Multi-scale models
Molecular, cellular, assay, process, and population scopes can be separated.
Programmable Life Surrogate
A digital surrogate framework for comparing trajectories, testing assumptions, and making uncertainty visible before translation.

Overview
Programmable Life Surrogate compares scenarios, sensitivity, expected value, and uncertainty so teams can prioritize experiments with the greatest information value.
Model scope
Molecular, cellular, assay, process, and population scopes can be separated.
Parameters and assumptions are tied to available evidence.
Alternative designs are compared under explicit conditions.
Model limits and drift remain visible to decision owners.
Workflow
Each transition creates a review point for evidence, assumptions, ownership, and next-step decisions.
Program fit
Public examples describe where a conversation may begin. Final scope, evidence requirements, availability, and access are confirmed through review.
Select experiments expected to resolve the most important uncertainty.
Compare candidate trajectories before physical execution.
Explore sensitivity and operational tradeoffs in controlled models.
Public evidence framework
Collaboration
Share the scientific or product context your team wants to evaluate.