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Target discovery based on unique data
Target DiscoveryFinding the needle in the data stack
The excellent quality of our matched tumor and normal tissue samples enables in-depth multi-omics analysis, resulting in very high-quality data. Our unique and comprehensive cancer database is the foundation of a streamlined process that significantly enhances the likelihood of uncovering hidden patterns and identifying disease-related, therapeutically novel drug targets.
Target DiscoveryOur process helps identifying targets that can be drugged with low toxicity and high efficacy.
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Integrating multi-omics and clinical data
Our comprehensive clinical patient data and in-depth multi-omics data of matched tumor and normal tissue provide us with a distinct starting point for a holistic process to discover novel therapeutic targets. Analyzing these data sets independently usually only gives a partial view of the complex reality of cancer.
By integrating the different data levels, we generate a comprehensive picture of the underlying biological processes, enabling an innovative cancer R&D approach.
Data integration
- Pre- and post-surgical clinical data
- Whole genome sequencing
- Whole transcriptomics
- Proteomics
- Phosphoproteomics
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Multivariate data analysis
By implementing state-of-the-art biomathematical, bioinformatic, and biophysical algorithms, we have developed a workflow to analyze vast amounts of data in short time frames. Patterns and targets discovered in our data are cross-referenced with publicly available databases. Through protein-protein-interaction network analysis, functional protein models are produced from which our targets are selected.
Graph analytics
- PPI networks
- Survival analysis
- Mutation and expression profiles
- Functional protein module detection
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Selecting high-potential candidates
The real skill in AI-supported biological research is constantly recognizing that humans need to stay in control of the scientific decision-making process. That’s why we rely on an experienced team of scientists to select the right targets to be pursued. To reduce the dropout rate throughout the drug development pipeline, we integrate biological and clinical knowledge with advanced statistical and analytical tools. Selected targets then enter the validation process with subsequent assay development.
Target selection process and criteria
- Protein module interpretation
- Biological and therapeutic context
- Target pathway analysis
- Druggability assessment
- Patent landscape review
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