Generating Value from Public, Large Scale, Biomedical Datasets-video thumbnail

Generating Value from Public, Large Scale Biomedical Datasets — Video

February 1, 2021 — Translational and clinical researchers everywhere are harnessing public multiomics data sets to accelerate R&D. Renée Deehan, Ph.D., VP of Computational Biology at QuartzBio, described the enormous potential of public, real-world data at a panel discussion hosted by OBN.

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Derisking Drug Development with The Cancer Genome Atlas -- TCGA

Integrating Data and Knowledge from The Cancer Genome Atlas to Accelerate R&D

January 27, 2021 — Non-profit and governmental organizations have invested immense financial and labor resources, with generous contributions from participants, to create large-scale data sets. The Cancer Genome Atlas (TCGA) is one such publicly accessible resource, and represents a uniquely comprehensive collection of multiomic and clinical data, from which drug development researchers can derive knowledge about disease, treatment, and the biology of individual tumors.

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Centralizing PK, Clinical, and Exploratory Data to Streamline Biomarker-Centric Trial Operations

Centralizing PK, Clinical, and Exploratory Data to Streamline Biomarker-Centric Trial Operations

December 10, 2020 — Biomarker-guided trials frequently have an international footprint of sites to reach targeted patient populations and involve a complex network of specialty labs. Join us for our upcoming webinar, where QuartzBio's Tobi Guennel will discuss how his team is breaking down data siloes to create actionable insights into availability and quality of samples and data. These insights allow clinical and translational teams to streamline trial operations and enable early course correction.

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Enabling Translational Intelligence to Rapidly Surface On-study Operational and Scientific Insights

Enabling Translational Intelligence to Rapidly Surface On-study Operational and Scientific Insights

November 12, 2020 — In this article, QuartzBio Managing Director Scott Marshall discusses critical steps to integrating clinical, PK, and exploratory data on-study to advance operational and translational insights (without all the manual effort that has become all too common). With our experience working across dozens of clients and hundreds of studies, we’ve identified four key components necessary to efficiently centralize. Read More →