beyond automation: extracting actionable intelligence from clinical trials
DESCRIPTION
To meet the challenge we must break down organizational and procedural silos by: - Leveraging new technologies and work methods - Map out, re-engineer, automate and integrate processes - Leverage and establish procedural and data standards - Integrate computerized systems and data sources - Identify clear and measurable metrics and KPIs - Align and integrate the quality system with automated processesTRANSCRIPT
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Beyond Automation:Extracting Actionable Intelligence from Clinical Trials
Tevin Pathareddy
Fred Landry
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<<Section Divider>>
<<Subtitle>>
Introduction
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How we work today
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Information and procedural silos• In today’s GxP landscape we have:
– Many individuals, groups and organizations working independently
– Many computerized systems working independently– Many different department or organization specific
processes• All generate data and information which for the most
part remains dislocated and underexploited • This makes our working environment inefficient and
costly
Lack of operational knowledge
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• In a silo based model, it is difficult to gain cross system, cross functional knowledge
• We spend a lot of time transcribing, reconciling and collating data
• Often we do not have a clear picture of study progress at any one point in time, even less across programs of studies
• We do not fully exploit operational data (generated from automated system processes) and transform it into knowledge
The Challenge
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• In today’s R&D environment, our challenge is to:– Make better drug development decisions– Accelerate time to market– Increase organizational efficiencies and agility– Improve understanding and management of R&D
processes– Reduce cost– Reduce risk– Improve quality– Improve compliance
Meeting the Challenge..
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• To meet the challenge we must break down organizational and procedural silos by:– Leveraging new technologies and work methods– Map out, re-engineer, automate and integrate processes– Leverage and establish procedural and data standards– Integrate computerized systems and data sources– Identify clear and measurable metrics and KPIs– Align and integrate the quality system with automated
processes
BPM and BI can help!
Definition of BPM
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• Business process management (BPM) is a management approach focused on aligning all aspects of an organization
• It is a holistic management approach that promotes business effectiveness and efficiency while striving for innovation, flexibility, and integration with technology
• Is based on continuous improvement of processesSource: Wikipedia
BPM technology elements
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Definition of Business Intelligence
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In 1958 Hans Peter Luhn, a computer scientist at IBM used the term business intelligence for the first time. He defined intelligence as: "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."
Definition of BI
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• BI refers to skills, processes, technologies, applications and practices used to support decision making
• BI technologies provide historical, current, and predictive views of business operations
• BI is composed on reports, dashboards, metrics and analytical models
• BI is capable of transforming operational and business data into information and knowledge
BI Implementation
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Top Critical Success Factors are:• Business driven methodology & project management• Clear vision & planning• Committed management support & sponsorship• Data management & quality issues• Mapping the solutions to the user requirements• Performance considerations of the BI system• Robust & extensible framework
Mapping out processes – High level to detailed
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• We typically think of clinical trial organization as hierarchical
• Processes usually align to a particular level of hierarchy
• Processes can be high level and then drill down
Process Maps
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Identifying milestones and KPI
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• Milestones are predefined events within a process or processes
• Milestones are calculated or non-calculated values based on one or many datapoints
• Milestones correspond to predefined key events or values within the various levels of the process maps
• Examples of Milestones would be:– IND Submission (Molecule Level)– Protocol Approval (Study Level)– FPFV (Site Level)
Identifying milestones and KPIs with process maps
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• KPIs are key operational indicators which are measured using information from processes, data, documents
• KPIs are calculated or non-calculated values based on one or many datapoints
• KPIs can be drilled in to see underlying KPIs and data or rolled-up to see higher level KPIs (they are hierarchal)
• Examples of KPIs would be:– Time between FPFV and DB Lock (study level)– Time between last query and DB lock (study level)– Time to query resolution (study, site level)– Number of queries by status (study / site) – Average protocol IRB approval time (site)
Identifying milestones and KPIs with process maps
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Identify data sources and integration points
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• Data sources for KPIs and Milestones can come from:– Documents and document metadata– Procedures and procedural data (workflows)– Databases (EDC, CTMS, Safety etc.)– Project plans and manual metrics
• When thinking about data for KPIs and Milestones, it is important to identify unique data sources
• Establishment and use of standards is key to be able to integrate data sources and procedures
Integrating Processes through BPM
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Building an operational knowledge model
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Dashboards – roll-up, drill-down, drill-in
• By identifying key metrics, milestones and indicators at all levels we are able to develop multi-dimensional dashboards
• These dashboards allow up to move up and down in our operational knowledge
• By adding a third dimension we are able to drill in both in terms of data but also time
• This model enables us to pin point key factors which have positive/negative impacts on our operations
Aligning with the QMS
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• Implementing this approach often requires changes to components of the QMS
• When re-engineering processes break them down into clear steps, tasks, responsabilities and deliverable elements
• Clearly identify all interconnections on process maps• Re-engineer manual processes into automated processes• Finally align these elements to your BPM and
collaborative environment
Recommended approach
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1. Map out R&D process maps; remember high to low2. Identify processes (SOPs) and interactions for each level and
step3. Identify people and organizations who intervene in each
process and step4. Identify data sources5. Identify key metrics, milestones and KPIs6. Identify technology elements7. Define a scope for pilot project8. Implement and improve
The light is at the end of the tunnel
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Enterprise Architecture
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Enterprise
System Design Process
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SOPs
(MS SharePoint)
BPM• GAMP 5 (Issue Management, CAPA,
etc.)• ISO• ICH• CDISC• Object Management Group (
www.omg.com)
BI• Metrics Champion (
www.metricschampion.org )
BPM/Standards and Resources
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BI Example Using Out of the Box SharePoint Tools
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Excel Services
KPIDashboard
Workflows FormsLists / Libraries
Source: Microsoft
Study Level Process Break Down (Site Management)
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Site Level Process Breakdown (Site Initiation)
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Site Level Sub-Process Breakdown (IMP Management)
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IMP Authorization Process Dependencies
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BI Example Using Out of the Box SharePoint Tools
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Excel Services
KPIDashboard
Workflows FormsLists / Libraries
Source: Microsoft
IMP Shipment Authorization Workflow
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Clinical Operations Document Library
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New IMP Shipment Authorization Request InfoPath Form
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From CTMS
From SharePoint Library
New IMP Shipment Authorization Request in Forms Library
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IMP Shipment Request Approved by Clinical Operations (Form)
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IMP Shipment Request Approved by Clinical Operations (Library)
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BI Example Using Out of the Box SharePoint Tools
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Excel Services
KPIDashboard
Workflows FormsLists / Libraries
Source: Microsoft