Clinical Data Management plays a vital role in clinical research. It is involved in all aspects of processing clinical data and ensures that data gathered is accurate, complete, logical and consistent. In doing to the data is fit for statistical analysis, presentation and interpretation.

Clinical trial data gathered at the investigator site in the case report forms are stored in the Clinical Data Management System (CDMS). CDMS is a tool(s) intended to ensure that data gathered in the course of study is accurate, complete, logical and consistent. CDMS must be comply with the regulatory requirements (21CFR Part11). Commonly used CDMS are: Oracle clinical, Rave, Clinitrail, Promasys, Macro and eClinical Suite etc.

A database is simply a structured set of data and in its simplest form can be defined as a collection of rows and columns. Database design should allow for capture of all data on the CRF. eCRF should be an exact copy of the CRF design which allows entry of all data captured on the CRF. Once the funding for a trial has been secured, it is essential that the design of the database is initiated. If the research team is independent from the database design team, then, a user specification or requirements document is prepared by the research team that clearly explains the requirements of the database for a trial.

Roles and Responsibilities

• Trial Management Team: generation of user requirements/specifications document; user testing.
• Database Programmer: Development of the database, creation and implementation of edit checks, validation rules and logic checks.
• Data Manager: Creation of annotated CRF, DVP and DMP.
• Database Administrator: Creation of user access control.

The database should be designed in order to prevent errors in data management, archival, retrieval or transmission. Thorough documentation must exist at all levels of a clinical trial’s data collection and management process.

Computer systems used in the processing and management of clinical trial data must be sufficiently validated and tested prior to the development of the database. Validation of the database is essential, as it plays a key role in providing a high quality database that complies with all applicable regulations. It also helps demonstrate the quality of the data generated during the trial. Validation refers to both, validation of the Clinical Data Management System (CDMS) and/or validation of the programming related to the development of the database. CDMS validation involves Installation Qualification (IQ), Operational Qualification (OQ) and Performance Qualification (PQ). IQ and OQ are generally performed by the vendor which involves installation of the database and configuration of the server, and ensuring that the all system requirements are installed in the CDMS. Post-installation, the vendor conducts performance testing (OQ). The Data Management team then populates the database with dummy or test data on the system, to test the features on CDMS (PQ). In addition to any documentation provided by the vendor, trial-specific database manuals are developed with the help of screenshots (capturing all the steps) taken during the process of IQ, OQ and PQ.

Validation is required to confirm that the software has been developed in line with the requirements stated by the user, and is fit for purpose. User Acceptance testing (UAT), is an element of validation and is performed once the database has been developed. This is performed before the CDMS is used to capture/process any live data. It is performed by a user of the database or CDMS (data entry operators, data managers, medical department, statistician and principal investigator), and should follow a predefined protocol detailing each step and expected result with clearly defined pass and fail values. The UAT report provides objective evidence for the validation process. Once UAT has been successfully completed and documented and any remedial actions implemented and retested, the test database is moved into production mode to capture live trial data.

References and Further Reading

• Good Clinical Data Management Practices, Society for Clinical Data Management, October 2013 edition, available online (last accessed on 26.02.2019).
• Good Clinical Practices for Clinical Research in India, Central Drugs Standard Control Organization, Ministry of Health and Family Welfare, 2001, available online (last accessed on 26.02.2019).
• ICH Harmonised Guideline, Integrated Addendum to ICH E6(R1): Guideline for Good Clinical Practice E6(R2), current step 4 version, dated 9^th November 2016, available online (last accessed on 26.02.2019).
• MRC Clinical Trials Unit at University College London SOP on Database Development, version 4.0, 2017.