Novel markers to predict virological and clinical relapse onset following antiviral treatment discontinuation in chronic hepatitis B patients
In a collaboration with investigators at Janssen, the QuartzBio team sought to identify genetic markers correlated with protection against chronic hepatitis B early relapse in patients after withdrawal from treatment. The team identified several genes that were, for the first time, associated with protection against early onset of relapse.
Processing Public Data: Clinical Annotations, TME Insights & More
February 26, 2021 — Public data assets, such as TCGA, are rich resources for enabling pre-clinical discovery, translational, and clinical biomarker teams to make faster drug development decisions that are informed by human disease data.
Historically, this real-world, human disease data has not had much of a place at these points in the drug life cycle, simply because it didn’t exist. Now that it does, it is imperative that we as researchers figure out the optimal way by which we can integrate findings from public data.
In our last article on derisking drug development using TCGA, we discussed specific applications as well as some of the inherent challenges facing researchers who seek to use TCGA. In particular, significant data QC, processing, and normalizing steps are required to align and format the data as “analysis-ready” before translational researchers can begin interrogating TCGA. These procedures need to be robust in order to guarantee reproducibility, but flexible in order to integrate potential changes in TCGA annotations.
Given the challenges of using TCGA (including as additional data are added), translational researchers increasingly find that pre-aligned and pre-processed TCGA data accelerates their ability to generate reliable insights to inform critical drug development decisions.
Join QuartzBio at the SCOPE 2021 Virtual Conference for Clinical Operations Executives
Join QuartzBio at the SCOPE 2021 virtual conference for the “Clinical Biomarkers Operations and Innovation” track on March 2.
PRESENTATION: “Centralizing PK, Clinical, and Exploratory Biospecimen Data to Streamline Trial Operations & Intelligence”
Clinical samples are frequently a logistical headache – managed too often in Excel files that are time-consuming to update, and quickly fall out of date. Modern biomarker-centric programs demand a focused strategy to provide timely visibility into sample collection, processing, and storage status.
Dr. Tobi Guennel will share how clinical teams are leveraging technology to quickly and efficiently gain visibility into their clinical samples across sites, labs, and storage facilities. (more…)
Translational Intelligence: On-Study Applications of Machine Learning to Integrated Biomarker and Clinical Data
February 12, 2021 — Integrating clinical and biomarker data enables both operational insights as well as scientific insights that can help teams make clinical trial decisions on-study.
Our last article defined the synthesis of these insights as translational intelligence, with the potential to illuminate key insights in drug development just as business intelligence is used to optimize business performance. We showed that, for example, having all the biomarker and clinical data linked together enables sponsors to quickly explore the relationship between drug response status and specific biomarkers of interest.
In this post, we further illustrate how translational intelligence works in practice with example applications. Translational intelligence not only illuminates key trends that may be missed through manual data review, but it also facilitates the seamless exploration of interlinked clinical, PK, and exploratory biomarker data assets. (more…)
Webinar On Demand: Critical On-Study Biomarker KPIs for Modern Trials – Part 2
Register now to watch the webinar on demand:
Title: Critical On-Study Biomarker KPIs for Modern Trials – Part 2: Integrating Data Silos to Unlock Scientific Insights and Empower Translational Teams
Duration: 45 minutes
You will learn how to:
- Expand your use of exploratory biomarker data in combination with clinical metadata for on-study analytics
- Centralize integrated biomarker and clinical data as a single source of truth to expedite drug development decisions and enable translational exploration
- Leverage dashboards to support collaboration and quickly surface actionable insights