At Epigene Labs, we are committed to transforming today’s data into tomorrow’s treatments.
We believe that the wealth of available data is a treasure trove of information that must be made accessible for research.
By enabling data-driven drug discovery, we aim to accelerate breakthroughs in precision oncology.
Our mission is to provide the biopharma industry with valuable solutions that ultimately lead to more effective and personalized treatments for cancer patients.
Since 2019, Epigene Labs has achieved several key milestones that underscore our commitment to innovation and excellence. From the successful launch of our comprehensive cancer patient data atlas to the development of mCUBE, our groundbreaking computational platform, we have consistently pushed the boundaries of what’s possible in immuno-oncology research.
Secured pre-seed funding, led by Daphni and Majycc Innovation Santé/UI Investissement
Joined the Launch Lab X (LLX) program at the Harvard Innovation Labs
Partnered with Institut Curie on ovarian cancer transcriptomics research
Completed a seed funding round led by XAnge
Awarded the EIC Accelerator grant of the European Commission
Announced a partnership with Servier focusing on indication prioritization
Won the Concours d’innovation – i-Nov prize and grant from Bpifrance
Presented research at the ASH annual meeting with UCSF
Unveiled InMoose at the AACR annual meeting
Secured financial backing from the EIC Fund of the European Comission
Published pyCombat in BMC Bioinformatics
Unveiled first research results leveraging large language models at ESMO-TAT
Released 10th publication at AACR annual meeting
Since our inception, we have consistently advanced the field of secondary data analysis (SDA) by tackling some of its most challenging scientific questions. These include determining the appropriate amount of data for specific biology questions, identifying the best methods for combining datasets, and exploring which data types can be integrated to address specific biology questions more effectively.
Our ongoing computational research projects have been instrumental in developing mCUBE, significantly influencing numerous translational research projects, and making substantial contributions to the broader scientific community through our open-source initiative, InMoose.
