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Leveraging digital innovations to support the development of a risk prediction tool for Cytokine Release Syndrome (CRS)

DATAcc’s new project, Advancing Digital Capabilities to Enable Digital Risk Prediction for CRS, leverages new digital innovations to support industry leaders in developing a risk prediction tool for CRS. Digital technologies have matured to a point where we can – and should – rely on them to predict the onset of CRS outside of the clinic, improving access and equity while reducing the costs of developing and administering immunotherapies.

What is CRS?

Immunotherapies have emerged as promising treatments for devastating hematological cancers like leukemias, lymphomas, and multiple myeloma. They offer targeted, better-tolerated options with promising results, such as improved survival rates, enhanced quality of life, and ongoing advancements.

CRS can be a side effect of these immunotherapies and has become a significant risk for medicinal product developers, hospital systems, payers, regulators, and, most importantly, patients. It can threaten patients’ lives if the onset is not closely monitored and managed.

This project will:

  • Define technical definitions and ontologies for predictive measures of CRS;
  • Explore regulatory considerations and evidentiary requirements;
  • Establish what good technical performance looks like; and

  • Define operational best practices to support the development and implementation of digital capabilities.
Through this work, we aim to provide oncology specialists and researchers with a reliable way to detect and treat CRS in cancer patients using digital tools, allowing patients to spend less time in in-patient clinics and removing the added risk and stress to already burdensome cancer journeys.

Our Partners

Partners also include the National Cancer Institute

Get involved

Join our next project to develop a value framework, industry benchmarking tools, forecasting models, and a modular template business case framework to help innovators invest in digital endpoints and advance their broad adoption and scale in clinical research.