Medidata Rave Omics Collaboration Uncovers Novel Insights for Rare Disease Research
Discovery of biomarker evidence in Castleman Disease exemplifies the value of personalized medicine in rare diseases
The Castleman Disease Collaborative Network presented new research supported by Medidata at 60th Annual Meeting of the American Society of Hematology
Application of Medidata Rave Omics reveals new patient subgroups that can accelerate diagnosis and treatment
Medidata data analysis in collaboration with the Castleman Disease Collaborative Network advances personalized medicine for life-threatening disorder
NEW YORK – Dec 4, 2018 – The Castleman Disease Collaborative Network (CDCN) discovered new patient subgroups, based on previously unknown proteomic signatures, with Medidata’s Rave Omics, a machine learning-based solution. These discoveries provide novel insights into treatment response and potential new drug targets, highlighting the value of precision medicine.
Medidata (NASDAQ: MDSO) and the CDCN presented these insights at the 60th Annual Meeting of the American Society of Hematology (ASH).
Idiopathic Multicentric Castleman Disease (iMCD) is a rare, difficult to diagnose, life-threatening disorder.1 The CDCN advances research programs to develop better diagnostic methods, identify patients that will respond to approved therapy and find new drug targets to develop new therapies.
“iMCD stumped my doctors, and they didn’t think I would survive. My mission today is to bring new treatment options and hope to Castleman Disease patients and other poorly understood rare diseases,” said Dr. David Fajgenbaum, co-founder and executive director of the Castleman Disease Collaborative Network. “Rare diseases often lack sufficient sample sizes and necessary resources to make critical discoveries, which has limited the development of new treatment options for patients. This collaborative study combined patient samples from around the world and the Rave Omics tool to overcome these challenges and help to better understand this disease. We are now working together to use this data to personalize treatment for Castleman disease.”
Medidata Rave Omics enabled the discovery of novel biomarkers for Castleman disease. With unparalleled industry expertise, Medidata data scientists collaborated with the Castleman Disease Collaborative Network to make the following insights:
Six new patient subsets reflecting either distinct subtypes or proteomic disease states
Evidence of proteomic predictors of anti-interleukin-6 treatment response
Etiological insights into the poorly understood rare disease and toward new potential drug targets
“Medidata's analytics empower researchers to make new discoveries for all patients, including those with rare diseases,” said Glen de Vries, co-founder and president, Medidata. “We’re proud to help make personalized medicine and the development of targeted treatments possible with Rave Omics.”
Medidata Rave Omics streamlines omic data capture, linking and analysis inside the clinical study process. To learn more about how Medidata is accelerating personalized medicine research, visit mdsol.com.
1Fajgenbaum D, Ruth J, Kelleher D, Rubenstein A. Lancet Haematology. 2016;3:150-152
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About Castleman Disease Collaborative Network (CDCN)
CDCN is a global initiative dedicated to accelerating research and treatment for Castleman disease (CD) to improve survival for all patients with CD. The CDCN’s innovative approach first involved building a global community of over 400 physicians and researchers, assembling a scientific advisory board of 28 experts from eight countries, and supporting and engaging patients in research prioritization. Then, the CDCN crowdsourced among the global community to identify gaps in medical knowledge and determine high priority research projects. In parallel, the CDCN connects and supports thousands of CD patients around the world. Now, the CDCN recruits top researchers to conduct studies, and works with patients, loved ones, and the public to raise funding to enable these studies. More information is available at: www.CDCN.org
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