1. Use of Real-World Data in Clinical Drug Development
Julie Cong, Susan Wang
Boehringer Ingelheim, China
JSM 2018

2. Real-world data (RWD) and Evidence (RWE)
- FDA Voice blog by Dr. Scott Gottlieb on July 2018

3. Regulatory use of RWD/RWE
Post-approval benefits and risks monitoring through the FDA’s Sentinel System and the National Evaluation System for health Technology (NEST)
Label expansion
New $100M medical data enterprise proposal to build a modern system relying on Electronic Health Records (EHR).
Innovative statistical methods needed e.g. Bayesian and propensity score methods
- FDA Voice blog by Dr. Scott Gottlieb on July 2018

4. Outline
Overview of how real-world data can be used to optimize clinical drug development
Hypothesis generation
Patient availability
Site feasibility
Potentially minimize control arm
Tools/technologies needed
Summary and take-home message

5. Generate a more feasible and clinical relevant hypothesis
Treatment effect size
Historical trials, publications
RWE can rapidly explore and test hypotheses across diverse datasets.
Indication and severity of disease of interest
Outcomes
Unmet needs
Treatment journey

6. RWE to optimize trial design
Information from RWE regarding
Real-world treatment length and adherence data
Patient retention in RCT
Frequency of visits, trial procedures to minimize trial burden
Reduce protocol amendment and interaction with IRB

7. Patient availability and feasibility
Assess feasibility based on inclusion and exclusion criteria against available RWD when writing trial protocol
Availability of target patients in candidate sites
Look for potential sites with more patients

8. Example of locating target patients by geographical data (Fish where the fish are)
Picture taken from Bill Gwinn 2015 DIA

9. Evidence-driven site feasibility
Non-recruiting sites contribute to big financial loss
Traditional site survey administration is deemed inefficient. Lasagna’s Law
RWE assess
patient engagement
investigator skill sets
PRO data

10. Evidence-driven site feasibility
Picture taken from Bill Gwinn 2015 DIA

11. Example on how site selection influences trial conduct
Table taken from Johnson 2015

12. Synthetic Control Arm (SCA)
RWE serves as a control arm (synthetic control arm, SCA)
When placebo is unethical, active comparator is not available, adherence to placebo arm is problematic
Terminal illness, rare disease

13. Synthetic Control Arm (SCA)
Conventionally, SCA was built on historical or previous trial information.
SCA based on previous trials have the biases of those trials, can be reduced by considering multiple trials, e.g. Berry et al 2017, Medidata archival with >3000 trials

14. Example Berry et al 2017
Matched 340 patients from 7 Medidata archived trials, not real-world data
Particular phase I/II trial
This also helps develop early endpoints as predictor of long-term survival in AML patients.

15. Synthetic Control Arm (SCA)
With RWE, real-world practices; potentially large SCA
Challenges using RWD to create SCA:
Real-world data unorganized
not collected in a controlled environment
Methods to be considered
Propensity score matching to match demographics, baseline characteristics, treatment patterns etc.

16. Statisticians be well prepared for RWE
Innovative statistical methods needed
Big data
Bayesian framework
Propensity score methods
Machine learning technologies
Neural networks
Text mining

17. Checklist for Regulatory – Grade RWE
High quality
Complete
Transparent
Generalizable
Timely
Scalable
--- RA Miksad and AP Abernethy. 2018

18. Take-home message
Appropriate use of RWE can help expedite drug development
Limitation still exists
RWE with better quality needed
Regulatory agencies provide clarity guidelines on using RWE for drug approval
Call for statisticians on innovative statistical methods to ensure RWD quality and broader usage of RWE in drug development

19. References
DA Berry et al Journal of Clinical Oncology 35, no. 15_suppl (May )
R Ahmed et al. Whitepaper on “Using Real-world evidence to otimize clinical trials” Shyft Analytics
Bill Gwinn 2015 DIA ‘Data-Driven Study Feasibility Assessment and Impact on Successful Execution of Clinical Trial Protocols
Otis Johnson 2015 Clin. Invest. (Lond.) “An evidence-based approach to conducting clinical trial feasibility assessments”.
RA Miksad and AP Abernethy “Harnessing the Power of Real-World Evidence (RWE): A Checklist t Ensure Regulatory-Grade Data Quality”

20. RWE
What questions do you have for me?