New collaboration between Monarch Initiative and Critical Path Institute: Working towards improving drug discovery for rare diseases
For rare disease patients, limited drug treatments are available and research on specific diseases is often scarce. Improving access to drug treatments or repurposing existing drugs is a high priority for rare disease clinicians and researchers. The Critical Path Institute (C-Path) is a biomedical non-profit partnered with the FDA to accelerate medical product development for underserved disease areas, including rare diseases. Members of the C-Path Data Science team in the Data Collaboration Center (DCC) are contributing to the Rare Disease Cures Accelerator-Data and Analytics Platform (RDCA-DAP), which enables sharing of clinical rare disease data in an accessible data portal, where curated data are made freely accessible to researchers, clinicians, and patients for downstream analysis and new knowledge discovery. A representation of the portal is shown below.
Members of Monarch’s technical and curation teams are collaborating with the Data Science team at C-Path to work towards our shared goal of improving treatments for rare disease patients. Datasets in the RDCA-DAP include patient registry data, clinical trials, and observational studies. Data received by the RDCA-DAP undergo a rigorous curation process where the data are standardized against common data models, including clinical standards (OMOP CDM or CDISC SDTM) and OBO Foundry biomedical ontologies. As part of this process, the C-Path Data Science team developed the Critical Path application ontology (CPONT), which is used for data standardization and for RDCA-DAP’s underlying knowledge graph (KG). CPONT imports 17 OBO Foundry ontologies, including several Monarch Ontologies, to cover domains such as diseases (Mondo Disease Ontology), phenotypes (Human Phenotype Ontology), anatomy (Uberon Anatomy Ontology), and medical treatments (Medical Action Ontology).
The Monarch team is providing consultation on developing the C-Path knowledge graph and its alignment with the Monarch KG to integrate phenotype, disease, and gene data across the two platforms and improve data discoverability across human and animal model data. Additionally, we work collaboratively to improve and extend the mappings between the OMOP standard and OBO ontologies (extending the work of the OMOP2OBO project.) With the ultimate goal of developing new treatments for rare disease patients, this work improves the standardization of heterogeneous datasets to allow for enhanced querying across datasets and provides the ability to ask complex questions of the data.
