Journal Article

From sample to insight: how spatial biology is transforming cancer prognosis and clinical research

16 July 2026 · 10 min read
  • Automation
  • Biotech & Pharma
  • Widefield Light Microscopy
Profile Image of Sherry Derakhshani
Author Dr. Sherry Derakhshani Product Marketing and Applications Manager – Biopharma Solutions
Carl Zeiss Microscopy GmbH, Germany

Abstract

Spatial biology is moving from research curiosity to clinical reality – and the results are already changing how we understand and treat disease. The key to unlocking its full potential lies in automated, reproducible, end-to-end workflows that turn tissue complexity into clear, actionable decisions.

Key Learnings:

1. Spatial biology has matured into clinical reality

  • It has moved from a research curiosity to an operational, clinically impactful platform (e.g. TissueCypher for Barrett’s oesophagus risk stratification).
  • Recognition by Nature Methods and the World Economic Forum reflects both scientific and translational relevance.
  • Understanding where biomarkers are in tissue and how cell populations interact is critical for prognosis, therapy response and patient stratification.

2. Clinical and commercial proofs now exist

3. Spatial biology is strategically relevant beyond diagnostics

  • It supports target validation, mechanism-of-action studies, pharmacodynamics, toxicology, trial enrichment and companion diagnostics.
  • CROs are building full-service offerings around standardized ZEISS workflows, enabling sponsors without in-house expertise to access spatial biology at scale.

4. Barrier to entry is lowering; strategic adoption is the next step

  • With integrated, automated workflows, deep microscopy or spatial biology expertise is no longer a prerequisite to generate high-quality multiplex data.
  • The focus for pharma, biotech and CROs should shift from “can we do spatial biology?” to “how do we embed these capabilities into our R&D and clinical strategies?”
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From sample to insight: how spatial biology is transforming cancer prognosis and clinical research

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