Applications

Galileo TMA systems support high-value pathology applications where sample efficiency, standardization and traceability are essential.

IHC-stained TMA core
IHC-stained TMA core

Biomarker validation

Organize large cohorts, controls and replicates into reproducible TMA layouts for comparative staining and scoring.

Spatial omics TMA core
Spatial omics core

Spatial omics

Place multiple tissue samples on a single assay slide to improve sample throughput and reduce high-value assay consumption.

TMA core — multiplex immunofluorescence
Multiplex immunofluorescence

Multiplexing

Build standardized arrays for multiplex immunofluorescence and image analysis across many tissues under identical conditions.

Digital pathology image analysis on an IHC core
Digital pathology image analysis

Digital pathology

Link core position and donor metadata to de-arraying and image-analysis workflows.

Organoid / spheroid core
Organoid / spheroid core

Organoids and Spheroids

Standardize analysis of preclinical models, spheroids or organoids when compatible with the chosen sample preparation method.

Galileo with Frozen TMA Module
Galileo Frozen TMA Module

Frozen tissue research

Use the Frozen TMA Module with compatible Galileo systems for applications requiring frozen material.

Application visuals are supplied by ISENET.

Why TMA matters for advanced assays

Many modern assays are expensive, tissue-limited and image-analysis intensive. A well-designed TMA can increase comparability and reduce per-sample reagent and slide costs by allowing multiple samples to be processed together.

Design principles

  • Use replicate cores when tissue heterogeneity is expected
  • Add positive and negative controls
  • Include orientation markers or empty positions
  • Select core diameter according to assay and tissue availability
  • Preserve donor-to-spot traceability for downstream analysis

Design a TMA for your application

ISENET can help define the most appropriate instrument, core size and workflow based on your biomarker, multiplex or spatial omics project.

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