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From Here to EDC: A Dramatic Love Story

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CONFIDENTIAL All rights reserved

Introductions  Christine Warrington  Head of Global Sales and Marketing  Cato Research Ltd.  Daniel Cato, M.B.A  Vice President Operations  Cato Research Ltd.  Christine Lys, M.S.  Director, Business Development  Merge Healthcare Incorporated

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Electronic Data Capture  An Electronic Data Capture (EDC) system is a computerized system designed for the collection of clinical data in electronic format.  EDC not specific to Clinical Research  Systems have been around for decades

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History of Cato & Merge EDC Collaboration  Cato was the first CRO to partner with Merge on EDC  Duration of our relationship >15 years  Exposed to evolving technology  Used EDC in Phase I-III

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EDC: One of the greatest inventions for Clinical Research in the 20th century

Reduce, Reuse, Recycle!

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“Reduce" from EDC  Paper, saves trees  Storage Space  

Less than paper form Consequential costs of saving space:  Lower rent  Lower heating/cooling costs  Lighter environmental footprint

 Access Time  

Avoids shipment, collection of paper  Reduces greenhouse gases Easily accessible with Internet

 Eliminate Paper-based Processes  Inefficiencies 

The examination of processes/workflow in preparation for EDC results in reduction of inefficiencies

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“Reuse" from EDC  Systems & Processes  An EDC can be extended to other projects  Human Effort  For something more productive  Do more with less  Learning  Automating a process can perpetuate enhancements to related processes

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“Recycle" from EDC  Information  The information stored in electronic forms can often be reused in different forms without having to duplicate on paper and ship to its destination.  Capture other forms of data

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Benefits to Clinical Trials  Enables an organization to be more responsive, agile  Reduce cost and time in key processes  Increase data accuracy  Increase data integrity  Increase speed of access to data  Increase transparency to these data to key stakeholders

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EDC vs. Paper Process

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Roles impacted by EDC  Investigative Site  Compliance & Enrollment tracked automatically, enhancing grant administration  Minimizes paper processes  Enhanced focus on data quality due to automated queries instead of phone calls, numerous visitors and sticky notes  Monitor 

Focus on critical variables. Gives other privileged users access to query remotely and directly

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Reduces number and duration of onsite visits (on average 35%)

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Roles impacted by EDC  Data Manager  Double data entry is eliminated  DCF process is handled online in real time  CRFs are automatically tracked and filed  Workload shifts from a post-study peak to a steady flow throughout the study  Volume and frequency of interactions with site staff are greatly increased  Involvement begins much earlier in the study cycle to design eCRFs and database must be built before the study launches  Shift from a focus on collecting and cleaning the data to reporting of data  Quicker data-lock

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Roles impacted by EDC  Project Manager  Better data access in near real time allows managers to focus on more strategic issues rather than minor details  Reporting can be automated  Can attend to study-wide and site-specific issues immediately  Can detect need for protocol changes earlier

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Improves ability to manage site compliance and to link grant payments to milestones

 Statistician  Analysis and reporting become ongoing events rather than poststudy events  Will be working with more relevant (cleaner) data for interim analysis and reports

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“Ability has

nothing to do with opportunity.” Napoleon Bonaparte

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EDC Adoption Has Been Slow

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Canadian Study finds 41% use EDC The Use of Electronic Data Capture Tools in Clinical Trials:Web-Survey of 259 Canadian Trials Khaled El Emam1,2, BEng, PhD; Elizabeth Jonker1, BA; Margaret Sampson1, MLIS; Karmela Krleža-Jerić3, MD, MSc, DSc; Angelica Neisa1, BSc 1Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada J Med Internet Res 2009;11(1):e8 Background: Electronic data capture (EDC) tools provide automated support for data collection, reporting, query resolution, randomization, and validation, among other features, for clinical trials. There is a trend toward greater adoption of EDC tools in clinical trials, but there is also uncertainty about how many trials are actually using this technology in practice. A systematic review of EDC adoption surveys conducted up to 2007 concluded that only 20% of trials are using EDC systems, but previous surveys had weaknesses. Objectives: Our primary objective was to estimate the proportion of phase II/III/IV Canadian clinical trials that used an EDC system in 2006 and 2007. The secondary objectives were to investigate the factors that can have an impact on adoption and to develop a scale to assess the extent of sophistication of EDC systems. Methods: We conducted a Web survey to estimate the proportion of trials that were using an EDC system. The survey was sent to the Canadian site coordinators for 331 trials. We also developed and validated a scale using Guttman scaling to assess the extent of sophistication of EDC systems. Trials using EDC were compared by the level of sophistication of their systems. Results: We had a 78.2% response rate (259/331) for the survey. It is estimated that 41% (95% CI 37.5%-44%) of clinical trials were using an EDC system. Trials funded by academic institutions, government, and foundations were less likely to use an EDC system compared to those sponsored by industry. Also, larger trials tended to be more likely to adopt EDC. The EDC sophistication scale had six levels and a coefficient of reproducibility of 0.901 (P< .001) and a coefficient of scalability of 0.79. There was no difference in sophistication based on the funding source, but pediatric trials were likely to use a more sophisticated EDC system. Conclusion: The adoption of EDC systems in clinical trials in Canada is higher than the literature indicated: a large proportion of clinical trials in Canada use some form of automated data capture system. To inform future adoption, research should gather stronger evidence on the costs and benefits of using different EDC systems.

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Reasons for Slow Adoption of EDC  Conservative Industry  Perceived Risk- Time to create ROI  Lack of technical knowledge  Assumptions about training  Lack of process change management  electrified paper  integration  Job retention  Once bitten, twice shy  Choosing technology vendor vs. technology service provider

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“Maybe back in the days of the pioneers a man could go his own way, but today you got to play ball.” Sgt Milton Warden, From Here to Eternity

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Rising Costs of Drug Development  The most recent cost estimate of drug development is now $1 billion.1  Need to make Go/No-Go Decisions Quickly  Speed to market  Investment concerns

Cost 1,000,000,000

900,000,000

800,000,000

700,000,000

600,000,000

500,000,000

Dimasi 2003

1Adams

CP, Brantner VV (2010) “Spending on New Drug Development” Health Econ. 19: 130–141 (2010)

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Adams & Brantner 2010


Where myEDC comes in  Cost effective  Easy to learn  Easy to use  Repurpose jobs

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“A man should be what he can do.”  myEDC gives those with clinical research knowledge and an understanding of data management the ability to build their study without programming skills

Robert E. Lee Prewitt ("Prew"), From Here to Eternity

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When to use myEDC vs. EDC  Cost/Time constraints  Use myEDC

 Complex Integration  Complex, dynamic logic  Allocation of resources  Use EDC  Or consider using Service Provider like Cato who can implement myEDC

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Cato’s Experience     

Time to learn how to develop a myEDC Protocol Functionality Edit Checks Price Overall Experience

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Time to learn how to develop a myEDC Protocol  Merge has extensive tutorials and online help.  Setting up pages and visits was easy to learn.  Online help  myEDC has an extensive library of template pages and a sample study

 Determining how we would like to set the customizable features is a much longer process  Data Flow  Setting up procedures for system access and providing the initial help desk  Training the project team

 Optimizing the process 36


Functionality  Limited page flexibility  Two rows of question and response  Three levels of indent  Quickly add items to a page  Partial Dates are 3 lines  Only able to change one row at a time once items are added.  Merge collects enhancement suggestions.

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Edit Checks  Edit checks can only be created through the wizard.  Wizard easily creates univariate and multivariate checks.

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Price  Pay as you go – not a large up front payment  Competitive to paper for long term studies and small studies  Price covers hosting and software fee.  The developer is responsible for maintaining and supporting users with their own staff or through additional services through Merge.

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Overall Experience  The program is easy to learn  There will still be considerable amount of time to adapt the program to your own process  Project Teams like to see the pages and then make changes  Before building use an Excel sheet to approve the pages and questions (types and name)

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Case Study  Discuss Clients utilization of myEDC thus far  Press Release • Type of studies

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Future  Debating whether or not to discuss future directions of EDC methodologies with the increase in EMR, ePatients solutions, etc. or in the beginning

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