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