December 10, 2020 — Biomarker-guided trials frequently have an international footprint of sites to reach targeted patient populations and involve a complex network of specialty labs. Join us for our upcoming webinar, where QuartzBio’s Tobi Guennel will discuss how his team is breaking down data siloes to create actionable insights into availability and quality of samples and data. These insights allow clinical and translational teams to streamline trial operations and enable early course correction.
Today’s clinical trials have global footprints to reach targeted patient populations and rely on specialty labs running complex assays to assess safety, characterize patient response, and provide insight into efficacy. These biomarker-centric programs demand a focused strategy to provide timely visibility into sample availability and quality, data availability and quality, and critical on-study measurements.
Much of the information necessary to deliver translational intelligence exists today – though it is dispersed across workstreams (e.g. sample, assay, clinical, consent) and stakeholders (e.g. CROs, sites, labs, sponsors) and systems (e.g. EDC, CTMS, LIMS). Just as EDC adoption accelerated the centralization of clinical data, our team will highlight the opportunity to integrate and centralize biomarker data, the unique challenges that have historically faced the industry, and how overcoming these challenges can unlock transformative insights.
Join us for a two-part webinar series in which we discuss critical on-study biomarker KPIs and unlocking translational insights.
In Part 1: Centralizing PK, Clinical, and Exploratory Data to Streamline Biomarker-Centric Trial Operations, we will cover logistical challenges (many exacerbated by the pandemic) that have sharpened our industry’s focus on data centralization to ensure today’s investments in biomarker-guided clinical trials yield the volume, quality, and depth of data needed to advance translational research. Topics to be discussed include:
- Elevating site-level sample QC metrics and sample availability as critical KPIs for trial operations, enabling course corrections before it’s too late
- Monitoring results data availability across assay modalities at study, cohort, patient, and sample levels
- Evaluating assay- and batch-specific data quality on-study to ensure critical thresholds are met, and to accelerate insight
- Establishing a framework to centralize PK, exploratory, and relevant clinical data in accordance with data managemet best practices (FAIR, GCP, etc)
Throughout the discussions, our team will highlight how smart technology, consisting of sophisticated connectors and scalable data workflows, enables the rapid assimilation and synthesis of historically disparate data. This use of technology enables insights today – rather than as the product of years long enterprise investments – and reduces the burden, frustrations, and delays associated with manual data reconciliation and a patchwork of homegrown solutions.
In Part 2: Integrating Data Silos to Unlock Scientific Insights and Empower Translational Teams, we will discuss the opportunity to expand the use of exploratory data for on-study insights.
Join us for part 2 by registering here!