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Research-Ready Infrastructure for Real World Data Capture

Litmus helps researchers better understand patients’ behavior and environment.

We use wearables data collected at the point of experience to guide management and to inform clinical trial endpoints.


Digital endpoints. Multiple dimensions. Leverage remote patient data the right way.

  • Litmus collects data directly from hundreds of data sources, positioning it for later analytics work with zero wrangling. Integrate multiple sets and streams with ease.
  • Our iOS and Android patient apps gather even more data and trigger validated survey questions based on your protocol design. There’s no need for custom app development.
  • Study Hub monitors progress, alerts PIs, and visualizes population trends at-a-glance, with individual drill-down views for every patient, and faceted search throughout.
  • Litmus ML makes modeling a cinch. We also interoperate with your favorite data science tools. Align time series, interpolate, and look for correlations.

Deploy the Litmus health solution in as little as four weeks.

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Takeda + UChicago

Takeda Pharmaceuticals, along with Dr. David Rubin and his colleagues at the University of Chicago, are leveraging Litmus Health in a 500 patient study conducted over three years that is already producing exciting, publishable results.

We’re gathering data from smartphones, ePRO, and wearables to better understand the relationship between sleep, activity, and flares in Crohn’s and Colitis patients. Our ultimate goal is to use the models to accurately predict health outcomes.

Initial results have shown the potential to inform patient disease monitoring and management strategies. Dr. Rubin’s team and Litmus are now developing models capable of predicting IBD flares based on heart rate, sleep, and physical activity.

David T. Rubin, MD in his lab at UChicago
David T. Rubin, MD in his lab at UChicago
“We all want to collect higher quality and more accurate data from patients in our clinical trials. Litmus is the first platform I’ve seen that actually delivers.”
David T. Rubin, MD
Professor of Medicine, Co-Director, Digestive Diseases Center, University of Chicago

Read our latest Device Census Report — developed specifically to guide pharma looking to incorporate real world data from wearables.

Blue cover of device census report Vol.2: Extraclinical Wearables
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Wearable Devices Can Predict Disease Activity in Inflammatory Bowel Disease Patients

Inflammatory Bowel Disease Center, University of Chicago Medicine, Chicago, USA, Litmus Health, Inc., Austin, TX, USA
P. H. Sossenheimer, O. V. Yvellez, M. Andersen, T. Pearl, K. El Jurdi, D. B. Rubin, A. Mayampurath, D. T. Rubin
Black and white photo of cells under a microscope
Background Certain biomarkers, including C-reactive protein (CRP) and faecal calprotectin (FC), are sensitive biomarkers for active inflammation in IBD. As part of an ongoing prospective study on the use of biosensors in IBD, we aimed to determine the feasibility of predicting a patient’s disease activity based on data collected by wearable devices. Conclusion We demonstrate for the first time the use of passive biosensor data to predict elevated biomarkers of inflammation in IBD. These results inform our ongoing prospective work to develop disease monitoring and management strategies.
Read More
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Use of Wearable, Mobile, and Sensor Technology in Cancer Clinical Trials

Suzanne M. Cox, Ashley Lane, and Samuel L. Volchenboum
Grey-scale photo of an apple watch on a man’s wrist
As the availability and sophistication of mobile health (mHealth) technology (wearables, mobile technology, and sensors) continues to increase, there is great promise that these tools will be transformative for clinical trials and drug development. This review provides an overview of the current landscape of potential measurement options, including the various types of data collected, methods/tools for collecting them, and a crosswalk of available options. The opportunities and potential drawbacks of mHealth in cancer clinical trials are discussed. Specific concerns related to data accuracy, provenance, and regulatory issues are highlighted, with suggestions for how to address these in future research. Next steps for establishing mHealth methods and tools as legitimate and accepted measures in oncology clinical trials include continuation of regulatory definition by the FDA; establishment of security standards and protocols; refinement and implementation of methods to establish and document data accuracy; and finally, creation of feedback loops wherein regulators receive updates from researchers with better and more timely data, which should decrease trial times and lessen drug development costs. Implementing mHealth technologies into cancer clinical trials has the potential to transform and propel oncology drug development and precision medicine to keep pace with the rapidly increasing developments in genomics and immunology.
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About Litmus

Made up of clinical trial and bioinformatics experts, Litmus is ready to work shoulder-to-shoulder with your researchers and project leads.

We believe quality of life is the ultimate endpoint, and we’re focused on helping investigators and their sponsors bring better drugs and therapeutics to market, faster.

Get In Touch

Are you ready to incorporate real-life data into your observational study, therapeutic trial, or post-market research? We can help you get it right the first time.

The University of Chicago
National Cancer Institute
National Institutes of Health
Bristol Myers Squibb

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