Case Study | Clinical-Stage Cell Therapy
Unified process data across process development and MSAT.
A growing clinical-stage biotech developing in vivo cell therapies needed to scale bioprocess operations across two sites, five bioreactor systems, multiple vendors, all spanning production scales from 2L to 200L. They deployed Invert to replace their historian with a platform built for batch-based bioprocess operations. Invert connected directly to all five bioreactor systems via OPC-UA/DA and integrated with the company's ELN — no middleware, no custom ETL, no ongoing maintenance burden.
About the Company
Before working with Invert, the company had invested in a traditional data historian for bioprocess data collection and standardized on an ELN for experimental records, batch metadata, and analytical results. The systems worked, but connecting them did not scale.
The Challenge
Building a custom solution in-house would have cost $200K to $400K, taken 12 to 18 months, and demanded engineering resources they didn't have. Three problems compounded into one.
Fragmented process data and experimental context
Extracting batch-aware insight across multiple bioreactor platforms and production scales required increasing manual effort, custom data pulls, and spreadsheet-based reconciliation. Scientists had to match online bioprocess data with the correct batch ID, sample-level results, and process conditions before any analysis could begin. The process grew more time-consuming and error-prone as they scaled the team and throughput.
Increasing cost and complexity across systems
The company operated a diverse bioprocess stack spanning multiple vendors and scales, from small-scale automated systems through 50L pilot and 200L production bioreactors. Each additional system increased the marginal cost of analysis: parameters were named differently, sampled differently, and required custom reconciliation.
Batch-based workflows on continuous infrastructure
Without native batch awareness, scientists relied on manual batch-window identification, API-based data pulls, and spreadsheet-driven joins to bring historian data into their analysis workflows. The historian was built for continuous monitoring, not the batch-based reality of bioprocess operations.
How Invert Solved It
The team deployed Invert to replace its historian with a platform built for batch-based bioprocess operations. Invert connected directly to all five bioreactor systems via OPC-UA/DA and integrated with the existing ELN. It now serves as the team's primary environment for process monitoring, analysis, and visualization, harmonizing data across every platform with zero dedicated data engineering headcount.
Batch-aware monitoring, out of the box
Invert connected directly to all five bioreactor systems via OPC-UA/DA and integrated with the existing ELN. Scientists can monitor live runs and immediately see which product, process version, and conditions belong to each batch. Batch definitions and metadata come directly from the ELN, so the source of truth stays in one place.
Data harmonization across vendors and scales
Because every system speaks a different language, Invert's native ontology manager maps equivalent parameters across all five bioreactor platforms to a single canonical metric. The same measurement might be labeled differently in every system; Invert resolves them to one standardized reading continuously and without manual intervention.
Zero workflow disruption, less system complexity
The deployment required no changes to validated systems, no schema modifications, and no retraining. Consolidating data acquisition, monitoring, analysis, and visualization into one platform removed an entire layer of manual data prep. Scientists now spend time on process decisions, not data assembly.
The Bioprocess Cockpit
From legacy historian to production-ready platform
The alternative was a systems integrator engagement: low-to-mid six figures, 12 to 18 months, and a deliverable that would be static the day it shipped. Instead, the team deployed a production-ready platform in a fraction of the time.
As the company advances toward commercialization, all five bioreactor systems feed into a single environment, from 2L development runs through 200L production batches. The data infrastructure grew, but the team didn't have to.
Results
Invert gave us the confidence to scale our data infrastructure without needing to scale our internal headcount.
Avoided up to $400K in third-party integration and custom development costs.
Reduced batch analysis preparation from days to near real-time.
Enabled scale-up from 2L to 200L across two sites with no workflow disruption.
Five bioreactor platforms unified into a single monitoring and analysis environment with zero dedicated data engineering headcount.