Cypher AI for Process Development

Track fermentation, scale-up, and bioreactor runs with structured data, monitoring dashboards, and AI analysis.

Process development teams generate enormous amounts of time-series data — fermentation, bioreactors, downstream processing — but the data is locked into instrument-specific software, with handoffs to engineering and manufacturing that lose context. Cypher AI gives PD teams structured tracking from shake-flask screens to scale-up runs, with dashboards and analyses that follow the run, not the instrument.

How Cypher AI helps process development teams

One connected platform for the work you do today and the data you generate tomorrow.

Run tracking from shake flask to bioreactor

LIMS for fermentation runs with full lineage of strain, media, feed strategy, and operating conditions. Compare runs across scales with structured metadata, not file naming conventions.

Time-series data ingestion from PI, BioPAT, and Sartorius

Ingest historian and DCS data through pipelines. Align time-series across runs even when sampling rates and timestamps differ between systems.

AI-built monitoring dashboards

Build dashboards on demand — "compare productivity, yield, and titer across the last 12 runs by media condition." Engineering doesn't have to build it; PD scientists can ship it themselves.

Scale-up correlation analysis

Correlate small-scale screens to pilot and manufacturing scale through structured run metadata. Cypher's AI agent helps identify which lab-scale parameters predict performance at scale.

Audit-ready records for tech transfer

Every run, every change, every decision is traceable. When manufacturing asks "why did we change feed rate at 24 hours?", the answer is one click away.

A scale-up campaign in Cypher

1

Design the screen

Define the experimental design — strain × media × feed strategy — in the ELN. Cypher generates the run sheet and registers each fermentation in the LIMS.

2

Run and ingest

During each run, time-series data flows in through pipelines. A live dashboard shows OD, DO, pH, and feed rate per run, with anomaly flags.

3

Compare across runs

After the campaign, scientists compare runs through structured queries: best titer per media condition, fastest growth phase, highest carbon efficiency. Reusable analyses survive past the project.

4

Hand off to manufacturing

Tech transfer pulls full run metadata, decision history, and supporting analyses straight from Cypher. No re-creating the story from emails.

Bring the rigor of structured R&D data to your fermentation runs and scale-up campaigns.

Other use cases