Real-World Evidence in Drug Development and Evaluation 1E

Table of Contents

1. Using Real-world Evidence to Transform Drug Development: Opportunities and Challenges
Harry Yang

Introduction
Traditional Drug Development Paradigm
Drug Development Progress
Limitations of Traditional Randomized Controlled Trials
Real World Data and Real World Evidence
Real World Data
Real World Evidence
Differences between RWE and Outcomes of RCT
Regulatory Perspective
Productivity Challenge
FDA Critical Path Initiative
Regulatory Perspectives Pertaining to RWE
Historical Approval Based on RWE
Access to RWD
Opportunities of RWE in Drug Development
Early Discovery
Clinical Study Design and Feasibility
Study Execution
Marketing Application
Product Launch
Product Lifecycle Management
Challenges with RWE
Data Access and Quality
Technological Barriers
Methodological Challenges
Lack of Data Talents
Regulatory Risks
Concluding Remarks

2. Evidence derived from real world data: utility, constraints and cautions
Deepak Khatry
 
What is RWD in the context of drug development and clinical practice
Why is RWD important?
For what purposes can RWD be useful?
What study designs and statistical methods will be necessary to ensure high quality RWE?
Some application examples

3. Real-world evidence from population-based cancer registry
Binbing Yu

Introduction
Statistical methods for population-based cancer registry
Application to small cell lung cancer survival
Discussions

4. External Control using RWE and Historical Data in Clinical Development
Qing Li, Guang Chen, Jianchang Lin, Andy Chi and Simon Davies

Introduction of using RWE and Historical Data in Clinical Development
Single Arm Trial Using External Control for Initial Indication
Comparison Across Trials with External Control for Label Expansion
Important Considerations When Designing Studies and Analyzing Data Using
External Control in Clinical Development

5. Bayesian method for assessing drug safety using real-world evidence
Binbing Yu

Introduction
Bayesian sensitivity analysis for unobserved confounders
Bayesian evidence synthesis using meta-analysis
Discussion

6. Real-World Evidence for Coverage and Payment Decisions
Saurabh Aggarwal*, Hui Huang*, Ozlem Topaloglu, Ross Selby

Introduction
Defining value
Contracting trend/value-based agreeement
Importance of RWE for demonstrating value
Use of RWE by payers and health technology assessment agencies

7: Causal Inference for Observational Studies/Real-World Data
Bo Lu

Causal Inference with Real-World Data
Propensity Score Adjustment for Observational Studies
Sensitivity Analysis for Hidden Bias
Case study: Propensity Score Matching Design and Sensitivity Analysis for Trauma Care Evaluation

8. Introduction to Artificial Intelligence and Deep Learning with a Case Study in Analyzing Electronic Health Records for Drug Development
Xiaomao Li and Qi Tang

Introduction to AI and overview of break-throughts of AI in drug development
A minimalist overview of deep learning methods
Introduction of the big data in clinical space: electronic health record
A case study of using deep learning to analyze HER
Introduction to Python and cloud computing