DATA VALIDATION IN CDM
Introduction
CDM is the process of collection, cleaning, and management of subject data in compliance with regulatory standards. The primary objective of CDM processes is to provide high-quality data by keeping the number of errors and missing data as low as possible and gather maximum data for analysis.
Data validation is the process of testing the validity of data in accordance with the protocol specifications. Edit check programs are written to identify the discrepancies in the entered data, which are embedded in the database, to ensure data validity.
Data Validation in CDM:
Clinical Data Management (CDM) is a critical phase in clinical research, which leads to generation of high-quality, reliable, and statistically sound data from clinical trials. This helps to produce a drastic reduction in time from drug development to marketing.
Tools for CDM:
Many software tools are available for data management, and these are called Clinical Data Management Systems (CDMS).
In multicentric trials, a CDMS has become essential to handle the huge amount of data. Most of the CDMS used in pharmaceutical companies are commercial, but a few open source tools are available as well. Commonly used CDM tools are
ORACLE CLINICAL,
CLINTRIAL,
MACRO, RAVE, and
eClinical Suite.
The primary objective of Clinical Data Management (CDM) is to ensure timely delivery of high-quality data which are necessary to satisfy both good clinical practice (GCP) requirements and the statistical analysis and reporting requirements.
CDM data validation activities play a critical role within the drug development programme involving many people, multiple systems and several data transfers.
List of clinical data management activities:
Database design
Data collection
CRF tracking
Data entry
Discrepancy management
Medical coding
Database locking
The quality of the data validation process has a direct impact on the quality of data presented as part of an NDA submission. There is a general misconception that data validation activities commence when clinical trial data are presented to the sponsor’s data management department. The author will attempt to dispel this somewhat narrow view and discuss various stages of data validation activities which actually start when the investigator records the data on the case report form (CRF) and when the final medical report is issued as part of the overall clinical trial data handing and reporting process.
Data validation process during the conduct of a Clinical Trial
It is a defined number of steps needed to turn the original or ‘raw’ item or items into the finished item, that is to turn CRF data into a clean database. These steps should ensure that the database is accurate, consistent and a true representation of the patient’s profile.
Data Validation Steps Performed by the Investigator
The GCP guidelines are quite clear on when the data validation step starts; the ICH guidelines state: ‘The investigator should ensure the accuracy, completeness, legibility, and timeliness for the data reported to the sponsor in the CRFs and in all required reports.’ The investigator should ensure that any data reported on the CRF are consistent with the patient’s medical records and, where applicable, discrepancies should be explained.
The sponsor should ensure investigator training and education on the need to accurately record data on CRFs and the impact this has on the overall quality of the clinical trial. A perfect data management system can do little to improve sloppy data produced at the investigator site.
Data Validation Steps Performed by the Monitor
GCP states that the ‘monitor should check the CRF entries with the source documents and inform the investigator of any errors/omissions’ and ‘assure that all data are correctly and completely recorded and reported’.
Data Validation Steps Performed by CDM
CDM data validation activities are an integral part of GCP and fundamental to the delivery of high-quality data for statistical analyses and reporting. Attention should be focused on ensuring that the data are a reasonable representation of what actually happened at the investigator site. The aim is to transform data recorded on CRFs into information that can be used in the final clinical report from which the right conclusions about the new drug can be made. Figure 6.1 represents a generic model for processing CRFs through CDM’s data validation activities. Data clarification queries are issued to the investigator at various stages in the process, in particular, as a result of pre-entry review, data entry, and the running of edit checks.
CDM data validation guidelines should be developed to ensure data are processed in such a way as to maximise data integrity and to deliver high quality data for analyses and reporting.
CDM Data Validation In The Future:
In the quest to reduce development times of new drugs, new technologies and working practices are being tried and tested within CDM. These new systems have a direct impact on the data validation process. If we were to look at RDE, the investigator would enter data directly into the RDE system via electronic CRFs. The core of the edit checks could be implemented within the RDE software. Thus, the majority of the validation checks would be performed in ‘real time’ at the investigator site. RDE would streamline processes and make data capture more efficient by displacing activities which are a bottleneck or by removing those which do not provide significant added value.
In the future, the success of new systems such as those mentioned above will be measured in terms of:
Time savings (data flow from investigator site to sponsor, processing time)
Reduction in resource requirements (with sponsor’s clinical and CDM groups)
Improvement in Data Quality
Endorsement by regulatory authorities
Conclusion:
CDMs are charged with producing high-quality databases that meet clinical and regulatory requirements. The quality of a clinical trial determines the acceptability of the results and care must be taken to ensure that high standards of quality are present both in the clinical trial design and in the integrity and interpretation of data. To this end, all participants in the clinical trial have a role to play in safeguarding data integrity. As discussed, data validation activities start at the investigator site and end with a statement in clinical or expert reports to indicate that the clinical trial was conducted in accordance with GCP and that the report provides a complete and accurate account of the data collected during the trial.
Reference:
Clinical Data Management, 2nd Edition. Richard K. Rondel, Sheila A. Varley, Colin F. Webb Copyright 1993, 2000 John Wiley & Sons Ltd.
Student Name: Gali. Nikky bhedi
Student ID: 010/012023
Qualification: M pharmacy
e-Mail ID: nikkybhedi0904@gmail.com
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