Workflow Composer

Optimize experimental protocols using Bayesian optimization and active learning

Optimization Configuration

Configure optimization strategy and objectives

Optimization Method

Objective Function

Budget (Experiments)

Acquisition Function

Optimization Parameters

Growth Factor Conc.continuous

Range: 0-100 ng/mL

Temperaturecontinuous

Range: 35-39 °C

Seeding Densitycategorical

Options: Low, Medium, High

Experiments Run

0/50

Current iteration

Best Score

—

Maturation level

Improvement

—

vs. baseline

Est. Time Remaining

—

To completion

Optimization Convergence

Best objective value over iterations

Current Best Parameters

Optimal configuration found so far

Run optimization to see results

Predicted Outcomes

Expected results with optimal parameters

Run optimization to see predictions