Data-driven target discovery and disease insight

TNO combines data- and AI-based text mining with in-house expertise to create a comprehensive report of a target intervention’s safety profile. Our in silico TSA is designed to uncover adverse effects of target modulation. We have enabled pharmaceutical, biotech and nutraceutical companies make the right strategic choices in target progression and de-risking for hundreds of targets.

TNO can provide evidence to support the value of a protein as a potential drug target, using data- and text-mining strategies and our own understanding of the mechanisms of disease. We combine our expertise with expression data, genetics and (pre)clinical observations to enable target nomination and validation, and ensure translatability to later human studies. We have provided a multitude of thorough, accurate, and customised TEAs to our clients and partners.

Companies that prefer to conduct in-house safety/efficacy assessments can still make use of TNO’s expertise. Our intuitive, web-based TargetTri platform efficiently extracts essential, target-centric information from multiple data sources, including PubMed.

Unlike other commercial data collection services or manual searches, TargetTri is enhanced with TNO’s deep understanding of disease mechanisms and our work on hundreds of TSAs and TEAs. We support AI-based searches with our own enriched terminology, allowing for optimal searching. The proprietary system also contains expert-based ontologies and guides data interpretation by weighing data relevance. This saves significant time and resources, as compared to manual searches.

True understanding of disease mechanisms is the key to uncovering novel targets for intervention. TNO’s unique approach combines our expertise with proven technologies – including data mining, system biology and AI algorithms – and (pre)clinical expression data to accurately map human disease networks and weigh pathological pathways.

Target candidates are then validated with in vitro strategies, including gene knock-outs and interventions. This discovery workflow was validated using MASH (pdf) (formerly NASH)/liver fibrosis, in which we identified multiple targets that attenuate fibrosis. TNO is now ready to work with partners to both further develop the identified MASH targets and to use our target discovery workflow to map other disease networks and therapeutic indications.

Reliable detection of (early) biomarkers of disease can mitigate – or even prevent – long-term damage from disease progression. We apply our understanding of the fundamental mechanisms of disease to identify tissue-specific (early) biomarkers for low-grade inflammation. The validation of our workflow resulted in the identification of key biomarkers for inflammation in liver and adipose tissue.

In addition, we applied this workflow to identify biomarkers for fibrosis in MASH (pdf). The blood test that can analyse these biomarkers without a liver biopsy has been patented. TNO is now eager to apply this approach to identify key biomarkers for other diseases.