What is it? Why is it important?

Automated Data Processing is the use of technology with the aim to convert data into a more useful format or needed information (e.g. age upon study start, BMI based on height and weight). Automated processing has an important advantage, as it excludes human calculation errors.


Data processing can be done either before or after being entered in the study database.


Automated processing requires:

  • An electronic database (e.g. CDMS)
  • Ability to program processing procedures (e.g. calculations, classification)
  • Ability to perform applicable validations procedures to ensure automated processing was correctly implemented



Calculation of creatinine clearance requires the input of raw data into an applicable formula (age, weight, serum creatinine, and gender). Upon automated data processing the creatinine clearance number is no longer raw data but automated processed data.

What do I need to do?

As a SP-INV and based on data needed to answer your study question:

  • Make a list of study data (variables) that can only be obtained through automated processing
  • Define which variables are needed for the automated processing
  • Ask your data manager to program any required automated processing procedure(s) in the study database
  • In the event processing procedures are performed prior to being entered in the study database, provide applicable staff guidelines and ensure the technical equipment is validated for its intended use (e.g. pocket calculator, stop-watch). An added control measure supporting the detection input-errors are upper and lower input limits to input variables in the database.
  • Include a test phase to ensure automated data processing is correctly implemented
  • Document any performed validation procedures
  • Describe any automated processing in the DMP


Where can I get help?

Your local CTU can support you with experienced staff regarding this topic


ICH GCP E6(R2) – see in particular guideline

  • 5.5 Trial management, data handling, and record-keeping
  • CDMS – Clinical Data Management System
  • CTU – Clinical Trials Unit
  • DMP – Data Management Plan
  • ICH GCP – International Council for Harmonisation - Good Clinical Practice
Development ↦ Data Handling ↦ Database Development ↦ Automated Data Processing

Provides some background knowledge and basic definitions

Basic Monitoring
Basic Drug or Device

Starts with a study idea

Ends after having assessed and evaluated study feasibility

Concept Drug or Device

Starts with confidence that the study is feasible

Ends after having received ethics and regulatory approval

Development Drug or Device

Starts with ethics and regulatory approval

Ends after successful study initiation

Set-Up Ethics and Laws
Set-Up Quality and Risk
Set-Up Drug or Device

Starts with participant recruitment

Ends after the last participant has completed the last study visit

Conduct Drug or Device

Starts with last study visit completed

Ends after study publication and archiving

Completion Statistics
Completion Drug or Device
Current Path (click to copy): Development ↦ Data Handling ↦ Database Development ↦ Automated Data Processing

Please note: the Easy-GCS tool is currently under construction.