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Move promising molecules from shake flask to pilot fermenters 5x faster

Lemnisca's Tune accelerates early-stage fermentation programs by turning data into decisions. Stop wasting runs on blind optimization. Let Tune guide your next experiment using what your data has already taught it, so you hit productivity targets faster.

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01Audit thedata02Model theprocess03Optimize04Pilot-readyprocess01 / 04

PROBLEM

Biology proven. Bioprocess still unproven.

Most programs don’t stall because the molecule has no potential. They stall because the process is not productive, reproducible, and ready for pilot-scale investment.

The molecule works. The process is not ready.

A great molecule earns no revenue until the process can deliver it at scale.

Productivity misses the pilot threshold.

The process is not producing enough, fast enough, to make the unit economics work.

Runs don't reproduce cleanly.

Every batch still feels like a new experiment, so each cycle starts from scratch.

Pilot investment needs confidence.

Larger reactors and larger budgets need evidence that the process can deliver beyond the bench.

Budget goes in. Clarity does not come out.

Tune replaces guesswork with a systematic path to pilot.

It establishes your baseline, finds the variables that move productivity, and uses every run to build the case for pilot-scale investment.

Establish the baseline.

Tune first determines what your process reliably does today: productivity, variability, assay confidence, and run-to-run repeatability.

Find the process levers.

Tune identifies which variables are actually moving titre, yield, productivity, and reproducibility.

Turn R&D runs into process evidence.

Each experiment is designed to reduce a specific uncertainty and move the process closer to pilot-scale acceptance.

Move from proven molecule to proven bioprocess.

Tune delivers a productive, reproducible process ready for pilot-scale investment.

Tune explores 1000x the design space.
Run fewer but smarter experiments.

Tune replaces slow wet-lab loops with an accelerated loop that samples 1000× more of the design space, so your physical runs are the winners from thousands of virtual ones.

Without Tune
Run experiments
→
Analyse data
→
KPIs
achieved?
→Yes→
Pilot
Run experiments
↓
Analyse data
↓
KPIs
achieved?
→Yes→
Pilot

~10

Physical experiments per loop — guided by intuition, high uncertainty

With Tune
Run experiments
→
Build predictive model
→
Run virtual experiments
→
Validate recommended runs
→
KPIs
achieved?
→Yes→
Pilot
Run experiments
↓
Build predictive model
↓
Run virtual experiments
↓
Validate recommended runs
↓
KPIs
achieved?
→Yes→
Pilot

~10,000

Virtual experiments per loop — only targeted physical runs needed

Preparing for pilot scale?

See what your current data says about your path to pilot.

Request a Tune fit conversation

HOW TUNE WORKS

Audit, model, optimize, deliver.

Tune combines bioprocess engineering, process data, modelling, and experimental strategy into a structured program that takes your process from where it is to pilot‑ready.

Audit

01

Tune reviews the strain, media, recipe, assays, prior data, and the constraints that define the current process.

Model

02

Tune builds a predictive model of your fermentation, calibrated to your strain biology, process design, and reactor physics. The model explains current performance and predicts how it responds to change.

Optimize

03

Each cycle, Tune simulates thousands of experiments to find the conditions that increase productivity. Your team validates the top candidates in the wet lab, and the model gets sharper with every round.

Deliver

04

Tune hands over the optimized process conditions, expected performance, remaining risks, and the pilot run protocol.

What Tune delivers

Tune delivers a pilot-ready process.

Tune delivers optimized process conditions, a pilot run protocol, and model-backed expectations. Everything your team needs to execute the first pilot run with confidence.

Pilot-Ready Process Package

Optimized process window.

The recommended process conditions, critical ranges, control logic, and expected bench-scale performance.

Helps the team know what to run and where the process has room to operate.

First pilot run protocol.

A practical plan for what to run, what to measure, what to watch, and how to decide during the pilot.

Turns bench learning into a practical first pilot execution plan.

Expected performance and risk signals.

Model-backed ranges, key uncertainties, early warning signals, and success criteria for the pilot run.

Sets expected ranges, warning signs, and success criteria before the batch begins.

If your process is the bottleneck, let's talk.

We're running a limited number of free 10-day sprints for teams between early data and pilot readiness.

Our team reviews your current data, identifies what's blocking pilot readiness, and maps the exact next steps needed to get there.

Request a Tune fit conversation

Frequently Asked Questions

Tune is built for teams with promising early fermentation data but no mature, reproducible process yet. You've seen signals in flasks or early bioreactor runs, but can't reliably replicate the good ones or systematically avoid the bad ones. If you're asking "what should we test next?" or "are we ready to optimize?", Tune is a fit. If you already have a stable baseline and controlled DoE experience, you might want to explore our full learning loop iteration program, we can discuss the right entry point during the fit conversation.

Any format works. Send us what you have: Excel sheets, ELN exports, PDFs, Word docs, scanned notebook pages, CSV files etc. We'll pull out what we need: strain info, run conditions, measurements, recipes, assay notes. The sprint is format-agnostic. If you have it, we can work with it.

7-10 days from data handoff to interactive report. You send us what you have (batch records, recipes, assay notes). We run a statistical, biological, and engineering review. You get back a verdict (ready / fix baseline first / improve assays / defer), a risk map showing where your process is fragile, data gaps prioritized, and the next experiments we'd recommend. One call at the end to walk through it.

Understood. We sign NDAs as standard. Data stays secure, access-controlled storage. If you have extra compliance requirements, we can discuss those before you send anything.

Then we tell you exactly why and what to fix first. The report will say "stabilize your baseline before optimization" or "tighten your assay precision" or "run 3 more replicates at the current condition", whatever the actual blocker is. You'll know whether to spend the next 2 months on reproducibility, analytics, or earning more data. That's the point of the sprint: don't start optimizing a system that isn't ready to be optimized. A "not ready" verdict saves you 6 months of wasted DoE cycles.

We move to the full Tune program: hybrid model-guided optimization with either your wet lab (we design, you run) or our integrated wet + dry lab (we run everything). The models update after every experiment round. Learning compounds. We'll scope the program during the sprint debrief call based on what your process needs.

You could, but your team is already running experiments and managing the program. The readiness sprint needs three disciplines working together: bioprocess engineering, modeling, and experimental design, which is a rare combination to have sitting idle. We turn a 4-6 week analysis (competing with everything else on your plate) into a 7-day focused review. More importantly, we surface the gotchas before you're waist-deep in optimization: unstable baselines, assay precision issues, wrong variable prioritization. Early detection saves months. That's the value.

TUNE

by

Lemnisca