One platform.
Multiple solutions.

From target discovery to clinical trial analysis, the Biomedical Intelligence Cloud is here for your research needs.

A wide range of apps

12+ apps to analyze public and private data

Continuously updated knowledge

Integrated knowledge from thousands of datasets and millions of publications

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Omics data management

Semantic data integration, management and search to find data quickly.

The Biomedical Intelligence® DataHub provides a comprehensive solution for managing public and internal data and analyses.

Thousands of pre-integrated public data resources

Easy integration and annotation of private data (UI and API access)

Fine-grained access control and sharing of data and analyses

Clinical trial analysis

Multidimensional systems and machine learning-based analysis of clinical trial data.

The Biomedical Intelligence® App Engine is routinely used in explorative analyses of complex multidimensional data from clinical trials.

Interactive analysis of multi-omics and clinical data

Advanced systems biology and machine learning apps

Contextual prior knowledge from thousands of prior studies and millions of publications

Network and pathway analysis

Deciphering disease and drug response mechanisms through multiscale network and pathway analysis.

Comprehensive analysis of transcriptomic and proteomic data to identify key pathways and networks in your condition of interest.

Differential expression and enrichment-based analysis of over 20 different pathway and network domains

Detailed pathway maps and hierarchical network views to facilitate interactive exploration and contextual understanding

Expanding beyond manually curate pathways to identify subnetworks and network modules underlying conditions of interest

Target discovery

Multidimensional data- and literature-based
target discovery and validation.

Target discovery and validation using continuously integrated knowledge extracted from thousands of datasets and millions of publications.

Target prioritization using multidimensional evidence summarized within and across data dimensions

Ontology-based hierarchical evidence integration and cross-referencing to facilitate verification and follow up analyses

Network and pathway views to facilitate contextual interpretation of integrated evidence

Drug repositioning

Global analysis of thousands of datasets to match drugs to disease signatures and help identify new indications.

Leveraging the CURIE Knowledge Graph to find non-obvious connections between drugs and diseases and identify drugs which may reverse disease states.

Based on data-driven evidence for thousands of diseases and tens of thousands of compounds

Interpretable data-driven approach

Cross-referenced to underlying data evidence allowing users to understand why connections have been made

Disease subtype analysis

Multidimensional molecular
disease subtyping and subtype assignment.

Identification and interrogation of disease subtypes discovered from multidimensional molecular data. Subtype assignment for new samples.

Advanced algorithms for subtype identification and subtype assignment from multidimensional data

Interactive visualization tools to explore subtypes and underlying features

Direct integration of clinical data to identify associations between subtypes and clinical outcomes

Single-cell and cell deconvolution analysis

Deep interrogation of cell type-specific mechanisms via single-cell and cell deconvolution analysis.

Analysis and interactive exploration of single-cell RNA-seq data. Identification and quantification of cell types represented in bulk mRNA data.

Comprehensive pipelines for scRNA-seq data processing, clustering and cell type assignment

Ability to integrate CITE-seq, ATAC-seq, TCR and BCR sequencing data

Cell deconvolution analysis from bulk mRNA data using seven competing algorithms

Predictive modeling

Combinatorial biomarkers and predictive models via interpretable machine learning modeling.

Predictive models for identifying combinations of key predictors underlying disease, drug response or other clinical outcomes.

Advanced algorithms for building predictive models from multi-omics data

Interactive exploration of trained models and underlying evidence

Emphasis on model interpretability

Constantly growing

Looking to solve other challenges?
We can help.

We are continuously working on new apps and functionalities and we love to get requests from our users. Our scientific and software development teams are always ready for a new challenge. Let us know how we can help!

Sound science

Agile development cycles

Strong technical team

Responsive and open-minded


Turn data into cures.

Leverage the Biomedical Intelligence® Cloud to turn data into actionable knowledge driving new cures.

Schedule your demo today