medidata amug meeting / presentation 2013

Download Medidata AMUG Meeting / Presentation 2013

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The slide deck from my presentation from March 2013

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  • 1. Having your Cake and Ea1ng it Too Leveraging RWS with Phase 1 Studies Brock Heinz Spaulding Clinical March 19, 2013
  • 2. About me and Spaulding Clinical Research Brock Heinz - Engineering / Innovation; successfully demoted; introduced to Medidata in 2009; Technology Partner Established in 2007 with a team of experts from pharmaceutical, CRO, clinical practice, and the medical device industries with over 150 years of combined experience; Located in West Bend, WI 30 miles north of Milwaukee Highly integrated and automated phase I clinical pharmacology research unit; 155 beds 96 telemetry Data Management, Biostatistics and Medical Writing Services Full Service Core ECG Lab Medical Device Manufacturer 2
  • 3. Phase 1 trials at Spaulding Clinical EDC true to the acronym: truly using electronic means for data capture; not just electronic storage Barcode-driven data collection right subject each time Integration of ECG, vitals, labs Rapid data lock is the rule, not the exception Data cleaning is a dirty term Sponsors always have real time access to study data Basic philosophy Ive helped instill let computers do what computers are good at, thus maximizing the human touch Computers consistently do the right thing at the right time Humans work well with humans keep the peace with subjects Reducing variability is good science 3
  • 4. Phase 1 Trial at a Glance 4
  • 5. Whats the Cake? The cake in this context is a paperless and and automated Phase 1 study seamlessly integrated with the sponsors EDC system of choice Rave Whos Cake is it? Sponsors who have a desire to maintain study data throughout the lifecycle of a compound in Rave 5
  • 6. How can one have their cake and eat it too? Introducing SCi Rave (pronounced sky) The customer is always right. Sponsors understand their data structures and their processes, data standards come from the top down. Modular system consists of three major components Rave where are we going? ETL how / what should we pack? Interface Engine how do we get there? Process Overview Upload / parse loader file Develop / validate ETL Schedule and execute transfers 6
  • 7. Loader file driven design begin with end in mind 7
  • 8. Data model driven by Architect Loader
  • 9. ETL packing for the trip Extract, Transform, Load Incredibly flexible model layer of indirection can obtain data from other EDC systems, relational databases, flat files, etc Two primary tasks: Identify subjects Query study repository(ies?) and populate tables created by loader parsing process Script is uploaded through our web interface and is compiled and executed on the server Validate ETL script! Pre-transferred data can be reviewed in Excel / CSV 9
  • 10. Lets go! Scheduling and executing the transfer Transfer schedule is flexible can be dictated by sponsor Designate transfer schedule Automatic and near real-time Ad hoc Transfer schedule set from web interface Subjects inserted, form (Item Group) data sent Each transaction response from RWS is stored with the Item Group for which it was sent; available for review in web dashboard 10
  • 11. SCi Rave system architecture 11
  • 12. Configuring system 12
  • 13. Validating ETL; ad hoc interaction 13
  • 14. RWS transactions 14
  • 15. Memories of a recent trip 3 studies conducted in rapid succession 3,926 Folders 18,803 Forms 54,039 Item Groups (includes log lines) 322,685 Items 1,460,485 characters of time-point data 78,796 HTTPS Requests to RWS 0 CRFs manually transcribed from the Spaulding Clinical system into Rave 15
  • 16. Final thoughts Ive been around web services for a while this is well done: ODM, interoperable protocols, intuitive response messages, documentation, user group, etc. As leaders in EDC Medidata is refreshingly different than EMR vendors. Whats next? I think well seen see an evolution of drug development process. There will be disruption as there is a push towards personalized medicine. Tighter iterations, richer data. Big Data sensors; distributed telemetry; integrated data repositories. Mobile integration. Empower innovators RWS gives us the highway needed. Device level integration - today 16
  • 17. Spaulding webECGTM Hand-held diagnostic electrocardiograph uploads data to web-based ECG Management System Biometric voice ID eliminates demographic entry errors Single button allows for malleable user interface Stores up to 5 minutes of 12-lead ECG data Automated report available immediately Nearly instant over-reading Model 1000iQ Electrocardiograph
  • 18. Integrated data collection 18
  • 19. ECG document demographics via RWS 19
  • 20. Automatic transcription 20
  • 21. 21 Thank you!