Wisconsin Alumni Research Foundation

WARF Accelerator Oncology Diagnostics Grant

Understanding the biology behind the development and progression of cancer is crucial to evaluating strategies for prevention and treatment. Researchers across campus are identifying diagnostic tools – from biomarkers to machine learning algorithms, early detection tests and more – that can help guide decisions for clinicians and patients and improve outcomes.

WARF is launching a WARF Accelerator Challenge to identify and support technologies on campus that impact this important area of research.

Applications were due October 30.

Grant Details

  • WARF Accelerator will award 2-5 grants from a pool of approximately $100,000.
  • Individuals and teams should complete these questions and submit them as an attachment to your innovation disclosure. Please include “Oncology Diagnostics Challenge” in the description of your innovation.
  • WARF staff will evaluate proposals.
  • Proposed research to be completed within a year.
  • Project team must include a Principal Investigator (PI) at UW-Madison or the Morgridge Institute for Research.

Assessment Criteria

  • Projects do not need to be patentable
  • Concepts must be new (not something previously disclosed to WARF)
  • Technical readiness
  • Commercial potential

Oncology Diagnostics Projects

We’re looking for projects that focus on new ways of diagnosing cancer and improving patient outcomes, including: novel and creative proof-of-concept work in identifying/validating novel biomarkers (proteins, nucleic acids, metabolites, pathogenic mutations, epigenetic changes or tissue morphological changes) associated with cancer and/or platforms for diagnosing the presence of the disease, characterizing the stage of disease, optimizing treatment or tracking how the disease responds to treatment.

Projects may include:

  • Novel medical imaging technologies
  • Machine learning and AI tools for diagnosing disease
  • Biomarkers that are blood-based or in tissues
  • Label-free biomarker detection methods

Even if your idea doesn’t relate to the above examples or is early stage, please consider submitting an application. We’re interested in hearing your idea.

Any Questions?

Contact Beth Fischer