Synthetic customer trial

DOErecommendationand resultconcordance

Metastate recommends a focused DOE, analyzes returned results, and checks prediction concordance.

No confidential data used. Synthetic trial data. Historical data. DOE recommendation. Returned results and concordance.

Page 1 of 7

Historical data

Start from the historical runs a customer would already have.

Page 1 data gathered

Customer data starts as runs, factors, and measured outcomes

The synthetic dataset has 28 historical fermentation runs with strain, medium, feed, pH, temperature, DO, and final process readouts.

Measured run trajectory

Selected run facts

Page 2 process metrics

Raw measurements become decision metrics

Titer alone is not enough. The demo calculates yield, productivity, carbon efficiency, byproduct burden, viability proxy, and stress penalties before ranking.

Titer versus carbon efficiency

Screen-only ranking

Page 3 bottleneck analysis

Factor effects show where the next experiment should focus

This is intentionally practical: enough statistics to decide what to test next, not a heavy academic DOE interface.

ANOVA-style factor signal

Observed bottlenecks

Factor response map

Page 4 model review

Process data is translated into FBA-style constraints

The model layer checks whether the measured phenotype is feasible, which constraints are strained, and which high-titer runs are risky.

Selected run constraints

Model-adjusted ranking

Page 5 next DOE

The output is a small next-run plan, not a giant factorial

The system recommends 8 runs that test the main bottlenecks while staying close to feasible operating space.

Page 6 DOE results

Concordance is the proof step

The system does not stop at suggesting DOE runs. Once follow-up results return, it compares predicted outcomes with observed titer, yield, and byproduct burden.

Predicted versus observed titer

Result interpretation

Page 7 partner memo

Prospect-ready output

The final artifact is a concise recommendation package: what happened, what seems limiting, and what the next wet-lab run should test.

Assumptions and limitations

This demo uses synthetic data and a simplified model-review layer. It is meant to show the customer workflow and decision logic, not claim exact intracellular flux prediction. In a real trial, the model is configured from the customer's organism, GEM/SBML files, medium composition, historical runs, and assay context.