From Silos to Sync: Practical collaboration in clinical data delivery

  • Why traditional role boundaries slow down data quality and delivery
  • Shared ownership across the data pipeline leads to faster, cleaner outcomes
  • Leveraging standards to reduce rework and clarify expectations
  • Using shared metrics and dashboards to stay aligned throughout the process

CLOSING PANEL DISCUSSION: Overcoming disjointed CRO relationships and identifying successful vendor oversight strategies

  • Do service providers really understand what data needs to be collected? Assessing their familiarity and expertise of trials’ specific data needs
  • Better informed CRO oversight strategies to avoid noncompliance issues, protocol deviations, and misinterpretation of the study data
  • A look at why the industry is skeptical to lower-cost data service providers, when agency scrutiny and data safety can be faced by all companies
  • Basing the level of CRO oversight on the risk assessments carried out by different stakeholders involved in the study

A conceptual cross functional collaborative digital platform for data review

  • Integrating Data Management and SDTM business functions in a single platform for collaborative data review
  • Enabling Clinical Coding, Safety Coding and Medical Reviewers leverage a centralized Dictionary Coding platform
  • Leveraging Centralized Dictionary Coding platform to keep EDC and Safety databases in sync

TECHNOLOGY SPOTLIGHT: Reduce cycle time with elluminate  

  • Discover how the elluminate Clinical Data Cloud provides a flexible foundation for increased data democratization and accessibility in a regulated environment
  • Uncover the technology blueprint that enhances data value and enables the future state with efficiency through automation and AI
  • See the value of an interoperable ecosystem with an end-to-end solution for clinical data review and analytics needs – from ingestion through submission

Practical applications of Quality by Design in day-to-day data management

  • Unpacking the latest terms – RBQM, QBD, “informed data management” whatever is next..
  • Understanding why there is a shift in traditional data management
  • Requirements and potential barriers to entry
  • What is everyone else doing to solve this problem and do we need to do the same thing?