Beyond EDC: Custom reports

This is the fifth and final article in our series on the evolving EDC landscape and the pressing challenges shaping the industry’s evolution. 

In the previous article Beyond EDC: Wearable integrations, we explored Viedoc’s recent proof-of-concept smartwatch integration study, and its implications for clinical trials.    

In this article, we once again turn to Majd Mirza, Viedoc’s Chief Innovation Officer and Binish Peter, Technical Fellow at Viedoc to discuss how we can export, transform, and generate reports and dashboards, before pushing them to an external data repository used in clinical research. 

It’s time to think beyond EDC. 
 

​​Setting the scene​ 

This is another application of the data bridge discussed in previous articles. The goal is to transfer data from Viedoc’s EDC system to an external data warehouse or system, similar to a CTMS integration. 

Unlike a CTMS integration though, this process transfers all data, including both standard and custom reports. Reports are developed using R, a programming language widely used for data transformation, analysis, and visualization. 

As a result, clients can automate daily data transfers, ensuring their external systems always have the latest data. This means users can access all exported data, including reports, within their preferred analytics environment, without needing to interact directly with the EDC. The process also facilitates automated data backups. 
 

Integrating the Viedoc way 

This use case involves transferring data from Viedoc’s EDC system to an external data repository commonly used in clinical research. While this example focuses on LSAF (SAS Life Science Analytics Framework), the same approach applies to any destination system that can receive data using an API. 
 
Once a connector has been developed for a specific system, it can be reused for future integrations with that same system, eliminating the need to build a new connector each time. 

The workflow consists of several pipeline activities: 

1. Data export activity 

A clinical data report is generated and prepared for processing. 

2. Data conversion  

Exported CSV files are converted to RDS, a format readable by R. 

3. Custom report execution 

Custom R-based reports are generated using the same report logic available in Viedoc Reports. 

4. Data transfer 

A compressed (.zip) file containing all processed data is pushed to the external repository.

“This process is fully configurable,” explains Majd. “You control the frequency, number, and format of reports, as well as the destination system.” 

Viedoc supports both R and Python, allowing users to apply their own transformations, analyses, and data processing, before pushing the results to external systems. 

In addition to generating custom reports, this data pipeline provides an easy and efficient way to run AI models in real time or on a scheduled basis, leveraging Python as a programming language. For example, if a study receives large volumes of data from a wearable device, instead of running a custom report, an AI model can process the exported data, detecting anomalies such as outliers or unexpected patterns. The raw data can also be automatically transformed into a predefined format. 

“The possibilities are endless”, Binish summarizes. “Whether you are using an AI model, graphing, statistics, or a custom report, you have complete freedom to write any program. With reliable data extraction and integration capabilities, you can trust that your processes will run as scheduled.” 

Beyond EDC 

With the increasing volume of data and diverse sources, clinical studies no longer store all data in one system but instead leverage multiple systems, each holding key pieces of information.  

When we talk about Beyond EDC, we recognize that the role of EDC systems is shifting from being the sole data repository to becoming an integrated part of a broader ecosystem, where multiple systems work together to manage and analyze diverse data sources. Seamless collection, transformation, and distribution of data to where it is needed for analysis, reporting or further processing is crucial in this new paradigm. 

Thanks for looking beyond EDC with us—here are links to all the articles in the series: 

1. Current challenges
2. Solutions and capabilities
3. Enhancing clinical trials through CTMS integrations
4. Wearable integrations 

And why not explore our EDC software to learn more about how the Viedoc eClinical suite can elevate your data strategy.