Partner with ArcentLabs
Explore GEROTWIN
Computational Biology

AI for in-silico prioritization

in healthy ageing research

A virtual aged-tissue model — an AI-based New Approach Methodology that predicts and ranks the response of physiologically aged tissue to geroprotective interventions in silico, benchmarked to reduce and replace animal screening.

The Validation Bottleneck

Reducing uncertainty before validation

Healthy-ageing research requires better ways to prioritize intervention candidates before costly and time-consuming validation studies. GEROTWIN is designed to support earlier, evidence-informed decision-making through high-level computational modeling

What makes GEROTWIN unique

Predicts how aged tissue is expected to respond to senolytics, partial reprogramming, rapamycin-class compounds and related interventions before laboratory testing.

Trained on physiologically aged single-cell atlases rather than young or transformed cell lines.

Counterfactual intervention simulation
Foundation model for aged tissue
Decision-grade uncertainty

Ranks intervention candidates together with calibrated confidence estimates, supporting experimental prioritization rather than replacing scientific judgement.

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