Author: Data4Cure

Mapping immunotherapy resistance pathways with biomedically-informed AI [Data4Cure @ PMWC 2019]

Despite the groundbreaking success of immune checkpoint inhibitor (ICI) therapies in hard-to-treat cancers, still only a fraction of patients show long-term clinical benefit. With the rapidly accumulating molecular, pathologic and clinical data from clinical trials and cancer cohorts, the question is how to best leverage these data to identify better biomarkers of ICI drug response,…
Read more

Focus on nonalcoholic fatty liver disease and steatohepatitis pathways: data resources and analyses on the platform

A few weeks ago we wrote about the extensive updates to the CURIE Knowledge Graph (reaching 1 billion data-driven and literature-mined relations) and a new Data Resources framework integrating and semantically indexing thousands of biomedical datasets within the Data4Cure Biomedical Intelligence® Cloud platform. To demonstrate the power and utility of the new datasets and tools on the platform,…
Read more

Knowledge graph surpassing 1 billion biomedical relations and a new Data Resources framework

Greetings and Happy New Year! We are happy to report that the Data4Cure Biomedical Intelligence® Cloud and CURIETM Knowledge Graph are once again significantly expanding to help with a yet broader set of tasks in pharmaceutical R&D. With the updates this month, the CURIE Knowledge Graph is reaching 1 billion data-driven and literature-mined relations. And, we are introducing a new way to semantically organize and keep track of…
Read more

Focus on inflammatory bowel disease pathways: data resources and analyses on the platform

A few weeks ago we wrote about the extensive updates to the CURIE Knowledge Graph (reaching 1 billion data-driven and literature-mined relations) and a new Data Resources framework in DataHub for semantic integration and indexing of thousands of datasets. To demonstrate the power and utility of the new datasets and tools on the platform, this week…
Read more

Data4Cure @ PMWC 2018: Combining systems biology, machine learning and tumor evolution to improve biomarkers for IO

A key challenge in the field of immunotherapy is predicting which patients will respond to IO therapy either as a single agent or in combination with other treatments. Clinical and experimental strategies involve testing expression of individual markers or gene panels, assessing tumor mutation burden and MSI status, and more recently, approaches examining specific tumor…
Read more