Genialis is a data science company discovering new ways to treat diseases of high unmet need.
Our mission is to deliver benefit and hope to patients and their families.
We are Biologists. We are also Technologists. We have combined our expertise in both biology and Artificial Intelligence to build a biomarker discovery platform that models underlying disease biology. Together, we are enabling the development of the next generation of cancer therapeutics, to serve patients in need.
Our method is to leverage biomedical data and advanced analytics to help pharma companies develop more effective drugs with higher probability of clinical success, and diagnostics companies to deploy tests that lead to better treatment decisions.
Biomarker discovery challenges
Diseases are complex and patients are unique
- Determines which features to measure
- Constructs a model that learns signal and excludes noise
Disparate data sets
Evidence comes from all corners
- Weighs information content and consistency
- Harmonizes data across assay platforms, disease types, experimental models and clinical cohorts
Ensuring robustness on new patient data
- Confronts bias to enable cross-data comparisons
- Evaluates performance on retrospective, prospective and proxy data
While most biomarkers predominantly rely on a single analyte, we train our models on high-dimensional and/or multimodal data—such as RNA-seq gene expression profiles—that better capture the underlying biological complexity.
Unlike typical approaches, we model biology first, rather than drug response. This approach allows us to develop and validate biomarkers while drugs are in clinical development.
Biomarkers improve response rates
In both real world and clinical trial settings, a greater proportion of patients benefit when selected by biomarkers
Immune checkpoint inhibitor response rate1:
Without biomarker patient selection
With biomarker patient selection
Progression of drug to next clinical phase2:
Without using biomarkers to stratify patients
With using biomarkers to stratify patients