Epigene Labs

Epigene Labs

Paris, France· Est.
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Private Company

Total funding raised: $2.5M

Overview

Epigene Labs is a Paris-based data and analytics company building a foundational resource for precision oncology. Its flagship product, the mCUBE platform, leverages artificial intelligence and bioinformatics to harmonize over 2 million curated multi-omic patient profiles from public and likely private sources into a unified, searchable database covering more than 30 cancer types. The company operates on a B2B platform model, selling data access and insights to accelerate the R&D pipelines of drug developers, with the goal of reducing development timelines and increasing the probability of clinical success. Epigene is privately held, ISO 27001 and HDS certified for data security, and is backed by a team with strong expertise in computational biology, translational research, and product development.

Oncology

Technology Platform

mCUBE: An AI-powered bioinformatics platform that integrates and harmonizes multi-omic cancer data from over 100,000 patient samples across 1,000+ datasets into a unified resource for drug discovery and development.

Funding History

1
Total raised:$2.5M
Seed$2.5M

Opportunities

The rapid growth of precision oncology and AI-driven drug discovery creates strong demand for high-quality, integrated multi-omic data.
Partnerships with cloud/AI platforms like Databricks provide visibility and access to a tech-savvy customer base.
The company's ISO/HDS certifications are a key differentiator for handling sensitive health data in the European market.

Risk Factors

Faces competition from other data aggregators, public resources, and in-house pharma bioinformatics teams.
Commercial success depends on convincing large pharmaceutical clients with potentially long sales cycles.
The platform's value is tied to continuous, costly data curation and technological advancement to avoid obsolescence.

Competitive Landscape

Competes in the bioinformatics-as-a-service space against companies like Tempus, Sophia Genetics, and DNAnexus, as well as large public data repositories. Differentiation is based on depth of curation, multi-omic integration, AI-powered analytics, user-friendly platform design, and strong data security credentials.