Number of employees
Our customer is a leading, global pharmaceutical company that is committed to delivering innovative medicines to improve patient outcomes. They are heavily focused on oncology.
Our customer commissioned an internal, cross-disciplinary project in order to better understand biological mechanisms of immuno-oncology (I-O) resistance in cancer patients and to bolster biomarker identification. In contrast to previous approaches for studying I-O resistance, greater quantities of data and multiple clinical trial datasets needed to be harmonized and combined.
This presented an initial challenge due to the varying quality of the datasets: some sets were generated by internal pipelines, some by vendors, some already pre-formatted by ingestion scripts, and others were generated years ago by now obsolete pipelines.
Using ONTOFORCE’s DISQOVER, our customer was able to gather all sample information and connect the data within the DISQOVER knowledge graph. They were also able to combine their own ontologies with public ontologies. This ensured metadata followed controlled vocabularies and FAIR principles, and the provenance of the data source was recorded in DISQOVER to maintain full traceability.
As a result, curated datasets are now available for several studies and modalities. These datasets are being used to generate several new insights in I-O through different approaches (novel biomarker detection, cross-studies differential gene expression).
Using DISQOVER has reduced the time spent on curating and harmonizing disparate datasets.
DISQOVER is helping our customer to identify trends and relationships between different datasets, when previously they could only look at single project data in isolation.
Enhancing novel biomarker identification and widening the understanding of biological resistance in immuno-oncology.