Cell Line Development

The implementation of analytical techniques has revolutionized control of cell cultures during bioprocess manufacturing. The parameters used for monitoring cell cultures can be classified into four categories: cellular physiology, cellular environment, cellular metabolites and contaminant monitoring.

Cellular Physiology
Morphology | Viability | Density
Cellular Environment
T°C | pH | CO2 | Dissolved O2 levels
Cellular Metabolites
Nutrients | Byproducts | Cell-secreted products
Contaminants
Bacteria | Endotoxins
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Undoubtedly, all these techniques provide us with plenty of information about cell cultures. However, are they enough to understand the behavior of cells in their complex environment?

Example

Cell lines should give consistent productivity and product quality throughout the production process. Many factors such as shear stress may affect cell proliferation and activate genes associated with apoptosis (Bak, Bax, Caspase 3). Hence, the identification of genes expression level will help us to retro control cell culture by adding anti apoptotic proteins.

As for cell proliferation / apoptosis, gene expression level for genes implicated in metabolism and other signaling pathways can be monitored at GenSensor.

We help you defining biomarker panel adapted to your bioproduction, so you understand the modifications in gene expression level at different time points.

You’ll understand how your cells survive and function properly in the complex and noisy environment, and how they survive and behave appropriately with a complex transcriptome.

Check out our Proof of Performance Package

Biological PAT on-line

  • Per process : 12 sampling with GenSampler
  • 12 x [ RNA extraction + RNA
    sequencing + Full transcriptome
    analysis ]
  • Biomarker Intelligence | Bio-
    informatics | Signature identification
  • Project management
  • In line sampling (low contamination risk + low sampling artefact + less workload)
  • Kinetic study of Biomarkers
  • Process optimization (critical process
    parameters monitoring)

➡ Optimized process

  • Reduce tech-time dedicated to sampling.
  • No need to work nights and week-end
    for sampling.
  • Faster process optimization.
  • Less conditions to be tested.
  • Access to data driven performance

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