アダプティブ・プラットフォーム試験の設計：
REMAP-CAP を例にDesign choices of adaptive platform trials:
REMAP-CAP as an example
December 2, 2022

生物統計情報学シンポジウム「プラットフォーム臨床試験の統計学的課題と今後の展望～国内外における取り組みと事例に基づく議論～」
場所：東京大学大学院 情報学環・福武ホールおよびオンライン
東京大学 一原直昭

Nao Ichihara , The University of Tokyo

The presenter• Involved in• Design, statistics, and management of clinical registries andobservational studies• Regional and global management of REMAP-CAP• Design and planning of other APTs in/outside Japan• Has no conflict of interest

This presentation• The background, purpose, design features, and history of
REMAP-CAP as an example of an adaptive platform trial(APT)• Emphasis will be put on importance of design choicesthat reflect the purpose of the clinical trial• Some other non-statistical issues• Specific example for a generic conclusion

Establishing effective
treatment during theCOVID-19 pandemic
Successes and failuresSuccess: effective treatment was rapidly
established against COVID-19

World Health Organization. Therapeutics and COVID-19 Living Guideline. 22 April 2022.

Failure: lack of consorted effort in clinical study
and limited number of large trials

Nat Rev Drug Discov. 2021;20(4):254-255.

Are small clinical trials meaningful because they
contribute through meta-analysis?

https://ivmmeta.com/

Two major barriers in clinical trials(Pandemic and non-pandemic times)
1. Barrier to plan, conduct, and complete RCTs
2. Barrier to secure enrollment volume of RCTsExample of APT
REMAP-CAP

Visual Capitalist.
https://www.visualcapitalist.com/history-of-pandemics-deadliest/

Infection epidemics since 2000

REMAP-CAP
2016～ REMAP-CAP
症例登録

http://apps.who.int/iris/bitstream/handle/10665/272442/9789241565530-eng.pdf?ua=1REMAP-CAP• An APT• Population: adult patients with CAP or “pandemicdisease” (currently COVID-19)• Tests multiple treatments in multiple domains• Primary endpoints:• 90-day mortality in CAP patients• OSFD, censored on Day 21, in pandemic disease (COVID-19)
patients

REMAP-CAP

20,691

18,07957

Patient
randomizations

Patients
randomizations
with COVID-19

Current or completedinterventions in 17
domains

11,705

10,007326

Total patients

Patients withCOVID-19

Active Sites（26 countries）

As of Sep 17, 2022
https://www.remapcap.org, https://twitter.com/remap_cap/status/1524362298986487810?s=20&t=YfP030ypqL2SSLwhsv4A8Q

REMAP-CAP

R: Randomised
E: Embedded
M: Multifactorial
A: Adaptive
P: Platform Trial for Community Acquired Pneumonia

GCP (Good Clinical Practice) 準拠

Endorsed by WHO

REMAP-CAP• Purpose: fast provision of evidence for responding to a
global epidemic of respiratory infection (=pandemic)• Principles• Ensure scale through pragmatism• International “collaboration” with literally multilateral relationshipamong researchers. Emphasis on inclusion of LMICs and countries
with limited resources, e.g., Japan, with or without financial
capability to contribute to the platform• Design/operational features (reflecting the specific purpose)• Running APT through non-pandemic periods• Adapting the protocol in response to a pandemic• Open label (with exceptions) + “hard endpoints”• Given effective trade-off between speed through scale andimplementation of some bias-minimizing design features,
REMAP-CAP is designed to hit a balance optimized for apandemicComponents of the protocolAdaptive Platform Trial (APT)
Conventional design: Separate resources for each clinical question
Macrolide for
immunomodulation

Anticoagulation

Ventilation

High-dose
MacrolideLow-dose

Protocolized
Results

Results
No macrolide

No doseResults

Nonprotocolized

RCTs are executed for each treatment domain. No routine co-enrollment.
Costly, time-consuming, and causes burden on sites.

APT: Shared resources + question-specific “domains”
Domain 1: Aticoagulant

Domain 2: Antivirals
Domain 3: Investigational drug A

Cost-effective, fast, and less risky

Angus DC. Fusing Randomized Trials With Big Data: The Key to Self-learning Health Care Systems? JAMA. 2015;314(8):767–768.

Permanent adaptive platform trial
for rapid response to a pandemic
Conventional design| Start a new RCT
Investigational drug A

Design/protocol writing, ethics review, organizing
study group, engaging participating sites…

Drug A
Results
Control

Costly, time-consuming, and risky

REMAP-CAP| Add a “domain” to an existing platform
Domain 1: Aticoagulant
Domain 2: Antivirals
Domain 3: Investigational drug A

Cost-effective, fast, and less risky

Angus DC. Fusing Randomized Trials With Big Data: The Key to Self-learning Health Care Systems? JAMA. 2015;314(8):767–768.

Multifactorial design
Conventional design| Multiple RCTs
Macrolide for
immunomodulation

Anticoagulation

Ventilation

High-dose
MacrolideLow-dose
No doseProtocolizedResults

Results

Results

Nonprotocolized

No macrolide

RCTs are executed for each treatment domain. Costly, time-consuming, and causes burden on sites.

Platform is operated indefinitely
with domains replaced

REMAP-CAP| Multifactorial design
Domain 1: Anticoagulation
Domain 2: Antivirals

Domain 3: Ventilation strategy
A single patient canparticipate inmultiple domains, each of whichcorresponding to an RCT

Effectively run multiple RCTs;
efficientStreamlining site participation;
efficient, less burden on sites
Angus DC. Fusing Randomized Trials With Big Data: The Key to Self-learning Health Care Systems? JAMA. 2015;314(8):767–768.

Repeated interim analysis
Based on Bayesian statistics
Conventional design | Pre-determined enrolment volume
Anticoagulation

Targetenrolment
volumeTermination

Antivirals

Targetenrolment
volumeTermination

Ventilation strategy

Targetenrolment
volumeTermination

Enrolment is continued until pre-determined target volume is reached;(1) Potentially wasteful enrolment(2) Risk of failure to deliver conclusive results even with planned enrolment volume

REMAP-CAP | Repeated analysis based on Bayesian statistics
Anticoagulation

IAIAIA

Antivirals
Ventilation strategy

Termination

IAIAIAIA:
interimanalysis

Termination

IAInterim analysis is conducted at a pre-specified interval, andenrolment is terminated with statistical conclusion;(1) No wasteful enrolment(2) No risk associated with pre-determined enrolment volume

IATermination

Especially effective withlimited preexisting knowledge,e.g., in a pandemic

Angus DC. Fusing Randomized Trials With Big Data: The Key to Self-learning Health Care Systems? JAMA. 2015;314(8):767–768.

Response adaptive randomization (RAR)

Conventional design | Fixed-ratio randomization
Intervention A

Randomization

Intervention B
Standard care (control)

Randomization ratio is fixed; (1) psychological barrier for participation,(2) potential ethical concern, (3) challenging to compare many treatments

REMAP-CAP | Response-adaptive randomization
Intervention A

Randomization

Intervention B

Interimanalysis
based onBayesianStandard care (control)

statistics

Reflecting results of interim analyses, randomization ratio is adjusted to “favor” the more
promising treatments, and patients will likely receive the best treatment.
(1) Reduces psychological barrier, (2) mitigates ethical concern,(3) Identify the best treatment
when there are multiple candidate treatments
Angus DC. Fusing Randomized Trials With Big Data: The Key to Self-learning Health Care Systems? JAMA. 2015;314(8):767–768.

Protocol adaptation
in REMAP-CAP• Specifying the pandemic disease (COVID-19) and aspecific primary endpoint• Domains (add/drop)• Interventions (add/drop)• Inclusion of pediatric patientsContribution of APTs during
the COVID-19 pandemic
REMAP-CAP as an exampleWHO Living Guideline

WHO Living Guideline

World Health Organization. Therapeutics and COVID-19 Living Guideline. 22 April 2022.

WHO Living Guideline

World Health Organization. Therapeutics and COVID-19 Living Guideline. 22 April 2022.

Contribution of REMAP-CAP
To establishing COVID-19 treatment

World Health Organization. Therapeutics and COVID-19 Living Guideline. 22 April 2022.

COVID-19治療確立にREMAP-CAPが果たした役割
Corticosteroid

Results from REMAP-CAPImmune
modulators

N Engl J Med. 2021 Feb 25

Results from REMAP-CAP
Antivirals and hydrooxychloroquine

J Crit Care. Published 12 July 2021.

Results from REMAP-CAP
Anticoagulation

Through collaboration with other large scale trials

N Engl J Med. Published Aug 4, 2021.

N Engl J Med. Published Aug 4, 2021.

Results from REMAP-CAP
Convalescent plasmaPublications from REMAP-CAP
Corticosteroids

Anticoagulation

Immunomodulators

Convalescent Plasma

Antivirals

Antiplatelets

and more to come…

COVID-19治療法確立に貢献：
パンデミック初期におけるスピード感
Corticosteroid

January 31, 2020
WHO declared PHEIC*Public Heal Emergency of International Concern国際的に懸念される公衆衛生上の緊急事態

January 31, 2020
Revised protocol was published ****Pandemic Appendix only revised

March 9, 2020
The first patient was enrolled in the Corticosteroid domain of REMAP-CAP
June 16, 2020
Press release on effectiveness of corticosteroid from the RECOVERY Trial
June 17, 2020
Patient enrollment for REMAP-CAP Corticosteroid domain was terminatedAugust 12, 2020
Patient follow-up of the REMAP-CAP Corticosteroid domain was completed
September 2, 2020

Results of the REMAP-CAP Corticosteroid domain was published on JAMA

Meta-analysis: pathway for establishing treatment

CorticosteroidImmune
modulators

Anticoagulation

Publications from REMAP-CAP• Results of all the “completed” domains have been
published• Some domains have been / and likely to be discontinued
due to slow enrolment

Definition of an APT

Adaptive Platform Trials (APTs)“the broad goal of finding the best treatment for adisease by simultaneously investigating multipletreatments”

Growing interests in APTs because of“the need to rapidly evaluate multiple potential treatments”“the ethical imperative to achieve the best possible outcomes intrial participants”
JAMA. 2015;313(16):1619.

Adaptive Platform Trials (APTs)
Conventional design: Separate resources for each clinical question
Macrolide for
immunomodulation

Anticoagulation

Ventilation

High-dose
MacrolideLow-dose

ProtocolizedResults

Results
No macrolide

No doseResults

Nonprotocolized

RCTs are executed for each treatment domain. No routine co-enrollment.
Costly, time-consuming, and causes burden on sites.

APT: Shared resources + question-specific “domains”
Domain 1: Aticoagulant

Domain 2: Antivirals
Domain 3: Investigational drug A

Cost-effective, fast, and less risky

Angus DC. Fusing Randomized Trials With Big Data: The Key to Self-learning Health Care Systems? JAMA. 2015;314(8):767–768.

Design features associated with APTs
• Multifactorial design• Maximum value per patient• Challenge with co-enrollment across multiple traditional
studies• Use of non-concurrent control• Repeated analysis based on Bayesian statistics• Response-adaptive randomization• Protocol adaptation beyond addition/deletion ofinterventions/domains, e.g.,• Addition of new populations and strata

Advantages of APTs
• Cost-effectiveness through resource sharing• Management of the protocol• Management of study database (EDC)• Management of data, e.g., monitoring• Management/support of sites• Statistics• Scalability• Enables a complex organization, e.g., internationalcollaboration• Resource building and continuous improvement
through long-term operation• Patient and family engagement

Strategies associatedwith APTs
Large simple trial (LST) and international collaboration,
Permanent multi-study clinical research network,
Contributorship-based academic assessment

Large Simple Trials (LSTs)“pragmatically designed studies that enroll a large
number of participants according to a relatively
straightforward protocol”• Simple protocol• Limited number of inclusion and exclusion criteria• Heterogeneous population
Multicenter, multinational• Close to the real-world
Large enrolment volume• Allows embedding the trial into routine clinical• Sensitive
practice
External validity• Avoid administrative burden
Cost-effective• Randomization• Typically, open-label• Endpoints – not “surrogate endpoints”• “Hard” and objectively measurable• Directly relevant

Typical features••••

Saesen R, Huys I. COVID-19 clinical trials: see it big and keep it simple.
BMJ Evidence-Based Medicine. 2021;26:147–148.

Relatively simple data collection
in REMAP-CAP• Screening• Baseline• Day X
• No mandatory lab tests or any
other non-routine measurements• Discharge outcome• Day 90 outcome• (Optional Day 180 outcome)• Serious adverse events• Protocol deviation(Extreme example)
Simple data collectionin WHO SOLIDARITY•••

Open-label RCT
100+ countries
Data are collected only at
the times of:• randomization(baseline)• discharge or death(discharge outcome)Is REMAP-CAP an exploratory trial, ora confirmatory trial?
• Pragmatic trial specializing in response to a pandemic
which defies the “exploratory vs. confirmatory trials”
framework• However, in existing “exploratory vs. confirmatorytrials” framework, most of its domains do not fulfill
requirements as a confirmatory trial, e.g., collectionof detailed safety data, and is considered exploratory• This more reflects the pragmatism of REMAP-CAP asa strategy for expand its scale, rather than its
fundamental design. REMAP-CAP can be used as aplatform for confirmatory trials, with examples of:• Immune Modulation 2 Domain• ACE2-RAS Domain

International collaboration• Ubiquitously discussed, infrequently achieved• Multilateralism vs. single strong leadership• REMAP-CAP is based on multilateral collaboration• Designed and launched by researchers in: UK, EU, Canada, AUS/NZ, and US• Other regions have joined since (now 30+ countries)• Key functions are distributed across regions• Chairperson of the steering committee changes every year (previous ITSC
chair served for 2+ years as an exception)• Global Project Manager is based in Australia. Manages protocol documents,EDC, Website, etc.
• UK ICNARC serves as the DCC (Data Coordinating Center). Previously, Monash.
• Many specific committees• Design team
• Pharma Liaison• PPI• Financing• Regional sponsors are responsible for funding operational cost in each region• Central costs are distributed across regions through negotiation, with aprinciple to incorporate (1) recruitment volume, and (2) financial capacity

A Permanent Multi-study
Clinical Research Network• Some of APTs’ advantages can be achieved
through a platform of trials, or integration ofmultiple trials at the organizational level, notnecessarily a platform trial, or integration ofmultiple trials at the protocol level• Platform of trials ≒ permanent multi-study
clinical research network

A Permanent Multi-study
Clinical Research Network
A traditional CRN

A permanent multistudy CRN• Developed based on
existing networks ofresearchers (“… StudyGroup”)• Representatives of thesites are listed as“authors” of themanuscript• Participation of sites with limited
resources for clinical trials• Questionable practice• Difficult to engage sites
beyond existing networks• Often without any
financial compensation• Site participation• does not lead to “authorship”• serves as an opportunity fordeveloping skills in clinical trials• Expansion beyond networks ofresearchers• Resource sharing across studies anddisciplines• Economic efficiency• Financial compensation• Resource building/problem solving
beyond specific studies

A Permanent Clinical Research Network:Functions• Support for sites• Securing trained CRCs/CRAs (clinical researchcoordinators/associates)• Training/education of clinical staff• Minimize administrative burden• Standardized admin process, e.g., contract, datacollection including EDC, monitoring, andpayment• Remote access to source data, i.e., EHR• “Regulatory science”

Evaluating contribution tocomplex/large-scale clinical research• Complex protocols, e.g., APTs, and complex
research organizations, e.g., pmCRNs,
require contribution of experts to the“central” resources• Poorly aligned with the current environmentof the academia that encourages a larger
number of publications per person• Authorship cannot be the sole indicator• From “publish to perish” to contributorshipbased academic assessment

Remaining challenges
Some old issues with clinical research must be addressed for
APTs to be leveraged

Remaining challenges:
Team/organization building• Operational complexity• “(re-)building an airplane while flying it”• Governance/leadership• Think protocols. Think beyond protocols(organizations).
• Involvement of junior investigators and allied
health professionals• From authorship to “contributorship”

Remaining challenges: mitigating publication
bias and promoting large-scale collaboration• Publication bias
• Published study results are still biased even withstudy registration. How can we ensurecompletion and publication of “negative”
studies?

• Limited large-scale collaboration• Clinical research resources are excessively
dispersed: especially patients and trained
personnel• “Publish or perish” culture encourages small
studies - need to redesign academic incentives

Remaining challenges: Leveraging design features with tradeoffs and improving predictability of regulator decisions• Design choices with trade-offs: when?
• Use of non-concurrent control:
Feasibility/efficiency/cost/scale vs. bias avoidance• Response-adaptive randomization: perceived ethicalbenefit and potential increase in patient recruitment vs.
bias avoidance and efficiency (required enrollmentvolume)• Researcher-regulator exchange• Effectively leveraging APTs’ design choices that involve
trade-offs necessitates predictability of regulators’
responses to study results• Regulatory agencies must provide more effective
prospective consultation

Remaining challenges:
Reporting results of APTs
• Increased complexity of trials needs to be addressed bycorresponding transparency measures: additional items
specifically for APTs
• Clinical trials (trial registries)• Clinical trial results (manuscripts)• Non-concurrent control, e.g., enrollment volume in each month• Co-enrollment with other trials/domains• Existing guideline:• The Adaptive designs CONSORT Extension (ACE) statement: achecklist with explanation and elaboration guideline forreporting randomised trials that use an adaptive design