NEW YORK – Dec 4, 2018 – The Castleman Disease Collaborative Network (CDCN) discovered new patient subgroups, based on previously unknown proteomic signatures, withMedidata’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:
â Six new patient subsets reflecting either distinct subtypes or proteomic disease states
â Evidence of proteomic predictors of anti-interleukin-6 treatment response
â Etiological insights into the poorly understood rare disease and toward new potential drug targets
“Medidata's analytics empowers 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
About Medidata
Medidata is leading the digital transformation of life sciences, with the world's most used platform for clinical development, commercial, and real-world data. Powered by artificial intelligence and delivered by the #1 ranked industry experts, the Intelligent Platform for Life Sciences helps pharmaceutical, biotech, medical device companies, and academic researchers accelerate value, minimize risk and optimize outcomes. Medidata serves more than 1,000 customers and partners worldwide and empowers more than 100,000 certified users every day to create hope for millions of patients. Discover the future of life sciences: www.mdsol.com
About Castleman Disease Collaborative Network (CDCN)
CDCN is a global initiative dedicated to accelerating research and treatment for Castlemandisease (CD) to improve survival for all patients with CD. The CDCN’s innovative approach firstinvolved 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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