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Common digital clinical measures to de-risk CRS

Our community of experts has identified a set of common digital clinical measures that are essential for developing Cytokine Release Syndrome (CRS) de-risking products.

We’ve also developed an ontology to help you standardize data collection for assessing CRS onset and severity, whether you’re collecting data manually or digitally, in inpatient or outpatient settings.

These resources are designed to help you streamline data collection efforts, supporting the development of more efficient CRS de-risking products and risk prediction models.

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Ontology of early warning signs of CRS

Discover how others are using these resources

Leveraging DATAcc by DiMe’s ontology for data transfer specifications development for early detection of CRS in CAR-T and BiTE therapy patients

Melinda Chen & Erik Koenig | Takeda

Milos Todorovic | Director of Biomedical and Clinical Engineering Analog Devices, Inc.

Optimizing sepsis and CRS detection: A data-driven approach to improve patient outcomes

Lavi Kwiatkowsky | Founder & CEO, Canopy

Premal Kamdar | Director, Digital Health Product Management, Bristol Myers Squibb

Michael Pettinati | Senior Data Scientist, ActiGraph

    Additional resources to support your success

    Innovation roadmap

    By using this roadmap, you’ll explore important milestones that inform the development of your CRS de-risking product—thereby enhancing patient outcomes, optimizing care, and accelerating drug development.

    Practical guide

    Bring your CRS de-risking product to market with expert strategies for development, safety, streamlined workflows, and adoption—all in this guide.