The Challenge

A biotech company specialising in therapeutic antibodies wanted to assess the potential of a lead compound in a novel disease indication. They needed to mine public single‑cell RNA‑sequencing datasets to evaluate target gene expression and understand mechanisms of action.

Our Approach

We mined and integrated single‑cell datasets, uncovered mechanisms and hallmarks of disease, and provided actionable insights for follow‑up.

• Data mining & integration: Searched and integrated disease‑specific single‑cell datasets from multiple tissues to map target gene expression across cell types.
• Mechanism and hallmark identification: Performed differential gene analysis to characterise disease‑associated states and identify hallmarks persisting after therapy.
• Actionable insights: Analysed on‑ and off‑target gene‑expression patterns and provided an integrated view to guide toxicology and follow‑up experiments.

The Outcome

• Provided independent confirmation that the lead compound remains viable for further development.
• Delivered a comprehensive map of target activity across cell types and conditions.
• Highlighted hallmarks persisting after therapy and supplied mechanistic insights to guide future studies.
• Saved costs by extracting actionable information from public data rather than generating new datasets.

Why It Matters

De‑risking a therapeutic programme by leveraging publicly available data reduces cost and accelerates decision‑making. This approach allows companies to validate compounds and understand mechanisms before committing to expensive experiments.