Spatial Biology & Digital Pathology
From native tissue to quantitative translational insight.
IRBM combines automated multiplex staining, whole-slide imaging, high-plex spatial proteomics, and quantitative digital pathology to reveal where biology happens — across oncology and neuroscience discovery programs.
Native tissue contextSingle-cell quantificationDecision-ready reporting
Why spatial tissue analysis
Move beyond whether a marker is present.
Resolve which cells express it, where they sit, who surrounds them, and how that architecture changes with disease or treatment.
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Biology in context
Preserve tissue architecture while measuring cell identity, phenotype, and local microenvironment.
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More biology per section
From focused mIF panels to 100+ marker discovery, extract deeper information from limited tissue.
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From image to decision
Convert morphology and marker expression into reproducible single-cell, regional, and spatial readouts.
Traditional IHC → Multiplex spatial contextDrag to compare
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Traditional IHCMultiplex / spatial
One platform, two depths of interrogation
Choose the spatial depth your question needs.
Focused, hypothesis-driven multiplexing and high-plex discovery sit within the same digital pathology workflow.
Targeted Multiplex IF
Up to 9 biomarkers per section in established mIF workflows
Automated staining on Leica BOND RX
Whole-slide multispectral imaging on PhenoImager HT
Panel optimization for FFPE tissue
Quantitative single-cell and ROI analysis
Ideal for focused biomarker, PD, target-validation and translational studies.
High-Plex Spatial Profiling
100+ biomarkers with PhenoCycler-Fusion
Iterative high-plex whole-slide imaging
Single-cell spatial phenotyping at scale
Deep discovery from one tissue section
Customizable protein panels and spatial analysis
Ideal for discovery research, complex biology, and comprehensive spatial profiling.
High-Plex Spatial Dataset • PhenoCycler-Fusion
33 biomarkers. One section. A systems-level view.
Toggle individual channels to reconstruct epithelial, lymphoid, myeloid, vascular, proliferative and checkpoint biology directly within the native tissue architecture.
33protein biomarker channels
plus DAPI nuclear counterstain
plus DAPI nuclear counterstain
Explore all 33 biomarkersSwitch any channel on or off. Marker buttons are grouped by biological program for easier navigation.
15active markers
End-to-end workflow
From tissue section to decision-ready spatial insight.
A controlled workflow that combines assay development, automation, whole-slide imaging, single-cell quantification and spatial biology — with targeted mIF and high-plex options.
Study
report
report
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Tissue sectionThe workflow starts from native tissue architecture, preserving the context required for downstream quantitative spatial biology.
Automated staining
Leica BOND RX
Standardized, reproducible staining for IHC and targeted multiplex IF, supporting efficient panel implementation across preclinical studies.
Established mIF workflows • up to 9 biomarkers / section
Whole-slide acquisition
PhenoImager HT
Multispectral whole-slide imaging designed for robust multiplex fluorescence acquisition while retaining tissue architecture and regional context.
High-plex branch
PhenoCycler-Fusion
Extend the same tissue-to-insight workflow into discovery-scale, single-cell spatial profiling when much deeper marker coverage is required.
100+ biomarker spatial profiling • single-cell discovery
Digital pathology analysis pipeline
From pixels to cell-level biology.
The analysis layer converts multiplex imagery into quantitative, interpretable endpoints — moving from tissue architecture to single-cell phenotypes and spatial systems-level insight.
01 • Architecture
Tissue segmentation
Separate biologically meaningful compartments and define region-specific analysis spaces before cell-level quantification.
02 • Single cell
Cell segmentation
Detect nuclei and cell boundaries to create a quantitative single-cell representation of the tissue.
03 • Phenotypes
Cell phenotyping
Classify cell populations from marker combinations and quantify expression within biologically relevant phenotypes.
04 • Spatial insight
Spatial & systems biology
Resolve regional distributions, proximity, neighborhoods and cell-cell relationships to support biological interpretation.
Quantitative endpoints% positive cells, intensity, counts and densities
Cell-type specificityMarker expression resolved by phenotype
Spatial relationshipsProximity, neighborhoods and regional burden
Decision-ready outputFigures, tables, statistics and scientific reporting
Therapeutic focus
Spatial biology in Oncology and Neuroscience.
Two therapeutic areas, one principle: preserve tissue context and convert it into quantitative biological evidence.
Tumor microenvironment
Separate tumor, stroma and immune compartments and quantify cell populations within each niche.
PanCKCD3CD8CD68
Pharmacodynamic response
Connect tissue-level pathway modulation and proliferation to treatment groups and in vivo outcomes.
Ki67pERKPD-L1
Immune contexture
Map cytotoxic, regulatory and myeloid populations and their spatial relationships to tumor compartments.
FoxP3PD-1CD45
Target & biomarker validation
Localize target expression by cell type, tissue compartment and disease context before downstream decisions.
Regional brain mapping
Quantify cortex, striatum, hippocampus and other defined regions without losing anatomical context.
NeuNDARPP-32
Aggregate burden – case study example
Measure aggregate positivity, number, size and distribution at cell-type and region level.
EM48HTT
Neuroinflammation
Profile glial and neuronal responses while preserving the local CNS microenvironment.
GFAPIba1
Target engagement & PD
Link molecular modulation to anatomically resolved tissue outcomes and disease-relevant cell populations.
Whole-embryo mapping
Capture large anatomical context in a single section, from early structural organization to region-level biological patterning.
Whole sectionEmbryoAtlas-style view
Neurodevelopmental marker localization
Visualize lineage, differentiation and developmental programs across brain and peripheral embryonic compartments.
PatterningDifferentiationRegionalization
Single-cell and regional readouts
Move from visually rich morphology to quantitative segmentation, cell phenotyping and region-resolved endpoints.
SegmentationCell statesQuantification
Translational utility
Support developmental neuroscience studies, model characterization and comparative biology with high-content spatial imaging.
Mouse modelsCNS developmentSpatial biology
Quantitative digital pathology
Images are only the beginning.
Analysis plans are customized to the tissue, biological question and decision endpoint.
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Tissue segmentation
Define compartments, anatomical regions and ROIs with morphology-aware analysis.
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Cell segmentation & phenotyping
Single-cell detection, marker extraction, positivity scoring and phenotype assignment.
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Spatial relationships
Co-localization, nearest-neighbor, proximity and neighborhood analysis.
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Quantitative reporting
Cell-level tables, region summaries, figures, spatial maps and scientific interpretation.
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Object / aggregate metrics
Size, number, intensity and spatial distribution of disease- or target-related objects.
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Regional analysis
Normalize by area, cells or phenotype within biologically defined tissue regions.
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Whole-slide data
Preserve high-resolution context while extracting interpretable quantitative endpoints.
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Scientific interpretation
Deliver results as a biological story — not just a spreadsheet of measurements.
Resources
White papers, case studies and technical insight.
A resource section designed to turn the webpage into a scientific entry point — not just a capability list.
White paper
Insights from Spatial Biology in Drug Discovery at IRBM
The impact of cellular ecosystems, tissue architecture and spatial biomarkers across drug discovery.
Ready when you are
Let’s design your spatial biology study.
Tell us the tissue, the biological question and the decision you need to make. We’ll map the right platform, panel and analysis strategy.