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Beckman Coulter
Vi Cell Metaflex

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Lab Devices
Beckman Coulter
Vi Cell Metaflex

Analyze Vi-CELL MetaFLEX Bioanalyte Analyzer data with AI

Rapid measurement system for culture media metabolites and blood gas parameters in cell culture monitoring

Sample Volume: ~65 μL samples

Analysis Time: ~60 seconds per sample

Parameters: pH, pCO2, pO2, glucose, lactate, electrolytes

Design: Small benchtop unit

Data Export: CSV via USB/network/LIMS

Get Started For Free Fully compatible with Sourcetable

Quick Start Integration

Get your Vi-CELL MetaFLEX data into Sourcetable in 3 simple steps

Export Data

Export metabolite analysis data from your Vi-CELL MetaFLEX via USB or LIMS integration to CSV
Upload to Sourcetable

Import your bioanalyte data into Sourcetable for metabolic analysis
Start Analysis

Perform automated metabolic profile analysis and feeding strategy optimization

File Format Compatibility

Optimized for metabolite analysis with reference range validation and trend tracking

.csv

Raw Data

Full Support Immediate readouts with reference ranges, trend tracking for metabolites, built-in quality checks

Pre-built Analysis Workflows

Specialized workflows for metabolic monitoring and culture optimization

🔬

Metabolic Profiling

Comprehensive analysis of culture media metabolites and biomarkers

Metabolic Profiling Culture Media Biomarker Analysis

📊

Culture Monitoring

Real-time monitoring of culture conditions and metabolic status

Culture Monitoring Real-Time Analysis Metabolic Status

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Feeding Strategy

Optimization of feeding strategies based on metabolic data

Feeding Strategy Optimization Process Development

Technical Requirements

Software Dependencies

Vi-CELL MetaFLEX Rapid bioanalyte analyzer for culture monitoring
Control Software MetaFLEX software with LIMS connectivity
File Export Format CSV via USB/network/LIMS
Applications Biopharma, cell culture, bioprocess

Sourcetable Libraries

Data Processing pandas, numpy
Statistical Analysis scipy, statsmodels
Visualization matplotlib, plotly
Metabolic Analysis scikit-learn, seaborn

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