Bruker Online Organoid Summit 2026: Advancing 3D Biology Through Imaging
Join us for a two-day virtual event focused on the latest developments in organoid research and advanced fluorescence imaging.
October 6 - 7, 2026 | 8AM PDT | 11AM EDT | 4PM CET
At the Bruker Online Organoid Summit 2026, experts from the scientific community will share research, imaging approaches, and practical insights for studying organoids with greater depth, clarity, and precision.
Whether you are currently working with organoids or exploring how these models could support your research, this summit offers an opportunity to learn from leading scientists, discover new imaging possibilities, and connect with others advancing the field of 3D biology.
Join this summit to learn about:
- Innovative research and imaging approaches for investigating the structure, function, and dynamic behavior of complex 3D biological models
- How advanced fluorescence microscopy and atomic force microscopy can help address the challenges of imaging thick, complex, and highly dynamic samples
- Approaches for visualizing cellular organization, development, disease mechanisms, and treatment response in organoid models
October 6 - 7, 2026 | 8AM PDT | 11AM EDT | 4PM CET
Join the conversation shaping the future of organoid research
The Bruker Online Organoid Summit 2026 will bring together experts from the scientific community to share research, imaging approaches, and practical insights for studying organoids with greater depth, clarity, and precision.
Discover how researchers are using innovative imaging technologies to investigate the structure, function, and dynamic behavior of complex 3D biological models.
Through a series of scientific presentations, attendees will learn how advanced fluorescence microscopy and atomic force microscopy can help address the unique challenges of imaging thick, complex, and highly dynamic samples. Topics will highlight emerging applications and approaches for visualizing cellular organization, development, disease mechanisms, and treatment response in organoid models.
See the schedule of events, learn more about our featured speakers and presentations, or register now to secure your spot!
Date: October 6 - 7, 2026
Location: Virtual
Featured Technologies:
Contact:
Event Program
Time (PDT) | DAY 1 | DAY 2 |
|---|---|---|
| 8:00AM - 8:10AM | Moderator Welcome | Moderator Welcome |
| 8:10AM - 8:55AM | Presentation: Treatment Resistance and Relapse in Cancer Speaker: Dr. Martin Jechlinger | Presentation: Atomic Force Microscopy and the Mechanics of Cell and Spheroid Culture Speaker: Nazli Demirpehlivan |
| 8:55AM - 9:05AM | Q&A session with Dr. Martin Jechlinger | Q&A session with Nazli Demirpehlivan |
| 9:05AM - 9:50AM | Presentation: The Mechanics Driving Metastasis: Biophysical Phenotyping of High-Grade Serous Ovarian Cancer Spheroids Speaker: Jordan Turney | Presentation: Putting the Cell-Cycle Clock into Organoid Phenotyping: From CALIPERS Cardiac Organoids to Lumenoids and Gastruloids Speaker: Francesco Pasqualini |
| 9:50AM - 10:00AM | Q&A session with Jordan Turney | Q&A session with Francesco Pasqualini |
| 10:00AM - 10:45AM | Presentation: Label-Free Metabolic Imaging via 2-Photon FLIM: Establishing Analytical Pipelines for 2D and 3D Cancer Models Speaker: Valentina Pasquale | Moderator Thank You |
| 10:45AM - 10:55AM | Q&A session with Valentina Pasquale | |
| 10:55AM - 11:00AM | Moderator Thank You |
Abstracts
At the time of diagnosis, the majority of high-grade serous ovarian cancer (HGSOC) patients are late stage and show signs of peritoneal metastasis. The mechanism of metastasis is dissemination through the peritoneum as multicellular 3D spheroids, yet most nanomechanical characterisation of this disease has been performed on 2D monolayers The relevance of monolayers as a model of metastatic structures and how they can be targeted remains largely untested.
This talk follows one question through a complete workflow: does the mechanical state of an HGSOC spheroid matter functionally, or is it a byproduct of the underlying biology and can we use this to inform our therapeutic options?
This talk discusses sample optimisation and the use of the latest generation bioAFM from Bruker (Nanowizard V) on the cellwizard stage in order to achieve accurate and high resolution bioAFM measurements. Techniques included are substrate coating, colloidal probe geometry, per-frequency viscous drag calibration, and contact-point handling of rough heterogenous samples. The contact mechanics required when working with curved, layered multicelllar bodies rather than flat half-space samples will also be addressed.
To determine biophysical properties, nanomechanical maps and active oscillatory microrheology are compared across parental SKOV3, a cisplatin-resistant derivative, and MRC-5 fibroblast co-cultures, applying structural-damping, double power-law and stress-relaxation treatments to the same dataset to show where these models agree and where they diverge. Volumetric confocal quantification of crucial structures such as F-actin and Collagen I links the mechanical response to core-versus-periphery architecture that has no monolayer equivalent.
Invasive and metastatic potential are quantified using confocal microscopy and image-based invasion assay chambers. Matrigel-collagen type I matrices seeded with co-cultured spheroids provide a biomimetic model of peritoneal dissemination, enabling quantification of migration distance, trajectory angle, and spatial localization of cell populations initiating and leading invasion."
Finally, miR-200b gene therapy in monoculture spheroids is used to perturb this mechanical state directly, with invasion assessed under matched conditions in order to asses whether measured biophysical signature tracks invasive capacity. Measuring these biophysical properties also indicates and informs new molecular targets to improve therapeutic outcome.
Speaker: Jordan Turney
Date: October 6, 2026
Time: 9:05AM - 9:50AM PDT
Location: Virtual
Two-photon Fluorescence Lifetime Imaging Microscopy (FLIM) is a valuable, label-free technique for evaluating cellular metabolic states through intrinsic fluorophores such as NADH and FAD. However, establishing reproducible workflows and extending analysis pipelines from conventional 2D cultures to 3D models presents several technical considerations.
This presentation outlines the development and implementation of a 2-photon FLIM acquisition and analysis pipeline for cancer cell characterization. First, the application of this workflow on 2D cancer cell line monolayers is discussed, establishing baseline metabolic profiles and verifying the consistency of data processing strategies. Second, preliminary progress in adapting these analytical tools to 3D tumor spheroid models is presented, addressing technical aspects such as signal penetration depth, z-stack imaging, and spatial heterogeneity.
Rather than focusing solely on finalized biological outcomes, this talk aims to emphasize practical workflow development, data analysis methodologies, and current insights gained while transitioning 2-photon FLIM from 2D benchmarks to 3D systems
Speaker: Valentina Pasquale
Date: October 6, 2026
Time: 10:00AM - 10:45AM PDT
Location: Virtual
The mechanical properties of the cellular environment have historically been treated as an end product of its composition, with cell behavior explained mainly through biochemical signaling. However, over the past three decades, a wide range of work has established that substrate and matrix stiffness is sensed by cells and actively converted into functional outcomes (R.J. Pelham, 1997) (Lo, 2000) (Engler, 2006). More recently, this framework has been extended from single cells on two-dimensional substrates to three-dimensional multicellular spheroids embedded in hydrogels of tunable stiffness, revealing that the surrounding mechanical environment regulates spheroid growth, invasion, and internal mechanical state (A. V. Taubenberger, 2019). Therefore, we must investigate the biophysical cues that influence cell biology alongside biochemical composition, treating the two as complementary.
Atomic force microscopy (AFM) has been central to these studies, providing the quantitative, spatially resolved force-distance measurements needed to validate substrate stiffness and to characterize the resulting mechanical properties of cells and spheroids. To extract the mechanical information, force-distance curves must be analyzed through three critical steps; (i) pre-processing the curve, (ii) identifying the contact point, and (ii) fitting a contact mechanics model. The contact point is often indistinct, and errors at this stage strongly affect the extracted mechanical properties. The classical numerical fitting model that minimizes the mean-squared-error is time consuming for complex models. Even more, the dataset size necessary to characterize large specimens –such as spheroids– scales up quickly, increasing processing time and complicating the use of more complex contact mechanics models.
We present a set of new machine-learning powered processing operations to increase both speed and robustness of mechanical analysis, reducing user input. We have trained a regression model using experimental curves, which can simultaneously apply necessary corrections and detect the contact point. We couple this operation to high-throughput deep learning based fitting routine defined by (Tejedor, 2025). This is crucial because deep learning regression speeds up the calculation of complex contact models, including viscoelastic effects, so that online fitting during measurements is possible. This allows us to move beyond a single elastic modulus to quantify the mechanical properties of spheroids and process large datasets efficiently, representing a further step toward understanding the biology that underlies these structures. Alongside, new AFM simulation and analysis pipeline (ASAP) offers a customizable AFM-FDC simulation and regression model training pipeline. This module aims to overcome training data shortages and aid the development of fitting routines for specific contact mechanics and has been applied to contact stiffness measurements.
In conclusion, we propose a machine learning approach to AFM data analysis that removes the need for manual user input and computationally expensive processing steps. The goal is to carry state-of-the-art AFM-based mechanical characterization to its next step and broadening its use in 3D culture systems.
Speaker: Nazli Demirpehlivan
Date: October 7, 2026
Time: 8:10AM - 8:55AM PDT
Location: Virtual
Cell-cycle state is a hidden coordinate in live-cell phenotyping, especially in stem-cell-derived 3D tissues where proliferation, lineage commitment, morphogenesis, and functional maturation unfold together.
I will present CALIPERS, our recently published Nature Communications framework for cell-cycle-aware live-cell imaging in phenotyping experiments and regeneration studies. CALIPERS combines a spectrally redesigned FUCCI reporter, continuous cell-cycle inference, and compatible structural and functional biosensors in human cell and hiPSC models. In cardiac organoids, it tracks cell-cycle exit, tissue compaction, calcium onset, and distinguishes productive cardiomyocyte proliferation from multinucleation and endoreplication.
I will then discuss how CALIPERS hiPSC reporter cells are being extended into Lumenoids and Gastruloids to link cell-cycle dynamics to tissue organization and to enable live light-sheet phenotyping in developmental and regenerative contexts.
Speaker: Francesco S. Pasqualini
Date: October 7, 2026
Time: 9:05AM - 9:50AM PDT
Location: Virtual
Speakers
Francesco S. Pasqualini
Associate Professor of Industrial Bioengineering, Principal Investigator @ Synthetic Physiology Laboratory, Department of Civil Engineering and Architecture, University of Pavia
Jordan Turney
4th Year Biomedical Engineering Student, RBGO Group, Swansea University
Martin Jechlinger, Ph.D.
Head of VISION Laboratory at MOLIT Institut gGmbH;
Visiting Scientist at European Molecular Biology Laboratory (EMBL)
Nazli Demirpehlivan
Ph.D. Candidate in SPM4.0 Horizon Project MSCA, Software Group in BioAFM Bruker Nano GmbH
Valentina Pasquale
Post Doctoral Research Fellow & Scientific and Technical Lead for Two-Photon & High-Content Systems, Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy;
SYSBIO-ISBE-IT-Candidate National Node of Italy for ISBE, Research Infrastructure for Systems Biology Europe, Milan, Italy
