centralized monitoring: the role of process and technology · •cro oversight •clinical data...
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March 20, 2019
Centralized Monitoring: The Role of Process and Technology
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Veeva Intro Placeholder
Emanate Life Sciences
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•Provide CRO oversight •Provide 3rd party vendor oversight
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Speakers
Alec VardySenior Director, Data Management
Jazz Pharmaceuticals
Tom DekkerSenior Product Manager
Veeva Systems
Centralized MonitoringAlec VardyMarch 20th, 2019
Centralized Monitoring
Topics to be addressed: What is it? What are (some of) the implications? Thoughts on implementation
What is Centralized Monitoring?
Centralized Monitoring
On-site Monitoring
Remote Monitoring
What is Centralized Monitoring?ICH E6 R2 -- Addendum to 5.18.3 Extent and Nature of Monitoring tells us some of the things that centralized monitoring is expected to do.
Review, that may include statistical analyses, of accumulating data from centralized monitoring can be used to:
(a) identify missing data, inconsistent data, data outliers, unexpected lack of variability and protocol deviations.
(b) examine data trends such as the range, consistency, and variability of data within and across sites.
(c) evaluate for systematic or significant errors in data collection and reporting at a site or across sites; or potential data manipulation or data integrity problems.
(d) analyze site characteristics and performance metrics.(e) select sites and/or processes for targeted on-site monitoring
What is Centralized Monitoring?(a) identify missing data, inconsistent data, data outliers, unexpected lack
of variability and protocol deviations.
(b) examine data trends such as the range, consistency, and variability of data within and across sites.
(c) evaluate for systematic or significant errors in data collection and reporting at a site or across sites; or potential data manipulation or data integrity problems.
(d) analyze site characteristics and performance metrics.
(e) select sites and/or processes for targeted on-site monitoring
What is Centralized Monitoring?(a) identify missing data, inconsistent data, data outliers, unexpected lack
of variability and protocol deviations.
(b) examine data trends such as the range, consistency, and variability of data within and across sites.
(c) evaluate for systematic or significant errors in data collection and reporting at a site or across sites; or potential data manipulation or data integrity problems.
(d) analyze site characteristics and performance metrics.
(e) select sites and/or processes for targeted on-site monitoring
What is Centralized Monitoring?(a) identify missing data, inconsistent data, data outliers, unexpected lack
of variability and protocol deviations.
(b) examine data trends such as the range, consistency, and variability of data within and across sites.
(c) evaluate for systematic or significant errors in data collection and reporting at a site or across sites; or potential data manipulation or data integrity problems.
(d) analyze site characteristics and performance metrics.
(e) select sites and/or processes for targeted on-site monitoring
What is Centralized Monitoring?(a) identify missing data, inconsistent data, data outliers, unexpected lack
of variability and protocol deviations.
(b) examine data trends such as the range, consistency, and variability of data within and across sites.
(c) evaluate for systematic or significant errors in data collection and reporting at a site or across sites; or potential data manipulation or data integrity problems.
(d) analyze site characteristics and performance metrics.
(e) select sites and/or processes for targeted on-site monitoring
What are the implications?We need to look for unexpected lack of variability, examine data trends such as the range and variability of data within and across sites, and evaluate for potential data manipulation
We need to analyze site characteristics to select sites and/or processes for targeted on-site monitoring
We need to document plans, activities, conclusions and actions
What are the implications?
• Understand the mechanisms / processes that generate the data
• Target investigations accordingly
Data manipulation
• Typically done currently to identify and resolve issues
• Need to switch to a more predictive and proactive approach
Analyzing site characteristics
What are the implications?
• Support primary and key secondary objectives:
• Critical to subject safety• Support decision-making about
efficacy and safety of the drug
Critical Data
• Generate critical data• Support ethical and GCP
complianceCritical Processes
What are the implications?
• Variables assessed by comparison across countries, CRAs, and/or sites
• Include indicators relevant to critical data and to critical operational processes
Risk Indicators
• The level, point, or value associated with a Risk Indicator that will trigger an action
• Thresholds are set in order to clearly understand when the information from our Risk Indicators is inconsistent with the data we expect.
Thresholds
Thoughts on Implementation
Implement process and technology simultaneously
Work with entire study team to define risk indicators clearly
Clearly define actions to be taken if an indicator “fires”
Need training on root cause analysis and change management
Final thoughts
CROSS FUNCTIONALTEAM WORK IS KEY!
Building Quality by Design into design & planning of trial
Conducting early and ongoing risk assessments
Focusing on Critical Processes and Data
Using Risk Indicators, Thresholds & Action Plans
Adjusting monitoring activities based on risksRISK ASSESSMENT
CATEGORIZATIONTOOL
CRITICALVARIABLES
MONITORINGPLANS
Focus on what matters
Employ best mechanisms to monitor the remaining risks
Centralized Monitoring can: Ensure routine review of data in near
real time. Monitor data quality and critical data
reporting. Facilitate proactive and early
identification of quality, safety and operational risks
Identify unusual patterns in data earlier
Employ analytics to target on-site/off-site monitoring activities on areas of greatest need.
Track site performance metrics Identify higher risk sites to target
additional monitoring.
Final thoughts
Senior Product ManagerVault Clinical Operations
Tom Dekker
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Table of Contents
Process1Functional Capabilities2Unified View3Unified Technologies4Data Warehouse & Lake5Predictive Analytics6
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Process
Plan
ReviewReport
Act
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Capabilities
Report
PlanAct
• Define Roles• Capture Risk Assessment• Route with Workflow • Library of Risks• Leverage Learnings
Review
• Scheduling (monthly,quarterly)• Alerting / Notification• Unified View• Mediation Activities
Act
• Issue Management• Task Lifecyle• Workflow• Monitoring Plan
Report
• Dashboards• TMF• Inspection• Audit Trail
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Medical Review
Patient Safety
Site Monitoring Data
Management
Centralized Monitoring Holistic ApproachUnified View
• Previously siloed clinical data systems
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Medical Review
RIs, Alerts, Analytics
Patient Safety
Site Monitoring
Data Management
Unified View
• Previously siloed clinical data systems
• Technology breaks down these silos
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Unified View
• Previously siloed clinical data systems
• Technology breaks down these silos
• Unified view across the clinical trial
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Name Description Source
Subject Recruitment Enrollment, Screen Failure Rates, Discontinuation
IVR, EDC
Data Quality CRF Completion, Query Counts & Aging
CDMS/EDC
Safety AE & SAEs Counts Safety, EDC
Protocol Deviations Deviation Counts, Severity CTMS, EDC
Workload Overdue Visit & Trip Reports, Outstanding SDV
CTMS, EDC
IP Accountability Inventory Discrepancies IXR, Clinical Supply
Data SourcesRisk Indicators (RIs)
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• Unified− One system. Single database − Leveraging same instance of a records (study, site records)
• Connected− Separate applications, or databases − Connected by vendors− No customer configuration required
• Integrated− Application Programming Interfaces (APIs)− Batch, file based − Extract Transform & Load (ETL)
• Manual− Upload by user of formatted data− Excel, CSV
Unifying Technology
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• Data Warehouse (DW, EDW)− Repositories of integrated data from one or more disparate sources.− Used for analytical reporting across enterprise − Current and historical data− Sourced from operational systems− Extract Transform & Load (ETL)− Cleansing process− Highly structured schema designed for reporting− Valuable Data
Data Warehouse
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• Data Warehouse (DW, EDW)− Repositories of data from disparate sources.− Used for analytical reporting and predictive modeling− All data types
• Standard +, Sensor Data, Images, Documents, Web Logs
− All current and historical data− Unstructured Data, No transformation. − No Cleansing − All Data (may not be useful)
Data Lake
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Predictive analytics: includes techniques that analyze historical data to make predictions about future events.
• Anticipate Risk− Anticipate risk in the future based on historical data
• Identify sites with likely protocol non-compliance • Subject with likelihood of AEs
− Take actions ahead of problems
• Mediation Modeling− Model actions & results for impact
• Monitoring Visits• Training• SDV
− Optimize site visit activities
Predictive Analytics / AI
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Leveraging modern technology to proactively identifies emerging risk and take action to improve data quality and speed trial execution.
Central Monitoring
Question & Answers
Alec VardySenior Director, Data Management
Jazz Pharmaceuticals
Tom DekkerSenior Product Manager
Veeva Systems
Thank You