Parhelia Spatial Station for all-in-one spatial biology workflow automation

Click2Contact

Spatial biology and flow cytometry are time-tested hallmarks of cellular biomarker discovery, immune profiling and clinical practice — but the growing complexity of highly multiplexed experiments creates a challenge for researchers to design and prepare appropriate panels (or cocktails) and associated controls.

While precise panel design is essential for successful experiments, manual preparation involves increased systematic errors, inter-operator variability, and researcher hands-on time. Such drawbacks risk repeating experiments, wasting time and reagents.

Parhelia Biosciences is addressing the challenges of manual processing with dedicated automation solutions that address gaps in laboratory efficiency and standardise the sample preparation workflow for any spatial biology assay. The Parhelia Spatial Station solves the added complexity riddle with benchtop flexibility, high-quality staining, and verified and customisable assays.

The system features a small footprint with state-of-the-art robotics, liquid handling, temperature control and quality safeguards. The user can bring their own chemistries and/or scale with single-use Skylab kits. There is also flexible throughput, with the ability to prepare one sample or up to 48 (12 with temperature control).

Patented capillary laminar flow technology gently and uniformly applies reagents. Flow cells can be assembled in seconds and protect precious samples. 100 μL chambers and zero dead volume yield significant reagent savings.

A growing list of plug-and-play assays has been developed with Parhelia’s partners and collaborators. Protocols can be optimised quickly, with automated robotic efficiency. Users will also benefit from intuitive protocol builder software, hands-on training and a support team to guide them.

End-to-end automation of multiomics workflows removes labour-intensive and error-prone roadblocks from study design while enabling hands-free consistency and data quality.