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Next Generation Digital Trials - Introduction to a changing landscape

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Data Analytics Perspective: Stijn Rogiers, SAS and explained why his company is prepared – having being around for decades as the “Rolls Royce” software provider in the fields of data science and analytics.

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Next Generation Digital Trials - Introduction to a changing landscape

  1. 1. Copyright © SAS Institute Inc. All rights reserved. 1 DayOne - Next generation Clinical Trials Stijn Rogiers, Principal Industry Consultant SAS Global Health and Life Sciences Practice June 25th 2019
  2. 2. Company Confidential – For Internal Use Only Copyright © SAS Institute Inc. All rights reserved. Twitter: @StijnRogiers LinkedIn: https://www.linkedin.com/in/stijnrogiers/ Email: stijn.rogiers@sas.com Introduction
  3. 3. Company Confidential – For Internal Use Only Copyright © SAS Institute Inc. All rights reserved. Real World Evidence “Maximize product value beyond efficacy and safety” Society Patient Provider Clinical Economic Payer/HTA Comparative effectiveness Cost-utility Budget Impact Long-term Outcomes Direct/Indirect Cost Cost:Outcomes Cost Consequences Resource Utilization QALY Equal access to healthcare Return to work Caregiver burden Productivity Morbidity, Mortality Symptoms Functionality Preferences Quality of Life Effectiveness Tolerability Safety Compliance Adherence ConvenienceEfficacy Safety Morbidity Mortality Case Study: Maximize Product Value with Real World Evidence, Maria Kubin, VP Bayer Healthcare –Eye for Pharma
  4. 4. Copyright © SAS Institute Inc. All rights reserved. Regulatory Perspective (US FDA) Framework for FDA's Real World Evidence Program (Dec 2018)
  5. 5. Company Confidential – For Internal Use Only Copyright © SAS Institute Inc. All rights reserved.
  6. 6. Company Confidential – For Internal Use Only Copyright © SAS Institute Inc. All rights reserved.
  7. 7. Company Confidential – For Internal Use Only Copyright © SAS Institute Inc. All rights reserved.
  8. 8. Company Confidential – For Internal Use Only Copyright © SAS Institute Inc. All rights reserved. PRO EMR CLAIMS LABS RX REGISTRY COA SAFETY MORTALITY DIGITAL mHEALTH SOCIAL MEDIA CONSUMER Patient Recruitment Trial Optimization Synthetic Control Arms BOI Drug Utilization PASS Pragmatic Trial Natural Hx Risk / Benefit Disease Mechanism Comorbidities Value Prop Patient Journey Economic Model Comparative Effectiveness Outcome Predictions Patient Journey Epidemiology Pharmacovigilance Regulatory Affairs R&D Medical Affairs HEOR Market Access HTA Commercial
  9. 9. Copyright © SAS Institute Inc. All rights reserved. Feasibility Analysis How can sponsors accurately measure the feasibility of a protocol and plan accordingly to achieve timely and cost-effective enrollment and the quality data to advance their pipelines?  True clinical trial feasibility includes strategic, scientific, operational, and patient recruitment considerations  Traditional approach in our industry  Historical Data / Past Experiences, Previous Studies (CRO, Pharma)  Discussions with potential sites and Patient Organizations  Educated guesses  Focus is on the enrollability of a clinical trial
  10. 10. Copyright © SAS Institute Inc. All rights reserved. Cohort Generation “What if scenario(s)” … What if we loosen exclusion criteria https://www.statnews.com/2018/04/05/clinical-trials-excluding-patients/ Running clinical trials effectively and efficiently is critical to medical progress, not just in cancer care but across disciplines. Allowing more patients to be enrolled in trials will speed the medical innovation process, allow more sick people to access potentially beneficial therapies, and produce more generalized results. Spurred by this month’s FDA meeting, lead researchers, sponsors, and regulators must rethink their approach to clinical trial eligibility (5 Apr 2018).
  11. 11. Copyright © SAS Institute Inc. All rights reserved. Add-ins Cohort Characterization Reports
  12. 12. Copyright © SAS Institute Inc. All rights reserved. Add-ins Use SAS (industry) / Develop company specifics
  13. 13. Copyright © SAS Institute Inc. All rights reserved. Clinical Trial Operational Analytics Enrollment Optimization: State / Site Selection State CA Fl IL MI NY
  14. 14. Copyright © SAS Institute Inc. All rights reserved. Clinical Trial Operational Analytics Enrollment Optimization: Stringent Vs. Relaxed Stringent Scenario Relaxed Scenario
  15. 15. Copyright © SAS Institute Inc. All rights reserved. Generate additional insights Data Mining & Machine Learning – Model Comparison
  16. 16. Copyright © SAS Institute Inc. All rights reserved. A Study showing real world use of ‘real world data’ http://theoncologist.alphamedpress.org/content/early/2018/12/27/theoncologist.2018- 0307.short?rss=1&related-urls=yes&legid=theoncologist;theoncologist.2018-0307v1 https://datavant.com/2019/01/14/a-study-showing-real-world-use-of-real-world-data/
  17. 17. Copyright © SAS Institute Inc. All rights reserved. AI and medicine
  18. 18. Copyright © SAS Institute Inc. All rights reserved. Results An in-depth scan has a lot of data and the outcomes can be improved with the use of advanced analytics on patients’ health data and history. “ ”Prof. Dr. Geert Kazemier Cancer Center Amsterdam, aUMC
  19. 19. Automatic Segmentation
  20. 20. Copyright © SAS Institute Inc. All rights reserved. Precision medicineAI and medicine Kim et al., Nature Biotechnology, 37, 389-406 (2019)
  21. 21. Copyright © SAS Institute Inc. All rights reserved. ASSIST’s Always-on Wearable Platforms Long Term Monitoring of health and environment Correlation of multiple sensors signals Clinical studies in various health domains • Self-powered • Physiological, biochemical and environmental sensors • Wearable, wireless and comfortable • Informative and continuous data 25
  22. 22. Copyright © SAS Institute Inc. All rights reserved. Pricing and cost Ethical rulesAI/ML regulation Data TransparencyPersonal data protection
  23. 23. Copyright © SAS Institute Inc. All rights reserved. AI IN Health Care and Life Sciences OPERATIONAL EFFICIENCY CLINICAL SCIENCE  Reducing physician burnout  Meaningfully connect different data sources  Financial impact, cost, fraud and abuse  Workflow optimization (simulation, DL)  Clinical trial operations  Manufacturing quality REGULATION AND GOVERNANCE Efficiency increase of health care and clinical development Faster access to care and support for physician Risk, governance, auditability  Deep learning for computer vision and biological signals  IoMT : wearables, devices and modern clinical trials  Patient engagement : chatbots  RWE – cohort analysis – matching patients,  Ethical AI  Enterprise implementation and repeatability  Data privacy  Traceability

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