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Euretos

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About Euretos

Euretos provides contract research services and cloud access to the Euretos AI Platform for disease and drug research. We use AI technologies such as machine reading and learning, to create data driven disease insights into the systems biological, molecular mechanisms that drive phenotypes, disease pathology, toxicity and drug response. 


These data driven disease insights help researchers to be more effective in fundamental disease research, preclinical discovery & clinical validation of targets, biomarkers and indications. 

Our machine reading technology interprets and connects hundreds of public databases and millions of scientific publications to provide the largest knowledge base where multi omics data is interlinked to literature, patents, experimental and clinical evidence

State-of-the-art Machine & Deep Learning algorithms for cell type deconvolution, co-expression prediction and target perturbation analysis leverage this unique knowledge base to create highly insightful molecular disease models.

These unique assets enable (pre)clinical researchers to take a translational systems biology approach by connecting multi-omics interactions, through cell-type involvement, to downstream pathways, phenotypes and disease pathologies.

Our Services (3)


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Computational Drug Repositioning

Price on request

Euretos has developed in silico methodologies for Indication Expansion: the identification of (alternative) indications for a known target. We perform an in silico perturbation analysis to identify proteins that can correct the dysregulation profile associated with the disease. As part of this procedure, Euretos continuously develops and expands molecular disease models as new data becomes available. 


Approach - In the first step, we construct an in silico perturbation model for target modulation (inhibition or stimulation), based on experimental data from the customer, relations in our platform and public data on perturbations such as the Connectivity Map of the Broad Institute. This model aims to quantify the functional consequences of the target modulation in a cell-type dependent manner. 


In the second step, we will use the target perturbation model to evaluate the downstream consequences of target modulation in each molecular disease model that has been compiled by Euretos. A molecular disease model identifies for a specific disease the dysregulated genes, proteins and pathways as well as the underlying cell types and interactions between cell types that are dysregulated. Perturbation of the target using the established mechanism of action is evaluated in each molecular disease model to predict efficacy of target modulation for each indication. The different indications are ranked using a score that quantifies to what extent target modulation is predicted to correct the dysregulation associated with each indication.


For indication expansion, we use perturbation analysis to identify which disease indications are most closely associated with the target of interest. 


Deliverables - As a result of the process, we will provide a list of indications ranked using our target-indication score. It builds the case for several indication candidates, elaborates on the molecular drivers for each of the candidates and on the various evaluation criteria. For a number of selected indications, we will provide a description of the perturbation and disease model, as well as the evidence supporting the indication ranking in a report in the form of a research paper. The report will contain references and links to publicly available knowledge and data supporting the premise of the indication candidate.


Furthermore, the customer will be able to review the target/indications with the gene disease page and the gene detail page in the Euretos AI platform (https://ask.euretos.com) for a 1-month period.


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Computational Drug Target Identification

Price on request

Euretos has developed in silico methodologies for Target Identification: the identification of (alternative) targets for a known indication. We perform an in silico perturbation analysis to identify proteins that can correct the dysregulation profile associated with the disease. As part of this procedure, Euretos continuously develops and expands molecular disease models as new data becomes available. 


Approach - Conceptually, our approach consists of two steps. In the first step, we will construct an in silico molecular disease model for the indication, based on public and/or private data. A molecular disease model identifies for a specific disease the dysregulated genes, proteins and pathways as well as the underlying cell types and interactions between cell types that are dysregulated, to the extent that available data allows this. 


In the second step, we perform a perturbation analysis for each candidate target using the disease model developed in the first step. The purpose of the perturbation analysis is to identify targets that specifically modulate the genes that are dysregulated in the disease, as described by the disease model. Where possible, we take into account the mode of action and cell type specific effects of the target modulation, and aim to predict the extent to which the dysregulation associated with the disease is corrected. The different targets are ranked using a score that quantifies the degree of modulation of the disease genes.


Deliverables - Euretos will provide a list of targets ranked using our target-indication score. It builds the case for several target candidates, elaborates on the molecular drivers for each of the candidates and on the various evaluation criteria. For three selected targets, we will provide a description of the disease and perturbation model, as well as the evidence supporting the target ranking in a human-readable report in the form of a research paper. The report will contain references and links to publicly available knowledge and data supporting the premise of the three target candidates. 


Furthermore, the customer will be able to review the target/indications with the gene disease page and the gene detail page in the Euretos AI platform (https://ask.euretos.com) for a 1-month period (access for 2 users will be included in this pilot).


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Computational Systems Biology

Price on request

The Euretos AI platform is the premier data driven platform for disease and drug research. It provides novel insights through unique Search, Analytics, Relation Map Analysis and Target Assessment & Discovery applications that leverage the world’s largest AI integrated knowledge base. 


World's largest AI-integrated knowledge base

We use AI to connect over 275 life sciences databases and millions of publications and patents. This gives you access to the largest AI-harmonized knowledge base for molecular disease and drug research 


Intelligent and proactive Search

Our AI driven search engine automatically includes all synonyms of your search terms and finds database entries that Google can’t display. It gives you a list of all related terms to your query in 100+ categories, ranked on number of references. It interprets your queries and provides suggestions for what to explore next. Search also includes the following workflows: 


- Target Analysis

- Gene-Disease Analysis

- Set Creation


Powerful and intuitive Analytics

Euretos Analytics evaluates your experimental data against the entire knowledge base. It combines sets to create informative set overlays. These sets can either be uploaded by you or created using Search. It analyzes and ranks these overlays giving you new insights into underlying common factors, differentiators and associations. Analytics also includes the following workflows: 


- Gene Set Enrichment

- Gene Set Ranking

- Transcription Network Analysis


Visualized, low-bias Relation Maps

The Relation Map visualizes relations from databases, such as molecular interactions, expression values and human annotations. These visual maps enable unique, low-bias insights such as term clustering, indirect associations and term centrality. This way you can test your hypothesis, create your own disease models and share these as powerful visualizations.


Target Discovery in cancer

We have created powerful workflows to discover targets in oncology for compounds, antibodies and bispecific antibodies. These enable you to discover targets with high tumor expression and low expression in normal tissues to find selective, tumor specific targets. Two workflows are offered:


- Target Discovery for Cancer

- Target Discovery for Bispecific Antibodies.





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Arie Baak

Co-Founder

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