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Pingyan Chen
Southern Medical University, China
2020-09-23
Key Considerations in Using Real-World
Evidence to Support Drug Development
Contents
• Development of Regulatory guidance and activities
• Guidance of RWE and RWD issued by NMPA
• Visions
2016
Sec. 3022. RWE in
21st Century Cures
Act
2017
Guidance of RWE
for medical devices
(FDA, final)
2018
RWE Framework
Program (FDA,
final)
Part 1
Milestones of RWE & RWD
3
2020
Guidance of RWE, final
(NMPA, 2020.01.07)
Guidance of RWD, draft
(NMPA, 2020.08.13)
2019
Submitting
Documents using
RWD and RWE to
FDA (FDA, draft)
2021
Deadline of
Guidance of RWE
for industry
Development of Regulatory Guidance and Activities
• FDA
• Guidance
• RCT Duplicate project, www.rctduplicate.org
• EMA
• GetReal Initiative
• Adaptive Licensing Pilot, 2014
• HMA/EMA Task Force on Big Data
• PMDA
• Guideline on pharmacoepidemiological study for drug safety assessment based on medical
information database, 2014
• Basic principles on the utilization of health information databases for post-marketing surveillance of
medical products, 2017
• ICH
• Pharmacoepidemiology Discussion Group (PEpiDG)
• NMPA
• Key Considerations in Using Real-World Evidence to Support Drug Development
(Draft), May 2019
➢Received 400+ comments from PhRMA, EFPIA, BIO, IFPMA, JPMA, ISPE, RDPAC,
some hospitals, pharma companies, data companies and individuals.
• Guideline on Using Real World Evidence to Support Drug Development and
Regulatory Decision-making (Implementation for trial), Jan 2020
• Guideline on Real World Data Used to Generate Real World Evidence (Draft), Aug
2020
• Guideline on Real World Study Used to Support Pediatric Drug Development and
Regulatory Decision-making (Final), Aug 2020
Contents
• Development of Regulatory guidance and activities
• Guidance of RWE and RWD issued by NMPA
• Definition
• RWD
• RWE application scenarios
• Design
• Common statistical methods
• Evaluation of RWE
• Communication with the regulatory agency
• Case study
• Visions
Definition of RWD/RWE/RWS
Real-World Data(RWD)
Real-world data (RWD) refer to a variety of data, collected on a daily basis, which
are related to the patient’s health status and/or diagnosis and healthcare processes.
Real-World Evidence (RWE)
Real-World Evidence (RWE) refers to the clinical evidence on the use and potential
benefit-risk of a drug, obtained through adequate and sufficient analysis of fit-for-
purpose RWD. RWE includes evidence from retrospective or prospective
observational studies, or interventional studies such as pragmatic clinical trials.
Real-World Study/Research (RWS/RWR)
A process of, based on preset clinical questions, collecting data related to the
health status and/or the diagnosis and treatment of research subjects in a real-
world setting (ie, the real-world data) or utilizing the summary derived from the
RWD, through analyses, to obtain clinical evidence of the drug usage and their
potential benefit-risk (ie, the real-world evidence).
8
RWEAnalysis
RWDData collection
Unfitted
RWD
Accepted
Unaccepted
Protocol Research objectives
Data curation and
fitness assessment
Natural population
Clinical population
RWE
Others RWE
Analysis
Fitted
RWD
Pathways for RWS to support drug regulatory decision making (red solid line)
9Fitness evaluation and data curation process of RWD for retrospective RWS
Research protocol TerminationNot applicable
Applicable
Data Curation of applicable RWD source data
Data security system, Data transfer and storage, QC system
Extraction form
single data source
Extraction form
Multi-data source
Data desensitization
Data extraction
Process duplicate data
Process abnormal data
Process missing data
Data Cleaning
CDM
NLP
Medical Terminology
and Coding
Data conversion
Derived variable
calculation
RWEFitted RWD
(Analysis dataset)
Analysis
RWD Source
Data
Preliminary applicability
evaluation of
RWD source data
FittedFitness evaluation of
data after curation
TerminationNot fitted
RWD Sources Patient Reported
Outcome Data
Personal Health
Surveillance Data
From Mobile
Devices
Medical
Insurance
Claim
Data
Death
Registry
Data
Active Drug Safety
Surveillance Data
Data For Other
Specific
Purpose
Registry Data
Natural Population
Cohort Data
Omics Data
Hospital Information system data
NMPA CDE-Guideline on Using Real-World Data to Generate Real-World Evidence (Draft for Public Review)
RWD Quality Evaluation
• Inclusion of important variables and information
related to clinical outcomes;
• Definition of clinical outcome is accurate and
the corresponding clinical meaning is clear
• Patients in the RWD are representative of the
target population of the study
• Sufficient sample size and follow-up duration
• Completeness
• Accrucy
• Transparency
• Quality Assurance
Fitness (fit-for-purpose)
ReliabilityRelevance
NMPA Guideline on Using Real World Evidence to Support Drug Development and Decision-making (Implementation for trial)
Application Scenarios of RWE
• Provide Efficacy and Safety Evidence to Support the Registration of New Drugs
• Provide Evidence for Label Modifications to Marketed Drugs
• Provide Evidence for Post-marketing Requirements or Drug Re-evaluation
• Summary and Clinical Development of Distinguished Veteran Traditional Chinese
Medicine Doctors’ Experience Prescription and Traditional Chinese Medicine
Preparation from Medical Institutions
• Other Applications to Support Regulatory Decision Making
NMPA Guideline on Using Real-World Evidence to Support Drug Development and Regulatory Evaluation (For Trial Implementation)
RWE Study Design
• Single arm trial using external control (RWE)
• Pragmatic clinical trial (PCT)
• Observation study
AHRQ. Developing a Protocol for Observational Comparative
Effectiveness Research: A User‘s Guide (2013) was recommended as
a good reference
Common statistical methods in real world study
Descriptive analysis
Non-adjusted analysis
General multivariate regression
Propensity score
Disease risk score
Instrumental variable analysis
Subgroup analysis
Sensitivity analysis
Non-adjusted Adjusted Test robustness
➢Real-world Evidence and the Clinical Questions it Supports
• What is the clinical question of interest to be answered?
• Whether the use of RWE can answer the clinical questions of interest?
• Scientific validity (e.g., with interpretable results, reasonable assumptions, well controlled
type I error, etc.)
• Regulatory requirements (potential conflict with other regulatory requirements, regulatory
requirement for special disease areas, etc.)
• Ethical considerations (ethical issues without using RWE?)
• Operational feasibility (e.g., an independent statistician to ensure blinding and avoid bias
during matching; any other operational challenges, etc.).
Evaluation of Real-World Evidence (1/2)
Evaluation of Real-World Evidence (2/2)
➢Transform Real-world Data to Real-world Evidence
• The research environment and data acquisition need to be close to the real world, such as a more
representative target population, diversity of interventions compatible with clinical practice, or
natural selection of interventions;
• Use of appropriate controls;
• More comprehensive evaluation of drug effectiveness;
• Effective bias control, such as the use of randomization, harmonization of measurement and
evaluation methods, etc.;
• Appropriate statistical analyses, such as the correct use of causal inference methods, reasonable
handling of missing data, adequate and sufficient sensitivity analyses, etc.;
• The transparency and reproducibility of evidence;
• Reasonable interpretation of results;
• Consensus among the relevant parties.
Communication with the regulatory agency
• Scope : Any use of real-world evidence for the purpose of drug registration
• Content:
➢IND
• Study objectives, Feasibility of using real-world evidence, RWD sources, Data
curation plan, Data analysis methods;
• Need to reach consensus on the use of RWE and conduct of RWR.
➢Pre-NDA
• Study implementation status, results and conclusions, NDA requirements.
➢Use real-world evidence to support extended drug combination
Evaluate the effectiveness and safety of bevacizumab in combination with platinum-based
chemotherapy
• A vascular endothelial growth factor (VEGF) humanized monoclonal antibody
• In 2015, it was approved in China for combination with chemotherapy (carboplatin and paclitaxel)
for the first-line treatment of patients with unresectable advanced, metastatic or recurrent non-
squamous non-small cell lung cancer.
• Real-world use of chemotherapy with bevacizumab is not limited to carboplatin and paclitaxel.
• In October 2018, the drug was approved to extend the treatment regimen to a combination with
platinum-based chemotherapy, based on the strong supporting evidence from three real-world studies.
• Combination of bevacizumab with platinum-based chemotherapy significantly prolonged PFS and
OS compared with chemotherapy alone, consistent with global population data, and no new safety
issues have been found.
Case study
Contents
• Development of Regulatory guidance and activities
• Guidance of RWE and RWD delivered by NMPA
• Visions
• RWE and RCT evidence both support regulatory decision-making. The
strength of evidences from RWE, RCT or both of them is depended on
their roles played on the chain of evidences.
• Three crucial elements of real-world study:
• Fitted RWD
• Good design
• Proper analysis
• Bias of selected data must be avoided.
• Current Challenges Of Using RWD in China
• Data infrastructure needs more concern
• Data standards need to be unified
• Policy barriers to data sharing need to be cleared
• Data quality needs to be improved
• Data curation technology needs to be standardized
• Multidisciplinary collaboration mechanism needs to be strengthened
22
Acknowledgement
I would like to acknowledge Dr. Jun Wang from the Center for Drug
Evaluation, NMPA, one of two key authors of “Guiddline on Using
Real World Evidence to Support Drug Development and Decision-
making” and “Guideline on Real World Data Used to Generate Real
World Evidence” delivered by NMPA in 2020, who gave me a lot of
constructive suggestions and shared his insightful views and ideas
with me in preparing this PPT
Q & A
Q: Can you share the thinking regarding the decision for the China approval of Avastin in combination with platinum-based chemotherapy using 3 real-world studies?
A:
• Bevacizumab was approved in combination with chemotherapy (carboplatin orpaclitaxel) in China.
• Off-label use of platinum-based chemotherapy with bevacizumab is a commonphenomenon in the real-world setting.
• RWE generated from three real-world studies. These studies retrospectivelyanalyzed patient data from three hospitals and showed that the combination ofbevacizumab with platinum-based chemotherapy significantly prolonged PFS andOS compared with chemotherapy alone, consistent with global population datawithout new safety issues. In addition, related real-world studies have also provideddata in different patient subgroups such as those with EGFR mutations or brainmetastases, confirming the effectiveness and safety of bevacizumab combinationtherapy from multiple perspectives.
23
Thank you!
NMPA: Guideline on Using Real World Evidence to Support Drug Development and Decision-making (Implementation for trial)
25
1. INTRODUCTION
1.1Background and Purpose
1.2Progress in the Development of Regulations or Guidelines
2. DEFINITIONS IN REAL-WORLD RESEARCH
2.1Real-World Data
2.2Fitness of Data
2.3Real-World Evidence
3. RWE SUPPORTING DRUG REGULATORY DECISIONS
3.1Provide Efficacy and Safety Evidence to Support the
Registration of New Drugs
3.2Provide Evidence for Label Modifications to Marketed
Drugs
3.3Provide Evidence for Post-marketing Requirements or Drug
Re-evaluation
3.4Clinical Development of Traditional Chinese Medicine
3.5Other Applications to Support Regulatory Decision Making
4. THE BASIC DESIGN OF REAL-WORLD RESEARCH
4.1Pragmatic Clinical Trials
4.2Single-arm Trials Using Real-world Data as Control
4.3Observational Studies
5. EVALUATION OF REAL-WORLD EVIDENCE
5.1Real-world Evidence and the Clinical Questions it Supports
5.2Transform Real-world Data to Real-world Evidence
6. COMMUNICATION WITH THE REGULATORY AGENCY
References
Appendix 1: Glossary for Real-World Research
Appendix 2: Examples for Real-World Evidence Application
Appendix 3: Common Statistical Analysis Methods
NMPA: Guideline on Using Real-World Data to Generate Real-World Evidence(Draft for Public Review)
26
1. INTRODUCTION2. Sources and Current Status of RWD
2.1 Common Sources of RWD2.2 Main issues in the application of RWD
3. Fitness Evaluation of RWD3.1 Fitness evaluation of source data3.2 Fitness evaluation of curated data
4. Curation of RWD4.1 Personal information protection and data safety processing4.2 Data extraction4.3 Data Cleaning4.4 Data conversion
4.5 Data transmissing and storage4.6 Data quality control4.7 Common Data Model4.8 RWD curation plan
5. Compliance, Safety and Quality Management System of RWD
5.1 Data Compliance5.2 Data security management5.3 Quality management system
6. Communication with regulatory authorities
Definition of TermsReferences