Translational Health Science and Technology Institute
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The Clinical Portfolio Management vertical is an integral and core strength of CDSA. The team has successfully supported the delivery of numerous high quality research projects across a variety of disease areas. CDSA has partnered with both national and global stakeholders to support the conduct of regulatory trials, academic clinical studies, longitudinal cohort studies and national surveys.
The various verticals within CDSA can support studies and trials from the planning stage to publication of results, depending on the services requested.
The Data Science team plays an important role at CDSA and provides a range of solutions to projects undertaken at CDSA, THSTI. The team helps with the development and set-up of data management systems tailored for the project. This includes initiatives to develop and promote best practices in several areas including database development, adherence to regulatory requirements, standardization and simplification, data management methods, quality control and assurance. The CDSA Data Science team helps with:
CDSA utilises different databases and approaches, depending on the needs of the study, including (but not limited to) commercial Clinical Data Management Systems (CDMS) including ODK which supports both online and offline data capture. CDSA also provides data management service through globally accepted open sources like REDCap. The DM standards and procedures are tailored to ensure an optimal utilization of CDMS and monitoring tools.
The team works in collaboration with the IT team, statisticians and other members of the Trial & Study Management team and ensures that the internal data management methods are constantly reviewed and updated to ensure the quality, reliability, timeliness and their cost effectiveness.
At CDSA, the following systems are used to provide data management, project management and monitoring support to the studies:
CDSA has procured two commercial software to capture the participant’s clinical data. Both systems are validated and 21CFR part11 compliant, support paper based as well as electronic data capture. Both support real time data entry, online query management, remote monitoring, medical coding, data extraction, SAE data reconciliation, and batch data load for external data such as lab, ECG etc.
These can also be integrated with other tools like CTMS, BMS and eTMF.
Based upon the study budget and participant numbers, CDSA also offers data management service on validated open sources like REDCap and ODK tool.
It is a validated and regulatory complaint commercial software which is used to maintain, manage and supervise the study planning, performance, and reporting of the clinical trials, with an emphasis on keeping up-to-date contact information for participants, tracking deadlines, milestones, and documents such as those for regulatory approval or the issue of progress reports. It is a common platform, which enables access to all stakeholders irrespective of their location.
A validated computerized system used for managing the electronic inventory of the bio specimens collected under clinical research studies. Biorepository management system enables the users to track, store, manage and analyse bio specimens for instant and quality retrieval based on requests received by researchers to address their project requirements.
It is used for maintaining the trial master file electronically by organizing and storing the documents, images, and other content related to the study centrally. This data is stored on cloud which has a dedicated and secure server based in India. This tool is very useful for the monitoring teams to review the site files online.
Clinical Data Management (CDM) is one of the core strengths of CDSA for supporting the
clinical studies. CDSA currently provides data management support to many multi-centric clinical
studies and clinical trials. this ranges from case report form (CRF) designing to database development, database lock and archival.
CDSA has robust processes and data capture systems that ensures reliable data quality and an audit trail. The clinical data management systems at CDSA are installed in a secure and validated environment.
CDSA’s CDM support covers the entire spectrum of CRF designing, database development either through
the development of paper records or through remote electronic data capture systems, writing standard operating
procedures for quality adherence and CRF filling guidelines. Preparation of study related technical documents like
annotated CRF, data management plan & data validation plan/ edit specifications document, extraction/ import from
external databases lab, medical images (like ECG), SAE reconciliation, query management, database lock and freeze
followed by export to SAS/STATA/R/SPSS for statistical analysis with an audit trail to keep track of
modifications and changes done in data by users, followed by procedures for data archiving.
It is imperative that all data be held securely, robustly backed up and its confidentiality safeguarded. At CDSA, data integrity and confidentiality is maintained within CDMS (Clinical Data Management System) by a robust program security which provides restricted access to users, requires a login and password to access the program, monitors user activity andhas a time-stamped audit-trail system to help track changes to data.
CDSA also manages the central data repository for the scientific inventory for various consortiums and programs fornew assays, viral isolates, products, reagents, etc. and the clinical data generated and assists with the developmentof data sharing plans after consultation with all stakeholders.
At CDSA, quality of data is maintained across all stages starting from the initiation of the study for e.g., CRF designing, database development, implementation of edit checks and validation rules, User Acceptance Testing (UAT), training to the users, user management with restricted access as per their role and responsibility. QC of generated and collected data is performed at regular intervals. Interim tabulations and scatter plots for some key variables are made at regular intervals to identify potential data errors.
Data ownership and access is decided by the partner(s) generating the data and access is provided to all partners for the conduct of the project.