Research

Clean, validated data drives researchers to identify cohorts faster, generate reliable real-world evidence, and accelerate time to insight while building institutional credibility.

Clinical Trials

Typical requests from PI’s go to a limited data scientist pool and obtaining initial data pulls can take months, much less refining results. By enabling local control, open exploration, and scalable insight generation, CognomIQ bridges the gap between discovery and impact.

Assessing trial feasibility in your market or catchment?

Cohort Builder:

  • Enables users to define and compare patient cohorts using a wide range of criteria drawn from different dimensions of the patient–cancer center relationship, including regional data, patient demographics, and diagnosis information, to show a narrowing of potential cohort with each filter applied.
  • Streamlines the process of requesting additional data, and
  • Allows users to organize, track, and reuse those request parameters over time.

Seeking additional treatment opportunities for your patients?

Clinical Trial Matcher:

  • Physicians who seek alternative treatment options for their patients have direct access to Clinical Trial Matcher. The tool leverages data from patient medical records to query inclusion and exclusion criteria of local and national clinical trials, including those sponsored by your organization.
  • Researchers can also use the tool to determine if the catchment population has enough potential to meet requirements for recruiting trials that are not currently in the area, thereby proactively identifying opportunities to pursue site trial participation.

Visualizations:

  • Geospatial – Designed to foster deeper investigation into the relationship between cancer and environmental exposures, our interactive geospatial platform enables clinicians, researchers, and administrators to visualize real-time data mapped by patient census block group and filtered by demographics and disease characteristics such as age, sex, race, cancer type, and diagnosis year. The tool allows users to layer this patient data with environmental datasets—including pesticide usage by ZIP code, toxic release inventory facilities, air monitor concentrations, and radon measurements—sourced from local, state and federal public health organizations.
  • Ontology – Interactive ontology models allow users to drill in and out of a set of concepts and categories in a specialty area to show properties and relations between them.  One common usage is envisioning the relationships between specific molecular mutations in tumors for patients undergoing cancer treatment.