Indegene helps a Global CRO streamline collection of clinical trials data by automating eCRFs creation for their EDC systems

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Challenges

Poor quality electronic Case Report Forms (eCRFs) created using traditional approaches was not effective in data collection of clinical trials which led to significant process inefficiencies
Lack of global standardization for eCRFsglobal standardization for eCRFs, and difficulties in mapping eCRF variables to Study Data Tabulation Model (SDTM) variables

The Solution

Indegene deployed NEXT Study Build Automation, an AI/ML and NLP-based solution, which helped the CRO manage eCRF standardshelped the CRO manage eCRF standards across multiple phases and indications for study protocols. The solution was able to:

Ingest and analyze the contents of every protocol, and recommend the best eCRF designs
Automate the design of the eCRFsAutomate the design of the eCRFs, and conduct standard edit checks
Map SDTM for all source eCRF variables and generate fully executable SAS programs by complementing EDC with the SDTM module
Generate an importable file for the Medidata Rave EDC system to complete the build and go live

Outcomes

80%

Reduction in EDC build efforts

80%

Reduction in efforts for validation of edit checks

70%

Reduction in efforts for SDTM programming

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Automate effective eCRFs creation for your EDC systems