Effective Clinical Data Management (CDM) is essential in running a clinical trial. Otherwise, the reliability and accuracy of any evidence of the drug’s therapeutic value under examination may be called into question.
This post explores the role of clinical data management in clinical trials in the life sciences, including the relevant regulatory requirements. We will provide eight essentials for clinical data management to help you ensure the reliability and integrity of your organization’s trial data.
Why Clinical Data Management (CDM) Matters
The role of the clinical data management (CDM) team is to ensure proper collection, integration, and validation of all data relating to a clinical trial. This is essential to the overall research program, as the overarching goal of CDM is to ensure that conclusions drawn from a clinical trial or other research are well-supported by the data.
The CDM process must be capable of assuring the accuracy and integrity of the clinical trial data so that results from the trial can be relied on. The process also must ensure that the data are of sufficient quality to provide regulators with all the information needed to properly assess the safety and effectiveness of the drug on trial.
Insufficient or inaccurate data risks undermining the effort and resources invested in the clinical trial and extending the time-to-market for a new drug. Members of the CDM team are involved in all stages of the clinical trial, from concept to completion, to ensure all relevant data are collected and available for analysis and presentation.
CDM Regulatory Compliance Issues
For the data from a trial to be eligible for use as part of a submission to the regulatory authority, it must comply with the requirements of 21 CFR Part 11 – the Code of Federal Regulations Title 21, Chapter 1, Subchapter A, Part 11, Electronic records, electronic signatures.
This section stipulates that where “systems are used to create, modify, maintain, or transmit electronic records,” it is necessary to “employ procedures and controls designed to ensure the authenticity, integrity, and, as appropriate, the confidentiality of electronic records from the point of their creation to the point of their receipt.”
The regulation lists the procedures and controls required, with a key point for CDM being, “validation of systems to ensure accuracy, reliability, consistent intended performance, and the ability to discern invalid or altered records.”
For practical guidance on creating systems for data management in compliance with the CFR, the Society for Clinical Data Management (SCDM) has published an authoritative guide to best practice: Good Clinical Data Management Practices (GCDMP).
The GCDMP is not a regulatory document per se. Still, it does represent the current industry standards for clinical data management, including best business practices and best practices to meet regulatory standards.
How does CDM work?
Members of the CDM team need to be involved from the very beginning of a clinical trial, even before the study protocol is finalized. This allows the team to design a Case Report Form (CRF) with the data fields that meet the specific needs of the trial.
CRFs itemize the type of data that must be collected, the units of measurement to be used, and provide instructions for data entry (also known as CRF completion guidelines).
To guide their project work, the team will develop a Data Management Plan (DMP) that will set out the CDM activities for the trial.
They will then build and test the databases to support the CDM tasks with corresponding compliance tools. With the system in place, the team is then ready to manage the succeeding stages in the CDM process: CRF tracking, data entry, validation, discrepancy management, medical coding, and, finally, database locking.
Case report forms may be in paper or electronic format, though increasingly electronic data collection has become the norm for efficiency and cost-effectiveness. Electronic formats also enable further time-saving through remote data entry (e-CRF) and greater data reliability by eliminating transcription errors.
8 Essential Questions for Clinical Data Management
To gather the high-quality, reliable, and statistically sound data needed from a clinical trial, pharmaceutical companies and other life science organizations need to be able to answer these eight essential questions.
1. What’s your plan for collecting and managing the data?
The first essential is to have a plan that documents, in detail, how you will securely collect and store the trial data. This includes:
- Who will collect the data
- How many trial sites are involved
- Who will review and sign off on the data
- How will you share and analyze the information?
Your plan needs to encompass all CDM activities from startup to database closeout.
2. How will you capture the data?
Involve all key stakeholders in setting up case report forms and electronic data capture systems – including the sponsor, the study team, data entry personnel, statisticians, and clinical operations personnel.
In setting up your electronic data capture system, be sure to follow accepted standards as outlined in the CDISC and other relevant standards such as the Clinical Data Acquisition Standards Harmonization (CDASH).
3. How will you ensure secure access for team members?
Every person involved with the study will have specific roles and responsibilities regarding data capture and oversight during the trial. Your electronic data capture (EDC) system must provide secure, structured, and documented access so that each participant can fulfill their duties while preserving the integrity of the data.
4. How will you ensure high-quality data?
Reducing data collection and reporting errors reduces the time and use of resources investigating and correcting problems.
Creating well-defined SOPs that clearly outline organizational practices and role-specific responsibilities will help increase the accuracy of data collection – and can make it easier to identify the cause of any errors.
5. Which data points are the most important?
At the start of the clinical trial process, it’s essential to identify the critical data points. These data need to be measured to answer the scientific questions the trial is examining.
In addition, it’s important to remember to collect the data relating to the associated questions, for example, to establish the safety profile of the drug.
6. How will you ensure your operating procedures meet requirements?
It can help to develop SOPs collaboratively, involving all relevant organization members. This is an opportunity to document the best elements of current data collection practices and identify areas for improvement.
7. Is staff properly trained and prepared?
It’s vital to ensure all team members are properly trained and know how to use your data collection and management systems. For best results, they must be familiar with best practice guidelines and the regulatory requirements relevant to their role.
8. What is the system for managing the data?
In today’s fast-paced world, there is constant pressure to improve CDM standards and reduce the time-to-market for drug development. Secure and efficient data capture and analysis can significantly reduce the time to trial data submission for regulatory approval and allow faster product commercialization.
In this context, a QMS pre-configured on clinical trial best practice process that can integrate with leading data capture applications offers a comprehensive, cost-effective solution to ensure data quality and regulatory compliance for clinical data management.
Clinical Data Management and QMS
Effective data management is critical for a clinical trial’s success. Without sound data, a drug cannot obtain regulatory approval. Even in cases where the trial evidence does not support the hypothesis, having sound data can help to identify new avenues to explore.
A QMS designed for the life sciences industry enables highly efficient and cost-effective deployment for managing, analyzing, and preparing clinical trial data for submission. The QMS can be installed quickly with minimal setup and offers a robust, integrated process covering all aspects of trial data management, including simplified team collaboration.
Ensuring that CDM is organized, efficient, and meets all compliance requirements creates benefits for all stakeholders in a clinical trial and increases ROI for the development process, regardless of trial results.
