Immunotherapy Response signature genomics hot cold tumors QuartzBio

Translational Intelligence: Exploring Immunotherapy Response Signatures with Clinical Trial Genomics Data

May 5, 2021 — As the data generated during a modern clinical trial has dramatically expanded, sponsors must continuously evaluate novel approaches to help bridge the gap between millions of data points and breakthrough scientific insights (a goal we describe as delivering Translational Intelligence). One such example is assessing signatures of “hot” and “cold” tumors.

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May 12 webinar Exploring IO Signatures QuartzBio

Webinar On Demand: Exploring IO Signatures in Clinical Trial Genomic Data

Watch the webinar on demand:

Title: Translational Intelligence: Exploring IO Signatures in Clinical Trial Genomic Data

Duration: 30 minutes

You will learn how to:

  • Visualize gene alterations and tumor mutational burden (TMB) using heatmaps and tables, with subject and time point granularity. ​
  • Identify genes of interest and candidate signatures using visualization and statistical methods to relate clinical response data and gene expression data to regions of genomic alteration.​
  • Correlate genomic data with known signatures of immuno-oncology (IO) response through integrations with public data, knowledgebases and sponsor data.​
  • Define patient subgroups to generate deeper Read More →
genomics data in clinical trials quartzbio image

Translational Intelligence: Synthesis and Integration of Genomics Data in Clinical Trials

April 21, 2021 — A modern clinical trial, with well-characterized subjects studied over periods of time, presents unmissable opportunities for sponsors to characterize mechanism of action, prioritize target pathways for their pipelines, and generate as much data as possible to support regulatory filings.

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CDISC compliant submission article 1 image 202104

Delivering CDISC-Compliant Submissions of Biomarker and Specialty Lab Data

April 9, 2021 — With the rise of biomarkers used in clinical trials (e.g., prognostic, predictive, pharmacodynamic) and biomarker assay modalities (e.g. flow cytometry, multiplex protein detection, gene expression profiling), biomarker and specialty lab data are increasingly incorporated into FDA submissions. This data provides insights into key clinical objectives, including pharmacological effects, and drug safety and effectiveness.

Drug developers face operational challenges, however, in preparing complex, often unstructured, biomarker and specialty lab data in compliance with regulatory requirements.

Any study that began as of December 17, 2016 must use Clinical Data Interchange Standards Consortium Read More →