Figure-1-Genomics-file-viewer-QuartzBio-eBDM_
Figure-1-Genomics-file-viewer-QuartzBio-eBDM_

The client: Biologics company developing cell therapies for blood cancers, generating large amounts of genomics data across four clinical programs and preclinical research teams

The client’s bioinformatics teams approached QuartzBio seeking a better workflow for sharing insights obtained from their genomics data.

They were using complex, manual workflows to ingest and process next-generation sequencing (NGS) data. These workflows comprised multiple steps, including alignment processing, variant processing, annotation, and clinical interpretation in the context of clinical data and publicly available data.

The challenge: Complex data management workflows hindered decision-making and created bottlenecks

The company had made a large financial investment in their data-rich therapeutic development programs – approximately $150M across the portfolio to date.

However, the complexity of their bioinformatics workflows made it difficult to share reports, analyses, and other visualizations with these stakeholders to get necessary signoffs and approvals.

Other specific concerns included

  • Data integrity
  • Data security and regulatory compliance
  • User access management – not possible with existing workflows

The solution: Centralized visibility across a wide user base with QuartzBio® enterprise Biomarker Data Management (SaaS) solution

The client’s bioinformatics and translational medicine teams worked with QuartzBio’s genomics experts and data engineers to deploy the enterprise Biomarker Data Management (eBDM) solution.

QuartzBio® eBDM, an enterprise SaaS solution, provided intuitive data query and topline reporting on data availability, enabling seamless data consumption across a wide user base. Bioinformatics teams were able to give stakeholders access to a centralized data vault where they could search, navigate, and explore all raw and processed data related to their genomics workflows (Figure 1).

Genomics file viewer QuartzBio eBDM solution
Figure 1. Genomics file preview capabilities within QuartzBio® enterprise Biomarker Data Management solution provided stakeholders with centralized visibility across all source files, harmonized datasets, and various configuration files associated with a bioinformatics project. Vaults were access-controlled, with permissions controllable by the client’s administrative users. Shown here is an example of the .bam file preview tool within the eBDM solution.

To address the client’s concerns around data integrity, the eBDM solution included automated checks for data integrity and conformity with data transfer agreements (DTAs), providing transparent quality control of incoming data. All data workflow processes were set up in the eBDM solution with secure, 21 CFR part 11-compliant audit trails.

The outcome: Streamlined stakeholder approvals + integration with internal workflows = faster decisions

Deploying the QuartzBio® eBDM solution automated processes for cleaning and harmonizing the client’s genomics data and centralized it within a single solution.

The solution was further integrated with internal client workflows via API capabilities and native R/Python support, shortening the time from data acquisition to insight generation.

Most importantly, the bioinformatics teams could streamline stakeholder approvals by using a solution with both data security and fine-grained user access management.

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QuartzBio eBDM solution deployed across five clinical studies
QuartzBio eBDM solution deployed across five clinical studies

The client: Clinical development and translational research teams executing phase I and II studies for precision oncology 

A clinical-stage biotechnology company developing precision oncology therapeutics recently worked with QuartzBio to tackle challenges facing execution of three phase I and two phase II biomarker-informed studies.

Challenges facing clinical development included:

  • Limited pool of potential patients to recruit for studies
  • Challenges facing patient screening and stratification – ideal biomarker profile not well-defined

Specific challenge: integrating siloed data

The clinical development team was challenged to solve the problems of patient qualification and stratification by integrating data from multiple streams, across multiple clinical programs:

  • Electronic medical records
  • Lab data
  • Biomarker profiling with indication data for patients
  • Immune profiling data
  • Publicly available data
  • Preclinical data: cell data and animal (cytokine and biomarker) data

The data sets being generated as a result of the clients’ clinical programs were scattered across multiple, disconnected cloud storage solutions. The team needed data to be integrated in a unified, query-friendly database that complied with regulatory requirements.

The solution: QuartzBio® enterprise Biomarker Data Management (eBDM) Software-as-a-Service (SaaS) Application

The client’s clinical development team worked with QuartzBio’s informatics subject matter experts and data engineers to deploy the eBDM platform within 6 weeks.

QuartzBio® eBDM, an enterprise SaaS solution, enabled scalable, user-driven data management of the client’s entire ecosystem of biological data (Figure 1).

QuartzBio eBDM solution deployed across five clinical studies
Figure 1. Overview of the QuartzBio® enterprise Biomarker Data Management solution as deployed across 5 clinical studies. Multiple data types were automatically loaded into the data platform. After indexing, quality control (QC), and mapping in the landing, ingestion, and configuration layers of the platform, client teams could interrogate the data ecosystem using both the web interface and API access.

Because the QuartzBio® data platform is data type-, data source-, and vendor-agnostic, every one of the clients’ data streams could be acquired, ingested, quality-controlled, and harmonized within the platform.

  • Data type-specific templates were used to automatically harmonize and annotate data from different vendors at the time of or after data import
  • QuartzBio’s library of configuration-ready workflows spanned all assay technologies used by the client: genomics, high-content imaging, flow cytometry, immunohistochemistry

The outcome: freedom to explore and transform data via web-based UI

Once data was set up within the platform, users had the freedom to explore and transform data via a web-based user interface (UI) with data access controls, version history and audit trails.

The enterprise Biomarker Data Management application enabled collaboration among a diverse user base across the client’s organization. Not only did the clinical development team uncover insights to inform trial execution, but the clients’ bioinformatics, translational biology, and biomarker operations teams also used QuartzBio’s visualization, data analysis, and top-line reporting capabilities as follows:

Functional TeamHow the team used enterprise Biomarker Data Management
Biomarker OperationsOn-study reporting of data quality, data conformity, data availability, vendor performance, and turnaround times.
Data Integration and Validation
Bioinformatics / Computational BiologyGenerated visualizations (e.g., line plots, clustering, dimensionality reduction) and were able to connect data to existing tools (e.g., SpotFire, Prism)
Connect to Raw Data and Download Data
Translational ResearchObtained early insights into the ideal genomic profile of patients that showed response to the therapeutic candidate.
High dimensional heat maps

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QuartzBio Helps Keep Oncology Trial on Track at a Clinical-Stage Biotech 

A clinical-stage biopharmaceutical company has been developing novel therapeutics that selectively modulate gene expression to address unmet medical needs in cancer patients.  

To keep their phase I study of an epigenetic modulator on track, the program’s translational research team needed to be able to monitor clinical outcomes with respect to patients and with respect to biomarker-defined subgroups. 

To achieve this goal, the team needed to manage multiple data streams: 

  • Central lab sample inventory 
  • EDC/Clinical data 
  • Assay results data from multiple specialty labs, including IHC, flow cytometry, PK, and gene expression 

Biomarker Data Management (BDM) & virtual Sample Inventory Management (vSIM) 

In weeks, QuartzBio deployed its vSIM and BDM solutions to the clinical trial in progress, enabling the translational research team to: 

  • Gain centralized visibility into status of samples as they move from sites to central and specialty labs 
  • Revealed insights on actual samples collected vs. expected samples collected 
  • Generate hypotheses based on biomarker assay results linked to patient clinical data and dosage information 
  • Eliminate time-consuming and manual data cleaning and cross-referencing processes
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Figure 1 gene expression v response status heatmap
Figure 1 gene expression v response status heatmap
Biomarker Data Management in phase 2-3
Biomarker Data Management in phase 2-3

QuartzBio’s approach to biomarker data management can be seen in the context of a phase 2/3 dose evaluation and expansion oncology study with 5 assays run at 4 different labs. Using QuartzBio’s technology-driven solution, the sponsor could:

  • Pull together and visualize PK, cytokine, and flow cytometry data to inform optimal dosing
  • Integrate mutation, IHC, and cytokine data to develop a multimarker signature to stratify patients

The cross-functional QuartzBio team—including data scientists, biomarker data management programmers, and data managers—delivered a centralized data hub for biomarker data transfer, integration, and collaboration, as well as interactive reports and support for ongoing trial activities.

The client found that our approach transformed their ability to reach key clinical trial objectives.

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