US Hupo 2022

The US HUPO Annual Conference has established itself as a highly valued contribution to the interdisciplinary scientific field of proteomics, with a particular focus on current technologies in the field and their application to solving biological and clinical questions relevant to human health. The topics covered at the annual conference reflect the multiple disciplines, strategies, and technologies encompassing the proteomics field, and their use to address complex biomedical problems and enable new discoveries aimed at advancing diagnosis, prognosis and treatment of human disease.

Olink is happy to be sponsoring this year’s US Hupo as a premier sponsor.

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andres-hurtado-lorenzo

Olink Speaker: Andres Hurtado-Lorenzo

Vice President, Translational Research at Crohn’s & Colitis Foundation

Advancing Precision Medicine: Prognostic Biomarkers for Pediatric Crohn’s Disease

18:00 GMT / 19:00 CET / 13:00 EST

Prognostic biomarkers are measurable indicators that provide information about how a disease will progress over time. At present, due to a relative lack of available prognostic biomarkers, it is difficult to predict long-term outcomes in patients with pediatric Crohn’s disease. A test that would provide information regarding the probability that a given patient would later experience major debilitating intestinal complications of pediatric Crohn’s disease, like fibrostenosis and fistulas, could be an important tool to optimize care, particularly for vulnerable pediatric patients.

Multiple technologies have been explored for this purpose, however, there is still a need to identify and validate improved prognostic biomarkers to advance precision medicine for inflammatory bowel diseases like Crohn’s disease. One approach that has generated significant enthusiasm is the use of analytically validated high-throughput proteomics platforms developed by Olink Proteomics. The Olink Proximity Extension Assay (PEA) platform is analytically validated for high-throughput and provides highly sensitive quantitation of over 1,000 protein markers; the platform is relatively cost-effective; and development of custom assays is available, including regulatory-grade validation.

This session will discuss findings related to the identification, using machine learning, of prognostic mRNA-based and protein-based biomarkers able to identify pediatric patients at high risk of developing complications with a high degree of accuracy at diagnosis.

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Protein data points generated

997

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