Managing Complex Biomarker Data Archives - Page 2 of 5

QuartzBio Connecting Raw Processed and Ancillary Data

Translational and clinical teams spend more than 70% of their time managing, cleaning, and harmonizing data generated in biomarker-rich clinical programs.

In a webinar now available on demand, we demonstrated how the QuartzBio® enterprise Biomarker Data Management (eBDM) solution addresses one set of frequently intractable challenges: connecting raw, processed, and ancillary data across multiple clinical studies.

We invite you to sign up for on-demand access to the recorded webinar.

Multiple Assay Modalities, File Types, Data Storage Locations

As we have previously described, research teams are generating biomarker data from a wide variety of assay modalities, and this data can be housed in multiple, disconnected storage locations. In the example use case described in the webinar, data was being generated from targeted assays like flow cytometry and immunohistochemistry to high-throughput omics assays.

The QuartzBio eBDM solution is specifically engineered to ingest, standardize, visualize, and analyze this data. The unified data platform connects raw and processed data to ancillary files, such as the images used for immunohistochemistry quantification or PDF omics reports. All of the raw files are available for download individually or in bulk. They can also be previewed directly within the user interface.

As shown in Video 1, the QuartzBio enterprise data platform can centralize and harmonize data from multiple file types across clinical programs, including:

Image files
Tabular files
Omics files, e.g., BAM or VCF files
Sequencing reports for particular mutations or genomic regions of interest

**Video 1** (Click image to view video): The QuartzBio enterprise data platform can centralize and harmonize data from multiple file types across clinical programs. Video demonstrates access to images, PDF files, and genomics data.

As shown in Video 2, the QuartzBio eBDM solution can combine processed files with harmonized clinical annotations, with both subject and sample level data, as well as the relevant quantified reportables for a specific assay modality. These reportables are very configurable and can be changed according to the needs of a sponsor, a program, or even a specific study.

**Video 2** (Click image to view video): Processed files combine harmonized clinical annotations with both subject- and sample-level data.

The QuartzBio team can also further preprocess raw assay data directly and apply quality control metrics as well as normalization techniques. We can also extract relevant data and metadata from PDFs, such as omics reports and informed consent forms.

In summary, the webinar demonstrated how the biomarker data modules of the QuartzBio platform can enable easy access to both key raw and processed data assets through the user interface, in addition to robust visualization and data exploration capabilities.

Flexible Biomarker Data Management Means Faster Deployment

QuartzBio’s enterprise-grade Biomarker Data Management application provides a flexible, scalable solution for transforming biomarker data into consumable information across a sponsor’s entire study portfolio.

This resilient approach is enabled by a robust enterprise data platform with a library of pre-built, configuration-ready pipelines for data ingestion.

Contact us to learn more about data management SaaS solutions and let us know which additional features and capabilities you’d like featured in our next webinar.

Contact Us to Continue the Conversation

Duration: 30 minutes

Register for the Webinar:

Translational and clinical research teams spend more than 70% of their time wrangling information from disconnected clinical trial data sets.

Data ends up in silos, making it hard to compile information and surface insights.

Watch this short webinar, where Adam Brown and Mike Waters will demonstrate how integrating exploratory biomarker, PK, and clinical data in a unified data platform enables teams to interrogate trends and identify insights as data is generated on-study.

Register for the Webinar:

Translational and clinical research teams spend more than 70% of their time wrangling information from disconnected clinical trial data sets.

Data ends up in silos, making it hard to compile information and surface insights.

Watch this short webinar, where Adam Brown and Mike Waters will demonstrate how integrating exploratory biomarker, PK, and clinical data in a unified data platform enables teams to interrogate trends and identify insights as data is generated on-study.

Join QuartzBio at the 8th Annual Bioinformatics Strategy Meeting East Coast USA for the “Omics-Driven Approaches” track on 23 May 2022.

ROUNDTABLE DISCUSSION: “Turning Multi-omic Data Chaos into Translational Insights”

Mike Waters of QuartzBio will facilitate a discussion among 10-15 industry leaders around critical topics relevant to biomarker-rich clinical trials:

January 10, 2022 — With immuno-oncology assets progressing in the clinic, a growing biotechnology company we work with faces an increasingly common challenge:

Their trials are generating large datasets across a wide range of assay modalities (Figure 1), but the data remains siloed.

In addition to clinical data coming from the clinical research organization (CRO), the velocity of data coming from an assay services laboratory continuously delivering biomarker data from flow cytometry, immunohistochemistry, and genomics platforms quickly becomes overwhelming. Still another, separate data stream comes from a specialty laboratory delivering T-cell receptor (TCR) profiling data.

August 31, 2021 — Clinical samples are moving across an increasing number of physical/virtual locations and data is delivered in an expanding array of file formats as clinical trials become increasingly more complex and data rich (report).

Biospecimens are analyzed using a variety of assay technologies, each generating its own set of reportables, quality control metrics and data/file formats. Data is delivered through multiple, disconnected pipelines (Figure 1).

This complexity creates obstacles for many functional groups within sponsor organizations:

Register for the webinar here

Title: Transcending Biomarker Data Chaos: How Integrating Disparate PK, Clinical & Exploratory Data Enables Deep Translational Insights

Duration: 30 minutes

You will see how teams unlock translational intelligence:

Navigate vast exploratory data – identify trends and data points of interest
Surface insights – analyze biomarker trends in collaborative dashboards across subject IDs, time points, response status, and treatment groups
Access data rapidly – point and click navigation to underlying data files to interrogate the raw data behind the summary values
Interrogate cross assay – map to a common data dictionary to enable rapid interrogation of trends across assay modalities: within and across studies

July 29, 2021 — Translational research teams producing large datasets from biomarker-rich trials quickly face the next challenge: generating actionable insights from their data.

As we described in a previous case study, we have been working with many teams to enable deep mechanistic insight generation from their biomarker data to aid in signature development for selecting patients, predicting therapeutic response, and informing key development decisions.

May 19, 2021 — Biomarker data generated to support clinical development has multiple roles:

Inclusion in end-of-study regulatory submissions. As such, data must conform to FDA data exchange standards and need SDTM programming for analysis and submission.
Supporting on-study decisions. Data must be stored in an accessible, flexibly structured format to adapt to on-study needs. These diverse needs include data visualization, mock TLFs, materials for investor meetings, posters, and reporting for safety review, data monitoring, and dosing decisions.
Enable deep exploration to generate translational insights. Biomarker data generated during clinical trials presents opportunities for sponsors to further characterize mechanism of action and prioritize additional target pathways for their pipelines.

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.

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 biological/ mechanistic insights.