SIX technological steps
to enhance your research

Innovation, the key to performance

Our solutions are the result of over a decade of expertise in functional genomics. The process we developed has been optimized to produce powerful, reliable results at close-to-physiological conditions.


Extensive expertise in cellular biology and culture optimization in a wide range of cellular models.

3D High-Content Screening

Integrated and automated process for drug profiling on 3D tumor models. The traditional method for studying cancer in vitro is to grow cancer cells in 2-D monolayers on plastic. Yet, tumor microenvironment is very complex and heterogeneous and the 2-D artificial conditions do not sufficiently mimic how the physiological tumor will react to a drug. Spheroids, self-assembled aggregates of cancer cells, are one of the most promising models. This model naturally mimics tumors, is simple to form and allows a reproducibility of the measured phenotypes (cell proliferation, cell viability...). The major challenges for the use of spheroids in high-throughput functional screening tend to have a visualization system specifically committed to 3-D structures and a robust and reliable data analysis. Here we present an innovative and powerful functional screening process dedicated to 3-D tumor models.
3 types of breast organoids were treated with Everolimus (2 concentrations 100 µM in red 10 µM in green). Organoids were labeled with 2µM CellEvent Caspase 3/7 Green Detection (apoptosis). Images were acquired after 48h of everolimus treatment.
A- Caspase 3/7 labeling ctrl B- Composte – brightfield and Caspase 3/7 C- Caspase 3/7 labeling after Everolimus treatment (100 µM) D- Composite after Everolimus treatment (100 µM)
We propose to analyse your compounds with the standard conditions belowed:
  •     5 dilutions in triplicates.   
  •     Treatment times upon request.   
  •     5 readouts included: area, apoptosis (Caspase 3/7 labeling), ATP assay (WST-1 based assay),   
  •     cytotoxicity, growth inhibition.   
  •     4 packs: 6 – 24 – 48 and… more compounds or with your specific conditions.  
  •     Several hundreds of 3D tumor models per well.   
  •     Automatic analysis for different morphologies of 3D tumor models (grape-like, mass, round…)   
  •     New robust statistical data processing dedicated to physiological models.  
  •     Validate compound efficiency with more physiological tumor models.   
  •     Use an integrated process from 3D cultures to data processing.   
  •     Improve the reliability with our automated platform.  

RNAI-based screening

List of provided siRNA libraries All our libraires are tested with a 80% efficiency rate and are non-pooled siRNAs.
  •     1. Genome-wide  (human genes)   
  •     2. Cell death and stress response library (human genes)   
  •     3. Cancer library   
  •     4. Kinase library ((human genes)   
  •     5. LNA library: genome-wide (micro-ARN)   
  •     6. Phosphatase library   
  •     7. Nuclear Receptors Library   
  •     8. Customized library  
METHOD Functional screening of 7000 genes

Imaging system

  •     High-content analysis.   
  •     Cells segmentation.   
  •     Integrated analysis, visualisation software.   
  •     Fluorescent and brightfield measurement.  
  •     True 3D image reconstitution.   
  •     High resolution.   
  •     High content imaging.   
  •     Fluorescent and brightfield measurement.  

Data analysis

Phi-score - a new cell-by-cell score Innovative statistical data processing dedicated to High-content Screening using physiological cellular models. Cell function is influenced by parameters like genetic material and micro-environmental stimuli. Our aim is to conduct screening on cells (primary cells from healthy or tumor tissue) with a genetic background as close to actual physiological conditions as possible. These physiological cellular models present technical contraints:
  •     Low transfection rates.   
  •     Low number of cells or organoids.   
  •     High-variability.  
Phi-score 3 times less false positive To overcome these challenges, we developed Phi-score. A robust statistical score, based on an individual fluorescence rank. This score takes into account:
  •     The number of cells or organoids per well.   
  •     The number of wells per treatment.   
  •     The response variability between wells.  
Example: Validation of the Lapatinib (Tykerb, GSK) effect on HER2-positive breast cancer
Genel's process is particularly powerful
in the challenging culture conditions of physiological models