AltraBio SAS


About us

AltraBio is an R&D company expert in analysis and interpretation of biomedical data in both preclinical and clinical development. Particularly focused on OMICS and Flow/Mass cytometry technologies, the goal of AltraBio is to unlock the value captured in large scale datasets generated in life science experimental studies.


Statistical Analysis; Automated gating; Cytometry; Omics; Clinical data

Business offer

AltraBio offers comprehensive services for omics and flow/mass cytometry data treatment and analysis.

- Flow/mass cytometry:
To maximise the value of your experimental results and to speed up your process, AltraBio’s offer covers the entire data analysis workflow from discovery and diagnostic studies to optimization of population identification processes.

* Gating step:
• AltraBio has developed a machine-learning-based approach able to reproduce your manual gating strategy to the full data of your study. This approach possesses numerous advantages:
o Standardized application of your gating strategy
o Enhanced reliability (reproducibility & accuracy)
o Removed subjectivity and variability of manual gating
o Reduced time of analysis

• AltraBio also proposes to use unsupervised automated gating strategies for the identification of cell populations and to describe the identified cell populations (e.g., statistics, hypothesis tests, advanced visualisation)

* Cross Sample Analyses:
• Initial import of raw data & gating workspaces from manual or automated gating, Preprocessing (e.g., compensation, normalization), Data Quality Control
• Predictive modeling, correlation identification, advanced visualisation, clustering
• Reagent panel selection, gating strategy optimization

- Omics:
The AltraBio's team implements and develops state-of-the-art and innovative methods for all kinds of omics studies (genomics, transcriptomics, proteomics,...).

• Time-proven and cutting-edge data analysis methodologies.
• Extensive quality controls to identify potential outliers and check for consistency with the experimental design, thus ensuring the relevance and quality of downstream analyses.
• Preprocessing and statistical analysis (e.g., identification of differentially expressed genes, SNP associations, microbiote analysis).
• Biological pathway approach from resources such as Gene Ontology (GO) and a homemade collection of novel sets based on publicly available gene expression data and associated literature.
• Biological interpretation in the context of the biological problem the experiment addresses.
• Comprehensive report summarizing the experimental observations, discussing the biological mechanisms underlying the observed effects.

Field of application
  • cellular immunotherapy
  • immunomodulators
  • therapeutic vaccines
  • biomarkers
Therapeutic application
  • genetic diseases
  • hematology
  • infectiology
  • immunology
  • oncology


  • Target Selection & Validation
  • Expression and pathway analysis of target
  • quantification of target
  • Immunotherapy Hit Discovery
  • Bioinformatics prediction & analysis
  • Immunotherapy Lead Generation
  • Pharmacology & Biological activity
  • Mode of Action
  • Therapeutic efficacy
  • Safety
  • Immunogenicity
  • Hypersensitivity & allergies
  • Immunotoxicology
  • Specificity
  • Preclinical biomarkers
  • Mechanism/Function
  • Mechanism of action
  • Safety
  • Specificity
  • Surrogate markers
  • Research exploratory Companion biomarkers
  • Bioinformatics prediction & analysis
  • Animal biomarkers
  • Human biomarkers
  • Predictive biomarkers
  • Treatment efficacy
  • Population stratification
  • Disease progression / follow-up
  • CMC
  • GLP compliance
  • Clinical Trials
  • Phase I
  • Phase II
  • Phase III
  • Phase IV
  • Clinical biomarkers
  • Predictive biomarkers
  • Treatment efficacy
  • Population stratification
  • Disease progression / follow-up
  • Safety
  • Surrogate markers
  • Disease progression monitoring


  • Service