Computational Prioritization

In-silico candidate prioritization models

GEROTWIN-RECODE is a generative in-silico model of the ageing cell state a multiscale, intervention-class NAM that predicts whether partial epigenetic reprogramming will deliver safe, functional and durable rejuvenation across aged tissues, thereby prioritising regimens before costly in-vivo development.

By integrating molecular, cellular and tissue-level evidence, GEROTWIN-RECODE helps prioritize the most promising interventions before costly in vivo development. Our goal is to enable more precise regimen selection, identify safety and durability risks earlier, and shorten the path from experimental design to translational validation.

THE EXPERIMENTAL BOTTLENECK

From computational prediction to experimental validation

Healthy-ageing research requires systematic methods to prioritize intervention candidates before committing to costly physical trials. We address this bottleneck with structured, computational modeling of aged biological states.

By identifying high-potential concepts early, laboratories can focus validation planning on pathways that demonstrate clear computational viability, reducing unnecessary early animal screening.

A virtual aged tissue model for predicting intervention response

Designed as a Next-Generation NAM (New Approach Methodology), GEROTWIN aims to reduce early animal screening by providing decision-grade computational evidence prior to in-vivo studies.

GEROTWIN is a foundation model of physiologically aged tissue that predicts cellular responses to geroprotective interventions before laboratory validation begins.

The platform simulates counterfactual intervention scenarios, ranks candidate therapies using calibrated uncertainty estimates, and helps researchers focus experimental resources on the most promising translational pathways.

Methodology

How GEROTWIN works

From aged tissue to prioritized interventions

01 / Model

Model the aged biological state

GEROTWIN transforms high-dimensional biological data into a computational representation of aged tissue, creating the foundation for predictive intervention modeling.

03 / PRIORITIZE

Rank with calibrated uncertainty

Predictions are accompanied by calibrated uncertainty estimates, enabling evidence-based prioritization for downstream validation.

02 / SIMULATE

Simulate intervention concepts

Candidate geroprotective interventions are evaluated in silico to predict biological responses before experimental testing.

Targeted Applications

Target Applications

GEROTWIN supports decision-making across early translational research by prioritizing intervention concepts, guiding validation strategies, and reducing unnecessary experimental screening.

Intervention Prioritization

Validation Strategy

Resource Optimization

Rank candidate geroprotective interventions before laboratory validation using uncertainty-aware computational predictions.

Design efficient experimental pathways by focusing on the highest-confidence computational outcomes.

Reduce unnecessary screening and allocate laboratory resources where they create the greatest scientific value.

Collaborative Research

Partner with ArcentLabs

We seek scientific and validation partners to advance computational ageing biology. Connect with our team to discuss GEROTWIN integration.