Biomarkers Consortium Digital Monitoring Technologies

Goals of the Workshop

• Bring together diverse stakeholders in the field to reach consensus on the use of a single vocabulary that will be understood consistently in the regulatory context

• Identify areas of high medical need that could be addressed using digital system technologies

• Ensure stakeholder alignment and application of an evidence-based framework for the use of digital health technologies for therapeutic research and development

The digital tower of Babel

• Language confusion hinders medical practice and drug development o Misinterpretation of evidenceo Misunderstanding of

evidentiary requirements and regulations

o Failure of clinical trials o Delayso Potential harm to patients

• BEST resource used as remedy for biomarkerso Publicly available at

http://www.ncbi.nlm.nih.gov/books/NBK326791/

• Pubmed citationso “digital biomarker” – 8o “wearable” – 12,096o “digital health technology” – 61o “remote sensing technology” –

2,933o “digital measure” – 12 o “mobile application” – 1,419

Disclaimers for workshop lexicon

The use of the term “digital measure” (i.e. digital monitoring technologies, mobile applications) is defined as:• Objective, quantifiable, physiological, functional, and behavioral data collected and measured through

the use of wearables, ingestibles, implantables, and mobile technologies for the remote capture of datao Consistent with definition of mobile technology proposed by CTTI

o Important to level set the group to ‘how this will be used in the Workshop’ – recognizing others may have different definitions or use slightly different lexicon.

The use of the term “device” is to be consistent with the FDA’s definition for a “medical device”

When the tool is not a cleared device (e.g., smartphone, fitbit), we will use the term “technology”

Analysis grid for prioritizing case studies

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Study or Specific Measure Name Measurement Thearpeutic area Measure status STD

Biomarker Type BEST

Algorithm availability STD

Reg path standard

Sensor Deploy Standard

Actigraphy as an assessment of performance status in patients with advanced lung cancer Performance status (ECOG) assessment via actigraphy in NSCLC Cancer existing measure prognostic black box Commercial wearableHome-Based Wearable Continuous ECG Monitoring Patch on Detection of Undiagnosed Atrial Fibrillation ECG patch for asymptomatic Atrial fibriallation Cardio existing measure diagnostic black box FDA Cleared wearable

The HUAWEI Heart study - JACC 2019 & Apple Heart Study Design Wrist wearable for A atrial fibrillation detection Cardio existing measure monitoring black box FDA Cleared wearableEvaluation of Wearable Digital Devices in a Phase I Clinical Trial; Clin Transl Sci (2018) Wearable pulse rate for Tachycardia Cardio existing measure monitoring black box FDA Cleared wearableContinuous Monitoring Using a Wearable Device Detects Activity-Induced Heart Rate Changes After Administration of Amphetamine

monitoring heart rate (HR) and respiratory rate (RR), via single-lead electrocardiogram (ECG) recordings; and mobility and sleep Cardio existing measure response black box FDA Cleared wearable

Home monitoring of HF patients at risk for hospital readmission using a novel under-the-mattress piezoelectric sensor

Heart rate and respiration monitoring during sleep for heart failure and asthma decompensaion Cardio novel measure monitoring black box Commercial In bed

Myocardial Infarction, COmbined-device, Recovery Enhancement Study (MiCORE)

Promoting self management, adherence to guided directed therapy Cardio novel measure prognostic black box Commercial wearable

VERKKO 3G-capable wireless glucose meter Diabetes existing measure monitoring black box unknown wearable

All of Us Research Program CRF Validation Study Smartphone-based measurement of heart rate and VO2max Cardio novel measure diagnostic open sourceResearch-grade tool

Smartphone sensor-based

mPower Parkinsons Study Smartphone-based measurement of tremor Neurodeg novel measure response open sourceResearch-grade tool

Smartphone sensor-based

Several validation studies onDuchenne Muscular Dystrophy patients Stride velocity 95th Percentile DMD novel measure response open source Commercial wearable

Digital biomarkers of mood disorders and symptom change actigraphy Neuropsych existing measure diagnostic published Commercial wearableCircadian rest-activity patterns in bipolar disorder and borderline personality disorder circadian rhythm, rest-activity cycles Neuropsych existing measure monitoring published Commercial wearableRelapse Prediction in Schizophrenia through Digital Phenotyping: A Pilot Study behavior sensing Neuropsych novel measure prognostic published Commercial

Smartphone sensor-based

REMOTE A series of modules (some worked; some didn't) Renal existing measure response published Commercial Smartphone sensor-based

Indoor Air Quality Sensor on Perceptions of and Behaviors Toward Air Pollution Indoor air quality monitoring Health existing measure diagnostic published Commercial In homeAchieving Self-directed Integrated Cancer Aftercare (ASICA) in Melanoma (ASICA) Promoting self exmination of skin amongst melanoma patients Cancer novel measure prognostic unknown unknown

Smartphone sensor-based

Digital Health Feedback System (DHFS) for Longitudinal Monitoring of ARVs Used in HIV Pre-exposure Prophylaxis (PrEP)

Longitudinal Monitoring of ARVs Used in HIV Pre-exposure Prophylaxis (PrEP) Infection novel measure monitoring unknown FDA Cleared

ingestible and a skin patch

Evaluation of a 'Hand-held' Fluorescence Digital Imaging Device for Real-Time Advanced Wound Care Monitoring (JDRTC/UHN) (JDRTC/UHN) Biological and molecular information of a wound Injury repair novel measure diagnostic unknown Commercial Hand HeldTelehealth Management of Parkinson’s Disease Using Wearable Sensors: An Exploratory Study;

motion sensor-based monitoring system(Kinesia™, Great Lakes NeuroTechnologies, Cleveland, OH) Neurodeg existing measure monitoring unknown FDA Cleared wearable

AT-HOME PD Change in Smartphone tapping (score) Neurodeg existing measure monitoring unknown Commercial Smartphone sensor-based

Smartphone-Based Testing to Generate Exploratory Outcome Measures in a Phase 1 Parkinson's Disease Clinical Trial

Smartphone based activity, transitions and movement measurements Neurodeg novel measure monitoring unknown Commercial

Smartphone sensor-based

Filter grid used by planning team

Strategy for selection of case studies

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Existing Measure

Wearable

Commercial

black box Cancer

published Neuropsych

FDA Clearedblack box Cardio

unknown NeuroD

Unknown black box Diabetes

Smartphone sensor-based Commercial

Published Renal

Unknown NeuroD

Novel Measure

Wearable Commercial

Black box Cardio

Open source DMD

Smartphone sensor-based

Commercial

Published Neuropsych

Unknown NeuroD

Research-Grade Tool Open source

Cardio

NeuroD

Unknown unknown Cancer

MEASURESTATUS

SENSORDEPLOYMENT

REGULATORYPATH

ALGORITHMAVAILABILITY

THERAPEUTICAREA

MEASURESTATUS

SENSORDEPLOYMENT

REGULATORYPATH

ALGORITHMAVAILABILITY

THERAPEUTICAREA

1

2

4

1

1

1

1

1

1

1

1

1

1

1

7

Priority criteria for case studies

• At least 2 neuro cases• 1 commercial and 1 cleared• 1 novel and 1 existing• 1 black box and 1 open source• Multimodal vs single measurement type

Workshop case studies

• Mobile Parkinson Observatory for Worldwide, Evidence-based Research (mPower) and Parkinson’s Disease

o Diane Stephenson (Critical Path Institute), Dan Karlin (HealthMode), Abhi Pratap (SageBionetworks), Ninad Amondikar (MJFF), Xuemei Cai (Pfizer)

• Cardiac Monitoring in Phase 1 Clinical Trials

o John Wagner (Foresite Capital), Elena Ismailova (Koneksa Health), Vadim Zupunnikov (Johns Hopkins Univ.)

• Continuous Glucose Monitoring & Remote Digital Monitoring (VERKKO Study)

o Roberto Calle (Pfizer), Nadir Ammour (Sanofi)

• Stride Velocity 95th Centile 2o Endpoint in Duchenne’s Muscular Dystrophy

o Pat Furlong (PPMD), Laurent Servais (Univ. of Oxford), Francesca Cerreta (EMA)

• Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR – MDD)

o Matthew Hotopf (King’s College), Vaibhav Narayan, Linda Brady (NIH/NIMH)

Evidentiary criteria framework

General• Characterization of Relationship Between the

Biomarker and Clinical Outcome• Biological Rationale for Use of Biomarker (If

Known)• Type of Data and Study Design (i.e.

Prospective, Retrospective, etc.)• Independent Data Sets for Qualification• Comparison to current standard• Assay performance• Statistical Methods to Use

Leptak, Menetski, Wagner, et al. Sci Transl Med. 9(417), 2017

General evidentiary criteria document development

Evidentiary CriteriaFramework [Drafts]

Workshop Framework & Case Studies

Case Study 1: Markersof Drug-Induced Kidney Injury

Case Study 2: Hepatotoxicity (GLDH)

Case Study 3: Markers of Drug-Induced Vascular Injury

M-CERSI Analytical Validation Workgroup Input

PhRMA Focus Group Review and Input

FDA Focus Group & Medical Policy Council Input

M-CERSI StatisticalWorkgroup Input

Final Framework

Workshop FeedbackPhRMA Focus Group

Review and Input

FDA Focus Group & Medical Policy Council Input FNIH Biomarkers

Consortium Website,STM publication;

assisted FDA Guidance

What does the framework provide?

• A clear set of steps needed for working toward Biomarker Qualification• Identify key areas for defining biomarker need• Specify and limit biomarker development focus to allow successful generation of

appropriate evidence• Provide consistent set of characteristics to describe and define the biomarker development

program with the regulatory agency

Primary Assumption:• A clearly defined goal to the project will provide a better view of a path to ultimate drug

development decision making and regulatory approval.• The framework provides a context for the discussion between sponsor and the agency

The Specific Context of Use for a Biomarker Drives the Extent of Evidence Needed for Qualification

Analytical Validation(establish performance and acceptance characteristics of the biomarker assay)

Clinical Validation

(establish that the biomarker acceptably identifies, measures, or predicts the

concept of interest)

Reference Ranges/

Decision Points

Pre-Analytical and Assay

Performance Characteristics

Analytical Rigor/ Reproducibility

Study Design Acceptability

Clinical Meaningfulness/Decision Points

Benefit/Risk Assessment

Analytical assay and clinical validation considerations in biomarker qualification

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Sample Handling/ Stability

Adapted from:Peter Stein, M.D.Deputy DirectorOND, CDER, FDA

Flow of data for digital monitoring technologies

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Raw data

Raw processing Processed

data

Final device

processingTransmit

Data

Data security

Data Storage Data

Analysis

Data Interpretation

Tool use

In Device

To Analysis

From Device

Each step needs evidence!

Receive Data

Data security

Raw sensor data

e.g. Heart rate or Blood O2

Packaging; or alerting

Convert to readout

Biology(Biomarker or COA)

Data transfer can occur at any step

FDA Qualification

Data Aggregation

Evidentiary Criteria

Evaluation

Characteristics of Types of EvidenceAs identified in Evidentiary Criteria Workshop – July 2018

• Universalityo to what extent is there evidence across drug mechanisms or across different populations

• Plausibilityo is the biology of the measure so compelling that it adds to the weight of evidence for

acceptance

• Causalityo is there a compelling case for it being causal so there is less of a need for evidence of

universality

• Proportionalityo to what extent does the measure explain the disease or the change in disease

• Specificity and potential for off target effects

Each biomarker class needs a different amounts and types of evidence

Caus

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Plau

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Prop

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Susceptibility/RiskAm

ount

of e

vide

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Surrogate Endpoint

Caus

ality

Plau

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Prop

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Amou

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f evi

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ePrognostic

Caus

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Plau

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Prop

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Amou

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Caus

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Diagnostic

Amou

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The type and amount of evidence will change depending on risk and benefit

Enough evidence needed to convince a company who to include in a trial

Enough evidence needed to convince the FDA that the biomarker faithfully

predicts the biological outcome

Conclusion

• Alignment from multiple, diverse stakeholders • Consistent, comprehensive, semi-quantitative parameters for biomarker qualification• Greater degree of clarity, predictability, and harmonization• Broadly applicable across multiple categories of biomarkers and COUs• Since each category of biomarker and COU has unique factors to consider as part of the development process,

multiple modules are proposed to address these more specific issues

• …and keep in mind that the evidentiary criteria framework, the BEST resource, analytical validation, clinical validation, and qualification have all be discussed and designed for biomarkers, not digital monitoring technologies

Template slides for the case study presentations

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The measurements are for the biology

18

Evidentiary criteria framework

General• Characterization of Relationship Between the

Biomarker and Clinical Outcome• Biological Rationale for Use of Biomarker (If

Known)• Type of Data and Study Design (i.e.

Prospective, Retrospective, etc.)• Independent Data Sets for Qualification• Comparison to current standard• Assay performance• Statistical Methods to Use

Statement of Need

• How is this needed in drug development?– Increase efficiency, safety, speed of drug development?

• Why take the path of digital measure vs. current modalities?• Ex. wearables, smartphone apps, etc.

Take several slides to describe the background that fits into the statement of need and

the known biology

Context of Use

• What decision is going to be made for drug development?

• What is the population involved?

• What factors will define the limits of the decision?

Benefit AssessmentTaken from the Evidentiary Framework Document (Oct 2016). Benefit with respect to the Context of Use (CoU)

• What is the relative perceived benefit of the new measure vs. the current standard (if there is one)?o If novel, there is no standard

• When in the drug development lifecycle is the measure intended to be used?

• How will the measure impact drug development and regulatory review?

• Is the benefit of the measure to the individual or society? o Separate discussions for both

o Does not include business issues

Risk AssessmentTaken from the Evidentiary Framework Document (Oct 2016). Risk with respect to the Context of Use (CoU)

• What is the potential consequence or harm if the measure’s performance is not aligned with expectations based on the COU?

• What is the severity of the disease or condition? What are the unmet needs of the population defined in the COU? What are the risks for mortality and morbidity in the absence of treatment?

• What is the relative overall perceived incremental risk vs. benefit of the new measure vs. the current standard?

• Is the risk of the measure to the individual or society? o Separate discussions for both

o Does not include business issues

• Risk mitigation strategy

State of EvidenceCurrent evidence available:

• Focus on the evidence relevant to the decision being made.

• Single or multi-component measure?

• Existing analytical and clinical validation?

Additional evidence needed to meet the minimum evidentiary standards given the benefit/risk assessment:

• Additional analytical and clinical validation needed

• Highlight gaps in the data that would need to be filled in order to make a confident decision

• Keep in mind that the decision maker is either the FDA reviewer or the industry/trial sponsor

Panel Discussions

• Did the framework help focus the case study discussion?• What was missing from the framework?• What needs to be modified in the framework to address unique questions around

remote monitoring?• Are there suggested modifications to the BEST vocabulary based on the case study?

Extras

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Constructing a biomarker road map

Leptak, Menetski, Wagner, et al. Sci Transl Med. 9(417), 2017

Need statement and context of use (COU)

• Need statemento The nature and extent of the need, drug

development issue it addresses and target population

o The major challenge(s) and unique aspects of these challenges the project is to address

o The reasons and causes for the deficit being addressed

• COU statement – concise description of how a biomarker is intended to be used in drug development

• COU simplified to only 2 elements:o What class of biomarker is proposed and what

information content would it provide? o What question is the biomarker intended to

address? (“What is the biomarker’s specific fit-for-purpose use?”)

Biomarker Classes Susceptibility/Risk: Indicate potential for developing disease in an individual without clinically apparent disease

Diagnostic: Identify patients with a particular disease or a subset of the disease

Monitoring: Detect a change, over time, in the degree or extent of disease

Prognostic: Indicate likelihood of a clinical event, disease recurrence or progression, in the absence of a therapeutic intervention

Predictive: Identify patients likely to experience a favorable or unfavorable effect from a specific treatment

Pharmacodynamic: Indicate that a biological response has occurred in a patient who has received a therapeutic intervention. May become clinical trial endpoints and for a very small subset, surrogate endpoints.

Safety: Indicate toxicity to a therapeutic intervention

BEST Resource (Biomarkers, EndpointS, and other Tools) http://www.ncbi.nlm.nih.gov/books/NBK326791/

Examples of COU

A prognostic marker for disease progression to be used as an inclusion criteria in a Phase 2 clinical trial of a novel drug to enrich for the likelihood of organ transplantation.

BEST: identify likelihood of a clinical event

Clinical Trial Decision

A safety marker for organ toxicity to be used in a Phase 1 clinical trial of a novel drug in addition to a standard measure of organ toxicity to explore and refine the clinical trials stopping criteria.

BEST: response to an intervention or exposure.

Clinical Decision

Benefit and risk

• The benefit and risk profile, given that the COU is related to the biomarker’s value to drug development or clinical trials, is assessed from the perspective of patients

• Benefit assessment o What are the unmet needs of the population defined in the COU? o What is the mortality and morbidity of the disease’s natural history in the

absence of treatment?o What is the severity of the disease or condition? o What is the perceived benefit of the new biomarker vs. the current standard?

• Risk assessment o What is the potential consequence or harm if the biomarker’s performance is not

aligned with expectations based on the COU? o What is the perceived incremental risk, new biomarker vs. current standard?o When in the drug development lifecycle is the biomarker intended use?o What is the scope of the biomarker COU in terms of impacting drug development

and regulatory review?

Examples of benefit and risk analyses

• Favorable benefit and risk profile – lower level of evidenceo Stratification of patients to ensure equal distribution of biomarker positive and biomarker negative individuals in

the different arms of a clinical trialo If biomarker does not perform – loss of resources but not patient safety

• Less favorable benefit and risk profile – moderate level of evidenceo Safety biomarker used in addition to the traditional safety biomarkerso Degree of risk depends on the impact on decision-making in drug development and the risk to patients enrolled in

the trials

• Challenging benefit and risk profile – higher level of evidenceo Surrogate endpointo If the biomarker is not truly a surrogate endpoint for predicting clinical benefit, results invalid and inappropriate

approval decisions madeo Leads to potentially ineffective drugs marketed or patients denied access to effective therapy

Evidence map

• The evidence maps in this framework are inspired by, but not identical to, the one used by Altar et al. (2008)

• The COU choices made determine the overall relative level of benefit and risk• Benefit and risk determined as a result of the COU in turn determines the levels

of evidence needed to evaluate the biomarker for qualification• The evidence acceptable for satisfying evidentiary criteria in some cases may be

partially or entirely composed of retrospective, literature, or other “real world” types of evidence

• The levels of evidence required to qualify the marker can be described according to a series of variables

Altar et al. CPT, 83:368-371, 2008