Automating an End-to-End Clinical Data Workflow with a Platform Approach
Innovation in clinical development continues to accelerate and decentralized trial models are becoming more widely adopted. As a result, the volume of clinical trial data from a variety of sources continues to proliferate, making end-to-end clinical data flow complex. Leveraging the right technology provides an opportunity to automate end-to-end data flow for improved data quality, greater efficiency and streamlined production of submission deliverables.
The elluminate Clinical Data Cloud serves as a foundation for digital trials, providing a centralized location for all clinical and operational data, regardless of source. The elluminate Statistical Computing Environment (SCE) is fully integrated within the elluminate Clinical Data Cloud. This enables the production of submission or exploratory analysis outputs in a way that is automated, transparent, auditable and reproducible.
This webinar will cover the core capabilities of elluminate SCE. The featured speakers will highlight how built-in automation and access to data, standards and mappings can be leveraged to maximize reuse and increase programming and analysis efficiencies.
Join this webinar to learn the benefits of a clinical data platform that automates data ingestion, standardization and publishing.
Who Should Attend
- Clinical Programmers
- Statistical Programmers
- Data Scientists
- R&D IT Leaders
What You Will Learn
- Benefits of leveraging a clinical data platform that automates the ingestion, standardization and publishing of all the clinical and operational data
- Advantages of utilizing a validated environment with built-in automation and access to all data, metadata, programs and results for the production of submission or exploratory analysis outputs
- How taking a platform approach allows greater accessibility, interoperability, reusability and automation in statistical analyses and programming processes
Nathan Johnson is Vice President, Digital Innovation at eClinical Solutions. Nathan has 20 years experience in clinical research as an innovator and programmer with expertise in statistical analysis and reporting, SAS programming, standards development, and data management. He is passionate about reshaping clinical trials through digital transformation, intelligent technology, and increased automation. Nathan has a Masters in biostatistics from Case Western Reserve University.
Berber Snoeijer started in clinical research in 1997 as a biometrician and has since then worked with clinical data in different functions. In 2001 she started a CRO, Biometric Support, aiming at the data management, data analysis and reporting of clinical trials. She switched in 2011 to work as a R&D manager dedicated to investigate and utilize the potential of real world data from electronic health records. This resulted in many different solutions including a full reporting system to give feedback information to clinical research professionals. She is experienced with software and database engineering, process engineering, and improving efficient utilization and interactions of people based on management drivers. Nowadays, she uses these skills and knowledge to help life science companies assess, design, and improve business solutions and processes at smaller and larger scales.