Synthetic Patient Data in Clinical Trials: Why it’s important to have meaningful synthetic data. 

It is time consuming and difficult to manually generate the test data to support Clinical Programming (CP)/Biostatistics and statistical processes and the differences in the quality and coverage of only limited type of scenario in test data causes the delay in the quality check processes.

To overcome these challenges, we should have the capability to generate the artificial data automatically with the use of synthetic data generation software that can be utilized to support these processes. Data which is not collected from real world event(s) and generated artificially is referred as synthetic data. 

Just Synthetic Data or should it be Meaningful Synthetic Data? 

Does it make difference? 


To fulfil the requirements to support Clinical Programming (CP)/Biostatistics and statistical processes, the availability of synthetic data which is not meaningful won’t be sufficient.

To cover all the scenarios of the real clinical trial data there are several points those needs to be considered and taken care of.

Such as, links between the forms/datasets i.e. concomitant medication (CM) given for an adverse even (AE) is not matching or not entered; results of pregnancy test should be available for females not males, etc. There are several such instances where synthetic data which is not meaningful will fail to serve the purpose. 

On the other hand, meaningful synthetic data covers all the scenarios required to boost Clinical Programming (CP)/programming/statistical processes. 

How can GENINVO help you generate “meaningful” synthetic data?  

GENINVO’s Datalution™ is all in one solution for generating meaningful synthetic data for testing electronic data capture, edit checks, data management (as part of UAT Process), programming, and statistical setup activities for Dry Run (mapping/transformation, TLFs & visualization ) and more. 

Advantages of using Datalution™

  • Easy to use user interface. 
  • Generate Real like synthetic data for upcoming or ongoing clinical trials integrated with patient journey. 
  • Zero risk of de-identifying patients 
  • Allow stake holders to have data at right time and increase the trial efficiency by performing data operations quickly without hick-ups. 
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