Clinical Data Management (CDM) plays a significant role in the implementation of Risk-Based Monitoring (RBM) within clinical trials. RBM is an approach that focuses monitoring efforts on areas of highest risk, thereby optimizing resource allocation, enhancing data quality, and ensuring patient safety. Here's how CDM contributes to RBM

1. Welcome
ROLE OF CLINICAL DATA MANAGEMENT IN RISK-
BASED MONITERING
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Name : Vannewada indu
Qualification :Msc biotechnology
Student ID : CLS_131/072023

2. What is Clinical Data management
Clinical Data Management involved in all aspects of processing the clinical data, working with a range of
computer applications, database systems to support collection, cleaning and management of subject or trial
data.
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3. Objectives of CDM
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Paper, Electronic and Remote data capture
Integration of data received from all sources in a
single DB. Ensures consistency and correctness
System validation done via UAT, QC and
programming Data Validation via edit check
programs and manual review
Data collection
Data integration
System / Data
validation

4. Importance of CDM
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CDM is a vital vehicle in Clinical Trails to ensure integrity & quality of data being transferred
from trial subjects to a database system. It helps:
• To provide consistent, accurate & valid clinical data
• To support accuracy of final conclusions & report

5. Good Clinical Data Management
Practice (GCDMP)
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• The objective of GCDMP is to generate high quality database devoid od errors and omissions
• ICH Guidelines
• US FDA REGULATIONS
• DRUG AND DEVICE DEVELOPMENT PROCESS
The society of clinical data management (SCDM) has created a comprehensive document- Good Clinical Data
Management practices (GCDMP) (Version 4.0 is the most recently updated version published in May 2007)- that
provides guidance on accepted practices of Clinical Data Management (CDM).

6. Risk-Based Monitoring in clinical Data
Management
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Risk-based monitoring (RBM) is a proactive approach to monitoring clinical trial data that focuses on
identifying and mitigating risks to data quality and study integrity. Traditional on-site monitoring, which
involves 100% source data verification (SDV), can be resource-intensive and may not effectively detect all
data issues. RBM aims to allocate monitoring resources more efficiently by focusing on critical data and
high-risk areas.
Interactions : Sponsors, Clinical Operations and CDM
Risk-Based Monitoring
 Challenges for Sponsors
 Challenges for Monitors
 Challenges for CDM

7. Traditional paper-Based work-flow
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8. Data flow & Monitoring : The Future
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9. Risk Identification and Assessment
 RBM starts with the identification and assessment of potential risks to data quality and study
endpoints.
 - Risks can arise from various Human Subjects Research courses, such as protocol deviations,
data collection errors, site performance issues, and data integrity concerns.
 - Risk assessment involves evaluating the likelihood and potential impact of identified risks on the
integrity and quality of study data.
Risk Prioritization and Monitoring Strategy
 Based on the risk assessment, risks are prioritized according to their significance, allowing for the
allocation of monitoring resources and the development of a tailored monitoring strategy.
 - High-risk areas may require more intensive monitoring, while low-risk areas may benefit from
less frequent or less comprehensive monitoring.
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10. Centralized Monitoring and source Data
verification (SDV)
 RBM emphasizes centralized monitoring methodologies that leverage technology and statistical
analysis to identify trends, outliers, and potential data anomalies.
 Rather than conducting 100% SDV, RBM utilizes targeted SDV based on the risk assessment and
critical data elements.
Key Risk Indicators (KRIs)
 KRIs are predefined metrics used to monitor key aspects of the study and assess data quality and
integrity.
 - KRIs may include metrics related to data completeness, data accuracy, protocol deviations,
patient enrollment rates, and data discrepancies.
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11. Supporting Risked-Based Monitoring – Challenges for Sponsors
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• “The most important tool for ensuring human subject protection and high-quality data is a well-designed
and articulated protocol.”
• Guidance intends to assist sponsors in developing risk-based monitoring strategies and plans.
- Tailored to the specific human subject protection and data integrity risks of the trial
- Focuses on critical study parameters
- Encourages use of a combination of monitoring activities
- Encourages greater reliance on centralized monitoring practices, where
appropriate –it is OK not to do 100% SDV

12. Supporting Risked-based Monitoring Challenges in
CDM
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• Centralized Monitoring
• Quality and integrity checks
- Increased checks
- Increased data collection
• Technologically Few Challenges

13. Data quality/ Integrity
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 Identify critical study data and processes, e.g.
- End points
- Serious Adverse Events
- Randomization/ Blinding
- Consent
- Eligibility Criteria
- Risks specific to protocol design and conduct
 Perform and document a risk assessment to identify risks to these critical data and
processes
 Design plans tailored to address important and likely risks identified during risk
assessment.

14. Role or skill set Adjustments Needed to support Risked-Based
Monitoring
 Sponsors
 Site Coordinators/ staff
 CRAs/Monitors
-Increases in support and technology skills
• CDM
- Increases in technology process
- Increases in training skills
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15. Summary
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 From the perspective of CDM
- Need Coordination in planning across functional groups/departments
- No overwhelming hurdles to implementation
 Process integration is key to efficient use of resources and to add quality.

16. Reference
 Law S. Clinical Data Quality & Query Resolution Costs. Linkedin; 2017. Available at
https://www. linkedin.com/pulse/clinical-data-quality-queryresolution-costs-steven-law/.
Ac
 TransCelerate Biopharma Inc. Position Paper: RiskBased Monitoring Methodology. 2013.
Available at https://www.transceleratebiopharmainc.com/ wp-
content/uploads/2013/10/TransCelerate-RBMPosition-Paper-FINAL-30MAY2013.pd
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17. Thank You!
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(INDIA | CANADA)
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