WEBINAR SUMMARY
This webinar will feature two 20-minute presentations by distinguished past award recipients. Each year at the CYTO meeting, early-career scientists compete for these highly regarded honors, which recognize outstanding scientific achievement and promise. The competitions are open to all eligible CYTO attendees, making these awards among the most competitive and prestigious recognitions within the community.

In addition to being honored at CYTO, award recipients are invited to present a CYTO U Webinar, providing the broader community with the opportunity to learn directly from their innovative research and insights.

To learn more about these awards, please visit the ISAC Awards page.

Beyond Coincidence: Leveraging Neural Networks to Overcome Coincidence in Flow-Cytometry – Presented by Martin Poinsinet de Sivry
In flow cytometry, increasing the particle rate improves measurement throughput but also increases the probability that multiple particles cross the interrogation region simultaneously. The resulting overlapping detector pulses, known as coincidence, can cause particles to be missed, merged, or assigned biased signal amplitudes. This webinar presents FLASH, a signal-processing pipeline designed to overcome this coincidence bottleneck in small-particle flow cytometry. FLASH combines a convolutional neural network for particle-event localization with a physics-based solver that reconstructs the amplitude of individual overlapping pulses. The approach is evaluated using digitized side-scatter signals from 300 nm polystyrene beads measured on a modified BD FACSCanto II across particle rates approaching one million particles per second. In the absence of direct ground truth, performance is assessed through physical consistency checks involving particle arrival-time statistics, amplitude distributions, and count scaling with concentration. Compared with conventional threshold-based detection, FLASH preserves plausible event timing, reduces coincidence-induced amplitude bias, and extends the usable throughput range by more than an order of magnitude. The webinar will discuss the underlying methodology, experimental implementation, validation strategy, current limitations, and prospects for real-time FPGA deployment and physics-informed analysis.

Imaging Flow Cytometry Detection of Cytogenetic Abnormalities in Circulating CD34+ Cells in Myelofibrosis - Presented by Ruby Hamilton
Patients with myelofibrosis can progress to acute myeloid leukemia (AML) following acquisition of new genetic changes that arise of cells in the bone marrow. Once patients progress to AML, they are typically refractory to treatment and have a median survival of less than 6 months. Evolution to AML is unpredictable and current tests lack the sensitivity and applicability needed to predict when transformation will occur. We aimed to assess prognostically important chromosomal abnormalities in circulating CD34/CD45-positive cells in myelofibrosis patients using an imaging flow cytometry method (immuno-flowFISH) that integrates immunophenotyping and fluorescence in situ hybridization. We also aimed to monitor changes in clonal evolution and burden throughout disease progression to see if we could identify these changes earlier than current methods. We propose that blood monitoring using immuno-flowFISH will enable earlier identification of high-risk clonal evolution, such as del(17p), providing a novel framework for disease surveillance which may improve prediction of leukemic transformation in myelofibrosis.

KEYWORDS: ISAC Webinar Featuring ESA and PAE Winners, Leukemia, Chromosomes, Imaging, Monitoring, Biomarkers, Flow Cytometry, Coincidence, Neural Networks, Signal Deconvolution, High-Throughput Analysis

THE SPEAKER

Yuta Nakagawa, PhD - Project Assistant Professor, University of Tokyo 

Yuta Nakagawa is a project assistant professor at The University of Tokyo, where his research focuses on developing novel flow cytometry tools to enable single-cell screening based on their function including secretion, proliferation, and cell-cell communication. He received his PhD from The University of Tokyo under the mentorship of Professor Keisuke Goda, where he worked on developing cutting-edge flow cytometers such as a high-throughput microfluidic droplet sorter. He was then trained as a postdoctoral scholar at UCLA under Professor Dino Di Carlo, where he worked on developing novel functional assays leveraging microparticles and flow cytometry. He is actively engaged with the ISAC community, including attendance at CYTO conferences and membership of Marylou Inghram Scholar of the ISAC leadership development program.

WEBINAR SUMMARY
Compartmentalizing single cells at the microscale is crucial for screening heterogeneous populations or libraries of mutants for functional properties such as secretion, cell-cell interactions or growth. Example applications include T cell receptor and antibody discovery as well as microbial colony picking, which have significant implications from drug screening to therapeutic development. Technologies based on microfluidics such as microwell and microdroplets have been applied to these problems. However, while these tools have been demonstrated to effectively perform cell assays, they typically require specialized instrumentation and are either limited in throughput or transport required for extended cell culture and reagent exchange, hampering wide adoption. More recently, lab-on-a-particle technologies have emerged as complementary tools for carrying out microscale reactions to analyze molecules and cells in a high-throughput manner. Microparticles suspended in oil-free aqueous phase and compatible with conventional laboratory tools such as microscopy and flow cytometry can be leveraged for assaying various functional cell assays. In this webinar, two implementations of lab-on-a-particle technologies will be introduced, namely (1) nanovials and (2) capped nanvoials. First, nanovials are cavity-containing particles that facilitate compartmentalization of single cells and capture of secreted proteins on the surface of the cavity. Here, nanovials are used to assay the single-cell secretion phenotype of collagen, a critical extracellular matrix (ECM) protein also known to play a role in fibrosis. Second, capped nanovials, which are self-assembling micro-compartments formed by “capping” nanovials with spherical particles, are introduced as a novel microcompartment functionally akin to a test tube. Crucially, capped nanovials are formed in a massively parallel manner (>100,000 capped nanovials/mL prepared in ~10 minutes) by simple pipetting and centrifugation and analyzed using accessible instruments such as microscopes and flow cytometers. Using this platform, key biomedical applications including yeast colony growth assay and a paired antibody-secreting and reporter cell assay are demonstrated.

Learning Objectives:
Participants will be introduced to an overview of lab-on-a-particle technologies and how to implement them, focusing on two specific implementations including (1) nanovials and (2) capped nanovials. The webinar will highlight how these tools can be incorporated into biomedical assays from sample preparation to assay execution, all while leveraging accessible tools such as microscopy and flow cytometry.

Who Should Attend:
Educators/Trainers, Imaging Cytometrists, Industry Scientists (vendor-agnostic; tool developers, method innovators), Research Scientists, Shared Resource Laboratory (SRL) Managers, Shared Resource Laboratory (SRL) Staff, Trainees (graduate students, postdocs, early-career researchers), Computational Biologists/Bioinformaticians, Research Scientists, Trainees (graduate students, postdocs, early-career researchers), Translational Immunologists

Keywords: lab-on-a-particle, functional single-cell analysis, flow cytometry, nanovials

CMLE Credit: 1.0

THE SPEAKER

Sara De Biasi, PhD - Assistant Professor, University of Modena and Reggio Emilia

Sara De Biasi is an Italian immunologist and researcher affiliated with the University of Modena and Reggio Emilia, where she works within the Department of Medical and Surgical Sciences for Children and Adults. She obtained her PhD in Clinical and Experimental Medicine (Immunology) from the same institution and has continued her academic career there, progressing from postdoctoral research to a research and teaching role in general pathology and immunology. Her research focuses on the human immune system, particularly T cell biology and immune responses in conditions such as HIV infection, autoimmune diseases, cancer, and multiple sclerosis. In recent years, De Biasi has been actively involved in investigations related to COVID-19, examining immune markers and vaccine responses, as well as broader immunological mechanisms underlying severe infections and neurological disorders. With over a decade of scientific activity and numerous peer-reviewed publications, she is recognized for her contributions to translational immunology and her role in advancing understanding of immune dysfunction in complex diseases.

WEBINAR SUMMARY

This webinar will present recent advances in translational immunology through the lens of single-cell metabolic profiling, with a particular focus on the scMEP (single-cell Metabolic Profiling) approach. Over the past two years, this framework has enabled the dissection of immune cell heterogeneity by integrating functional and metabolic features at single-cell resolution. The session will explore how immunometabolism shapes immune responses across different contexts, including cancer and autoimmune diseases, highlighting the relationship between metabolic programs, immune cell activation, and disease progression. In addition, emerging insights into vaccine responses will be discussed, with emphasis on the identification of metabolic signatures associated with effective and durable immunity.
 
The webinar will also address the impact of aging on the immune system, examining how metabolic rewiring contributes to immunosenescence and altered immune competence in older individuals. Overall, this talk will provide an overview of how scMEP and multi-omics approaches can advance our understanding of immune regulation and support the development of more precise and personalized strategies in oncology, autoimmunity, and vaccinology.

Learning Objectives:
Participants will learn:
- how to measure metabolic alterations in immune cells by mass cytometry
- why metabolism is important for cell function
- how to predict vaccine response on the basis of metabolic function of immune cells

Who Should Attend:
Computational Biologists/Bioinformaticians, Research Scientists, Trainees (graduate students, postdocs, early-career researchers), Translational Immunologists

Keywords: metabolism, aging, cancer, multiple sclerosis 

CMLE Credit: 1.0

THE SPEAKER

Smita Krishnaswamy, PhD - Professor, Yale University

Smita Krishnaswamy is a Professor of Computer Science and Genetics at Yale University. She is also affiliated with the Program for Applied Mathematics and WTI Institute for NeuroComputation and Machine Intelligence at Yale and an affiliate member of the MILA Quebec AI Institute. Smita's lab works on fundamental deep learning and mathematical machine learning methods for accelerating discovery from biomedical and neuroscientific data. Her work features many methods for generative modeling, graph-based learning, visualization, dynamics modeling and optimal transport as well as multimodal integration of high dimensional data. She has applied her techniques to discovery from cellular, molecular, and imaging data from neuroscience, psychology, stem cell biology, cancer, and immunology. Smita obtained her Ph.D. from the University of Michigan in Computer Science. Smita's work has won several awards including the NSF CAREER Award, Sloan Faculty Fellowship, and Blavatnik Fund for Innovation. Smita teaches deep learning, unsupervised learning, geometry topology in ML and other courses at the intersection of CS and applied math. She also teaches special courses in computational genomics at CGSI (UCLA), CSHL, as well as being a mentor for the Yale SUMRY math REU program.

WEBINAR SUMMARY

In this talk, Dr. Krishnaswamy will cover progress towards building a fundamentally new type of AI scientist that goes beyond orchestrating existing analysis pipelines or selecting among pre-defined tools. Instead, this scientist infers mechanistically plausible generative models of complex, systems-level data by unifying mathematical modeling with deep learning. Unlike current AI scientists, which primarily automate experimental design, literature synthesis, or statistical analysis, our approach seeks to learn an explicit, interpretable model of the underlying system itself. For example, in cellular data, the system infers an abstract but mechanistically grounded model of a cell that could generate the observed molecular measurements. Towards this end I will cover "ingredients" of this that we have been developing including geometric data representations, data shape detection, flow-based models for trajectory inference, and graph and sheaf ODE models for dynamics and perturbation modeling. These tools can then be orchestrated by an LLM agent.

 
Learning Objectives:

Participants will develop an understanding of:
- Representation Learning, Trajectory Inference, Dynamics modeling, AI Scientists, Lab-in-the-loop AI

Who Should Attend:
Computational Biologists/Bioinformaticians, Data Analysts, Educators/Trainers, Industry Scientists (vendor-agnostic, tool developers, method innovators) Research Scientists, Share Resource Laboratory (SRL) Staff,  Trainees (graduate students, postdocs, early-career researchers), Translational Immunologists

Keywords: Representation Learning, Trajectory Inference, Dynamics modeling, AI Scientists, Lab-in-the-loop AI

CMLE Credit: 1.0

Standardization for Precision: Building Best Practices for Automated Cell Sample Preparation Across Multi-Site Flow Cytometry Labs

Presenters:
Lili Wang, PhD, Senior Scientist, National Institute of Standards and Technology
Tom Hayday, PhD, Co-founder and Chief Research Officer, IMU Biosciences
John Ferbas, PhD, Senior Director, Cytometry & Imaging Sciences, Amgen
Raffaello Cimbro, PhD, Director of Flow Cytometry, AstraZeneca

Problem Focus/Summary:

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

Keywords: Sample Prep, Protocol standardization, Cytometry Hardware, Experimental Design & controls

CMLE Credit: 1.5

CYTO Women: Career Pathways Panel Discussion

Panelists: 
Arielle Ginsberg, MSc, SCYM, CEO, terraFlow
Kathy Muirhead, PhD COO, SciGro, Inc.
Laura Ferrer-Font, PhD, Scientific Solutions Manager -Scientific Affairs, R&D, Waters Biosciences
Pratip Chattopadhyay, PhD, Founder and CEO, Talon Biomarkers

Unlock the secrets to a fulfilling career in cytometry! Whether you are a student, a postdoc, or a seasoned professional, this essential mentoring session is designed to help you navigate your next chapter within the flow cytometry field. Join distinguished leaders Arielle Ginsberg, Kathy Muirhead, Peter Mage, and Pratip Chattopadhyay as they share firsthand accounts of the career paths, pivots, and breakthroughs that shaped their journeys. Gain actionable strategies for long-term planning and participate in an open Q&A to get personalized advice on your professional development.

Don’t leave your future to chance—come learn how to turn your passion for cytometry into a strategic career roadmap!

Keywords: CYTO, CYTO Women, Career Development

Fundamental Considerations for Quantitative Fluorescence Standardization

Presenters:
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.

Keywords: Calibration, Quantitative, Fundamental Concepts, Hardware, Standardization, Experimental Design

CMLE Credit: 1.5

Navigating SRL Recognition: How to Prepare Your Application

Presenters:
Jessica Prieto-Chavez, MSc, Co-Coordinator of the Cytometry Network of the Health Research Coordination, Mexican Social Security Institute (IMSS)

Abstract:
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.

Keywords: Management, Training and Education, SRL Recognition Program

CMLE Credit: 1.5

Business Intelligence for Flow Cytometry

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

Abstract:
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.

Keywords: Instrument Monitoring, Bioinformatics, SRL, Shared Resource Laboratories, Operations and Finance, Management

CMLE Credit: 1.5