Artificial Intelligence and multi-omics of dynamic 3D imaging to 

Unravel the molecular and cellular mechanisms driving tumor progession and resistance to treatment

Biomedical science has reached the era of ‘Big Data’ now allowing to better shape some of the main challenges that still limits the success of many clinical approaches in the oncology field: e.g. role of the microenvironment in tumor progression, patient heterogeneity, mode-of-action of immunotherapy or resistance to treatment. For these concepts understanding spatial-temporal organization of the tumors is key and thus requires of visualization techniques at single cell level: (live) microscopy. Modern advances in optical technologies now allow to generate complex imaging data, however the lack of appropriate tools or experts to process or analyze it, often leaves it unexplored. In imAIgene-lab we utilize modern artificial intelligence tools from distinct fields of computer vision, single cell technologies and data analytics to transform (dynamic) imaging data into meaningful information that can be exploited to study e.g. drug response prediction, combinatorial treatment in immune-oncology and personalized artificial-intelligence based diagnostics and treatment. 

Our computational developments are directed to solving three challenges of oncology:

While our main interest is (immune)oncology, our methodology is widely applicable to any field of biomedical science. Struggling with your complex imaging data? Contact us, we are always happy to collaborate.

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Bridging the gap between wet-lab and computational scientist.