PICI’s Best Practices for Building Oncology Studies in an EDC
Watch the video here: https://bit.ly/3vrYslR The Parker Institute for Cancer Immunotherapy (PICI) runs complex clinical trials that depend on an electronic data capture (EDC) system that is adaptive, flexible and innovating at the same pace as their patient-centric mission. Learn why their legacy EDC system workarounds and custom functions no longer sustained their business, which motivated them to take a new approach. In this webinar, Toby Odenheim, the Director of Technology and Governance, will share how PICI decided to adopt a new EDC system that streamlines the build process for oncology trials and how they better equip their clinical programmers and data managers. PICI’s lead study builder, Gary Smith, will provide a hands-on perspective and share strategies to handle the key challenges that oncology teams face with EDC systems, including: * Umbrella trials that evaluate multiple therapies * Adaptive trial branching and routing * Having an unknown number of treatment cycles * Amendments and other unplanned changes Who Will Benefit: * Data managers * Database Programmers * Clinical Programmers * Clinical programmers in charge of building studies * Clinical leaders in charge of selecting EDC systems * EDC Programmers Meet Your Presenters: Toby Odenheim Director, Technology and Governance, Parker Institute for Cancer Immunotherapy In his current role as director of technology and governance at PICI, Toby Odenheim, MBA, leads an array of technology and process improvement initiatives aimed at accelerating the development of innovative cancer immunotherapy treatments. Core areas of oversight include management of clinical and pharmacovigilance systems, including CTMS, eTMF, IRT, EDC, ePRO, medical coding, safety, and business intelligence systems. Prior to joining PICI, Odenheim was the founder and principal at Odin Life Sciences Consulting, where he guided companies in the selection, implementation, and validation of best-of-breed clinical technologies. Toby Odenheim has held management positions at Gilead, Synteract, ClinicalSoft, and Pfizer. He holds an undergraduate degree in biology, an MBA, and professional certifications in finance, Oracle database administration, and relational database design. Gary Smith Senior EDC Programmer/Analyst, Parker Institute for Cancer Immunotherapy Gary has over twenty years of experience in clinical programming and is a subject matter expert on study design, configuration, and testing with off-the-shelf EDC systems including Veeva Vault CDMS, Medidata Rave, and Oracle Clinical. Gary has deep expertise in building oncology studies, specifically platform studies, and is currently responsible for all aspects of EDC design and study builds in immuno-oncology studies with the Parker Institute for Cancer Immunotherapy. Gary has developed global libraries for five different companies, spanning medical device and pharmaceutical industries.
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PICI’s Best Practices for Building Oncology Studies in an EDC
- 1. 1 Best Practices for Building Oncology Studies in Vault EDC Toby Odenheim | Director, Technology and Governance Gary Smith | Senior EDC Programmer & Analyst
- 2. 2 Mission To accelerate the development of breakthrough immune therapies to turn all cancers into curable diseases. PICI’s
- 3. 3 Science first Collaboration Bold ideas & action Relentless commitment Patient - Centric Our Philosophy
- 4. 4 FOUNDING RESEARCH INSTITUTIONS How We Started How We’ve Grown ADDITIONAL AFFILIATED INSTITUTIONS
- 5. 5 What is an adaptive platform clinical trial? A clinical trial design that allows for • Prospectively planned modifications to one or more aspects of the study based on accumulating subject data • Multiple interventions entering and leaving the platform according to predefined criteria Adapt Periodic Review Conduct Design Analyse
- 6. 6 What is an adaptive platform clinical trial? What is NOT considered adaptive? • Unplanned changes based on interim results • Protocol amendments based on info from sources external to study A clinical trial design that allows for • Prospectively planned modifications to one or more aspects of the study based on accumulating subject data • Multiple interventions entering and leaving the platform according to predefined criteria
- 7. 7 More efficient Fewer patients randomized to less promising treatment Monitored closely Adaptable to open/close Set up efficiencies 20-50% reduction in costs Lower costs if fewer discrete trials needed Advantages of adaptive platform trials Combo 1 Combo 2 Combo 3 Combo 4 TIME: Trail Start
- 8. 8 PICI Prostate Platform Study Schema
- 9. 9 Challenges with a Traditional EDC • Integration Challenges - Not a true platform, collection of disparate systems • Continual challenges with coding module • RTSM not robust enough for platform trials • Downtime to migrate over post-production study changes • Limited feature enhancements • Complexity of supporting platform trials amplified above challenges New generation of legacy system had old problems and new
- 10. 10 Selecting a Fit-for-Purpose EDC Platform Strategy Investment and experience with other Vault suites, including Vault QualityDocs, eTMF & Safety Modern EDC Nice UI Intuitive study build tools Unified coding Cloud Pace of Innovation Rapidly filling gaps and adding innovations Reliable upgrade schedule
- 11. 11 In-house expertise helps us guide our sites and improve processes Faster and more cost effective to build internally The frequent modifications required for adaptive platform studies make outsourcing a challenge Getting Trained to Build our own Studies Different Systems Require Different Approaches Applying processes and techniques from legacy system reduces efficiency gains of a modern system
- 12. 12 What Makes Platform Trials Complex to Program? Multiple treatment groups Multiple treatment cycles, unknown number Multiple amendments expected Complex visit map Cohort / treatment changes mid-study (added and dropped) Frequent need for complex edit checks Forms differ by treatment, even some common forms
- 13. 13 Keys to Making Adaptive Platform Trials Easier to Build Study design building blocks Ease in configuring and deploying changes Repeating design elements with configurable labels Powerful rules and dynamics – build once, show as needed
- 14. 14 Configuring the Building Blocks
- 15. 15 Study Design Building Blocks Item Groups Items Forms Events Event Groups Forms Visits Treatment Cycles Fields Groupings of Fields
- 16. 16 Dynamically Adding Forms to a Visit
- 17. 17 Dynamically Adding Forms to a Visit Simple rule: “If cycle sequence number is 1…” …then add these forms
- 18. 18 Dynamically Adding Forms to a Visit Custom label, dynamically applied Forms added dynamically Standard form in all visits, no rule
- 19. 19 An organizing structure that groups one or more visits, and is reusable throughout the study Cycle Visit Visit Visit CRF CRF CRF CRF CRF CRF CRF CRF CRF Event Group (Cycle)
- 20. 20 Dynamic Event Group (Cycle / Days) Visits, forms, and fields are surfaced when and where appropriate, based on assigned parameters Cycle Visit Visit Visit CRF CRF CRF CRF CRF CRF CRF CRF CRF Route of Administration Dosing Schedule
- 21. 21 Cycle Visit Visit Visit CRF CRF CRF CRF CRF CRF CRF CRF CRF Dynamic Event Group (Cycle / Days) Route of Administration Dosing Schedule Visits, forms, and fields are surfaced when and where appropriate based on assigned parameters
- 22. 22 Weekly Weekly Bi-Weekly Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (IV) Blood Sample (SC) Drug Administration (IV) Drug Administration (SC) ICF Screening Cycle X D1 D8 D15 1-5 1-5 1-5 DYNAMIC CYCLE & VISITS Bi-Weekly Create one treatment cycle event group containing the superset of visits and forms for all pathways and cycles 1. Reuse event group for each new treatment cycle 2. Create rules specifying which visits and forms to surface when 3.
- 23. 23 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (SC) Drug Administration (SC) ICF Screening Cycle 1 D1 D8 D15 1-5 1-5 1-5 WEEKLY SUBCUTANEOUS Cycle 2 D1 D8 D15 1-5 1-5 1-5 Cycle3 D1 D8 D15 1-5 1-5 1-5 All Other Cycles D1 D8 D15 1-5 1-5 1-5 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (IV) Blood Sample (SC) Drug Administration (IV) Drug Administration (SC) ICF Screening Cycle X D1 D8 D15 1-5 1-5 1-5 DYNAMIC CYCLE & VISITS Weekly Weekly Bi-Weekly Bi-Weekly
- 24. 24 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (SC) Drug Administration (SC) ICF Screening Cycle 1 D1 D15 1-5 1-5 BI-WEEKLY SUBCUTANEOUS Cycle 2 D1 D15 1-5 1-5 Cycle3 D1 D15 1-5 1-5 All Other Cycles D1 D15 1-5 1-5 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (IV) Blood Sample (SC) Drug Administration (IV) Drug Administration (SC) ICF Screening Cycle X D1 D8 D15 1-5 1-5 1-5 DYNAMIC CYCLE & VISITS Weekly Weekly Bi-Weekly Bi-Weekly
- 25. 25 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (IV) Drug Administration (IV) ICF Screening Cycle 1 D1 D8 D15 1-5 1-5 1-5 WEEKLY INTRAVENOUS Cycle 2 D1 D8 D15 1-5 1-5 1-5 Cycle3 D1 D8 D15 1-5 1-5 1-5 All Other Cycles D1 D8 D15 1-5 1-5 1-5 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (IV) Blood Sample (SC) Drug Administration (IV) Drug Administration (SC) ICF Screening Cycle X D1 D8 D15 1-5 1-5 1-5 DYNAMIC CYCLE & VISITS Weekly Weekly Bi-Weekly Bi-Weekly
- 26. 26 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (IV) Drug Administration (IV) ICF 1-5 1-5 BI-WEEKLY INTRAVENOUS 1-5 1-5 1-5 1-5 1-5 1-5 Assessments Procedures Eligibility Demography Medical History Tumor Biopsy Vital Signs ECOG Blood Sample (IV) Blood Sample (SC) Drug Administration (IV) Drug Administration (SC) ICF Screening Cycle X D1 D8 D15 1-5 1-5 1-5 DYNAMIC CYCLE & VISITS Screening Cycle 1 D1 D15 Cycle 2 D1 D15 Cycle3 D1 D15 All Other Cycles D1 D15 Weekly Weekly Bi-Weekly Bi-Weekly
- 27. 27 Creating the Study Schedule
- 28. 28 Traditionally – Separate Schedule Matrix Needed Whenever Data Collection Requirements Differ In my last production study using an older system 292 matrices Difficult to manage with each matrix stored separately Limited visibility into rules associated with each matrix Difficult to QA during UAT Difficult to conceptualize overall schedule
- 29. 29 Visit Matrix: Legacy EDC Complex visit structure was difficult to model in prior EDC
- 30. 30 Partial look at the Visit Matrix from a Platform Study Maintained Separately in Excel
- 31. 31 • Single matrix for entire study Repeating event groups minimize cycles to display • Work directly from protocol to map schedule of events and related forms Schedule Editor in Vault EDC
- 32. 32 Specify which forms to associate with which visit Add, remove, modify, and reorder objects directly within the editor
- 33. 33 Easily see which groups, events, and forms are dynamic
- 34. 34 Gain visibility into rules controlling the dynamics
- 36. 36 Configure properties for treatment cycles, visits, or forms directly in the schedule editor
- 37. 37 Add new treatment cycles by updating the number of repeats
- 38. 38 Label each cycle and visit as appropriate
- 39. 39 Adding Treatment Cycles CONFIGURATION Example: If: “Next visit date” is populated, Then: Dynamically generate new visit and related forms OR If: “Start new treatment cycle?” is Yes, Then: Dynamically generate new treatment cycle with related visits and forms STUDY CONDUCT Trigger creation of new cycle or visit based on field entry or specific field value.
- 40. 40 Altering Treatment Paths Traditionally: Would need new forms, new folders, new visit matrices, and a significant number of dynamics to address changes in treatment paths. Significant QA needed to ensure dynamics work for every matrix. Lab Result Lab Result CD8 High CD8 Low Each arm has unique forms and specific fields on common forms (75 folders and matrices) (64 folders and matrices) With Veeva: Dynamics running at the event group level automatically impact nested events and forms. Predefined rules can route patients to different arms based on lab result criteria or trigger question
- 42. 42 Benefits During Build & Execution Simplifying Changes Adding new cycles Adding days to an existing cycle Adding additional forms to a visit Adding new arms Re-routing patients Nesting forms in a treatment cycle event group Using rules to surface forms at the right cycle, visit, and arm Writing rules and dynamics in the builder not in custom programming Speeding the Build
- 43. 43 Closing Advice Open Mind Be open to a new approach. Things need to be different to be faster Modern EDC Work with an EDC that provides suitable building blocks to model a modern trial Embrace Change Incorporate functionality of new releases to benefit from pace of innovations