HeartBeat.bio and Cubase Bio bring 3D spatial transcriptomics to Cardioids

HeartBeat.bio and Cubase Bio have formed a research collaboration to combine Cardioid cardiac organoids with three-dimensional spatial transcriptomics. The project, called FACTS-3D, is supported by roughly €1 million in Eurostars funding through Vinnova, Austria's FFG and the European Union's Horizon Europe programme.

The proposed platform

HeartBeat.bio contributes self-organizing human cardiac organoids designed for disease modelling and drug discovery. Cubase Bio contributes a spatial-transcriptomics method intended to map gene expression through an intact 3D sample rather than infer a volume from selected two-dimensional sections.

The collaboration will focus on myocardial fibrosis and heart failure. The aim is to connect spatially resolved molecular states with structural and functional responses to drug treatment.

Why it matters

An organoid average can conceal the biology researchers most need to see. Fibrotic programmes may be concentrated at an interface, arise around a particular cell population or spread unevenly through a tissue. True 3D measurements could reveal whether a treatment changes the number of responsive cells, their location, or the relationships among cell types.

Spatial information may also improve comparability. Two organoids with similar bulk expression can have different internal organization, which can translate into different function. A scalable spatial readout could become a richer quality attribute for complex models.

What to watch

The work is at collaboration stage. Its value will depend on spatial resolution, transcript recovery, throughput, cost and the ability to align molecular maps with functional Cardioid measurements. Sample preparation must also preserve both geometry and RNA quality without creating systematic distortions.

Most importantly, the partners will need to show that the extra spatial information changes a decision—such as explaining a drug response that bulk or single-cell data could not resolve.

HCMX take

The pairing is technically coherent: a 3D model should ideally be read in three dimensions. FACTS-3D will be compelling if it turns spatial complexity from an attractive image into a reproducible, decision-relevant measurement.