October 31, 2022 – Translational and clinical teams spend more than 70% of their time managing, cleaning, and harmonizing data generated in biomarker-rich clinical programs.

In a recent webinar, Adam Brown 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.

ICF Codification QuartzBio
ICF Codification QuartzBio

September 21, 2022 — Biospecimens collected as part of biomarker-informed clinical programs are precious resources for precision medicine research and development (R&D). However, the complexity of tracking and linking informed consent data at the sample and derivative levels limits the use of these biospecimens.

Most informed consent data exists in uncodified informed consent forms (ICFs) and ends up in silos spread across multiple databases. It can be manual and time-consuming to compile information and surface insights.

In this post, we’ll explore how clinical teams can benefit from QuartzBio’s flexible approach to ICF codification to reduce complexity, gain more value from their stored samples, and help turn their biorepositories into drug development engines.

The Challenge: Siloed, Uncodified ICF Data

The challenge many sponsors face is not one of quantity. Instead, it is one of complexity. Sponsors may have many thousands of biospecimens from many different clinical trials sitting in multiple long-term storage locations, each having varying ICFs and sample destruction dates. This makes it difficult for clinical teams to address questions such as

  • “Which FFPE samples in Biorepositories A, B, and C are consented for genomic analysis?”
  • “Which samples will be destroyed within the next 6 months per sample destruction date listed on the ICF?”
  • “Which samples need to be destroyed because the subject has withdrawn consent?”

The Approach: Tailored, Sponsor-Centric ICF Codification

The ideal virtual biorepository is a searchable master inventory of the vast array of samples from both open and closed clinical trials. With this much data on hand, R&D teams must be able to search and filter that inventory based on consent data fields such as:

  • Consent status – including withdrawal of consent
  • Consent restrictions and approved uses
  • Sample destruction date based on ICF linked to sample type
  • Links between multiple different ICFs (for example, a master ICF, future-use ICF, and a genomics ICF for subset of samples) at patient, site and country levels

In addition to these critical types of consent data, QuartzBio clients often seek to interrogate and visualize ICF data to suit specific applications. For example, a client may wish to explore codified ICF data linked to appropriate sample type, with parent/child linkages, filterable to find samples of interest, annotated with approved and restricted use cases.

By linking biospecimen metadata, informed consent, and biomarker data across multiple laboratory LIMS and inventories, clients can create a flexible virtual biorepository that is ready to use for a wide range of R&D needs.

The Results: More Codified Consent Data, More Power

Armed with a master inventory annotated with codified informed consent data, clinical and translational teams are empowered to

  • Save resources and time, using stored samples to advance research beyond this current study
  • Rapidly respond to requests for additional testing
  • Ensure regulatory compliance with retention, use, and destruction requirements based on informed consent
  • Facilitate efficient discontinuation or transfer of studies/programs
  • Perform risk-based monitoring to determine, at a distance, whether every sample has an appropriate consent status

At QuartzBio, we deliver solutions that advance our clients’ pipelines today while remaining future-proof for tomorrow. This resilient approach is critical, especially in the face of evolving scales, regulatory requirements, and complexity of clinical programs.

QuartzBio is rigorous with regards to regulatory compliance, yet flexible to sponsors requirements, both in terms of which information to extract as well as how to visualize, filter, and search it.

Some sample inventory management systems are limited as to which data structures can be imported, or even place data structure requirements on vendors. QuartzBio technology maps data as-is, from any source, into the QuartzBio® Data Platform using the format provided by the lab, vendor, or other source system with no changes required. The result: increased flexibility and faster deployment.

Further, while some ICF codification solutions limit users to filter using 7-9 rigid terms, QuartzBio’s virtual Biorepository solution enables clients to configure the platform to enable filtering, searching, and visualizations using sponsor-defined parameters.

How is your team thinking about making the most of your biospecimens? Connect with the QuartzBio team to discuss the structure your consent data and get a closer look at the QuartzBio data platform.

4 Strategic Imperatives Biomarker Operations image_2
4 Strategic Imperatives Biomarker Operations image_2

Keeping track of clinical trial samples across multiple sites and vendors can be manual and tedious (recent post) — we have demonstrated how virtual Sample Inventory Management can streamline the day-to-day reporting of sample collections, shipments, and discrepancies (webinar series).

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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.

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