Industry spotlight
PUBLICATION
Biomarkers are critical to the rational development of medical therapeutics, but significant confusion persists regarding fundamental definitions and concepts involved in their use in research and clinical practice, particularly in the fields of chronic disease and nutrition. Clarification of the definitions of different biomarkers and a better understanding of their appropriate application could result in substantial benefits. This review examines biomarker definitions recently established by the U.S. Food and Drug Administration and the National Institutes of Health as part of their joint Biomarkers, EndpointS, and other Tools (BEST) resource. These definitions are placed in context of their respective uses in patient care, clinical research, or therapeutic development. We explore the distinctions between biomarkers and clinical outcome assessments and discuss the specific definitions and applications of diagnostic, monitoring, pharmacodynamic/response, predictive, prognostic, safety, and susceptibility/risk biomarkers. We also explore the implications of current biomarker development trends, including complex composite biomarkers and digital biomarkers derived from sensors and mobile technologies.
LIBRARY BY DIME
The Library of Digital Endpoints by the Digital Health Measurement Collaborative Community (DATAcc) by the Digital Medicine Society (DiMe), is the only library specifically focused on industry-sponsored studies of new medical products or applications. The library is a living resource that is continuously updated, intended to be both a reference resource and a transparent library the community helps build and maintain. It benchmarks progress in the field and highlights the work we must continue to do to advance the use of digital endpoints to speed medical product development.
QUALIFICATION OPINION FROM EMA
EMA Qualified Endpoint – A real-world example of a digital performance outcome measure with a clearly articulated COU and accepted clinical difference.
PUBLICATION
A scientific perspective arguing that group-level MCID thresholds rarely capture the nuances of Alzheimer’s progression or patients’ real-world priorities; however, sensor-based digital biomarkers—paired with robust anchor, distribution, and longitudinal validation—can detect patient-level change and set stage-specific, patient-centered MCID/MIC thresholds.
PUBLICATION
“What is confusing?
DHT‐derived measures can capture multiple concepts of interests and may include data generated by active tasks performed by patients or passive data acquisition. In some circumstances, DHT‐derived measures constitute conventional biomarkers, such as heart rate measured by electrocardiogram, or blood oxygen saturation by pulse oximetry performed remotely: the nature of these measures align with the definition of biomarkers.
In other circumstances, DHT‐derived measures can constitute COAs, such as the instrumented 6‐minute walk test (6MWT). However, there are scenarios when DHT‐derived measures could be classed as either biomarkers or COAs depending on whether they measure (1) a characteristic as either an indicator of the pathogenic process of a certain disease/condition, or an indicator of a response to an intervention or exposure or (2) a patient’s performance or function linked to a concept that is meaningful to the patient. These DHT‐derived outcomes are objectively measured; can be responsive to change, such as treatment effects or disease progression; and can be used as disease‐screening features and/or to establish response to treatment, in the same way as biomarkers can be used.
As an example, for patients living with congestive heart failure, reduction in mobility (a predictive factor for mortality) can be measured with body‐worn actigraphy devices and could be considered a biomarker supporting a surrogate endpoint. The same digital measure could also be considered a COA because it assesses the patient’s physical capacity.”
PUBLICATION
“The use of multiple anchor measures for analytical validation purposes aligns with the concept of an anchor variable described by the FDA in their Patient-Focused Drug Development guidance for identifying meaningful score differences of clinical outcome assessments.”
FRAMEWORK BY DIME
This Quick Guide explains the crucial role of Intended Use and Indication for Use statements for digital health products in ensuring safe, effective use, and guiding regulatory decisions.
PUBLICATION
“There are currently multiple definitions of the term digital biomarker reported in the scientific literature, and some seem to conflate established definitions of a biomarker and a clinical outcomes assessment (COA). Biomarkers and clinical outcome assessments measure different concepts and both could be useful in understanding the impact of a condition on patients. For example, an investigational product used to treat patients with heart failure could be assessed by measuring a biomarker of the heart’s output (left ventricular ejection fraction) as well as through a COA, a subjective measure of how the patient feels (the Kansas City Cardiomyopathy Questionnaire). Conflating the terms can hamper communication and evidence expectations between medical product developers and regulators. Therefore, a clear definition of the term digital biomarker could potentially facilitate the effective use of a DHT in the evaluation of a medical product, potentially increasing patient access to safe and effective medical products.”
Biomarker definitions and their applications
Rapid development of digital biomarkers through sensors and personal devices.
Lack of established standards for evaluating digital biomarkers.
Challenges in handling large volumes of data, including missing data and outliers.
Recommendations
Improve the quality and reproducibility of research supporting biomarker use.
Ensure rigorous methodology in biomarker assessment.
Foster collaboration across disciplines for biomarker development.
Develop standards for linking digital phenotypes to traditional outcomes.
Address data handling challenges in digital health technologies.
Regulatory Considerations
Substantial validation work required for FDA approval of biomarkers.
Importance of rigorous scientific evidence for regulatory approval.
Need for collaboration in regulatory science to advance biomarker development.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Library of Digital Endpoints
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Qualification Opinion for Stride velocity 95th centile as primary endpoint in studies in ambulatory Duchenne Muscular Dystrophy studies
SV95C provides a reliable and sensitive measure of maximal ambulation, addressing limitations of traditional assessments like the 6MWT.
Real-world data collection via wearable devices enhances accuracy and reflects true ambulatory capabilities.
Longitudinal studies confirmed SV95C’s ability to detect disease progression and response to corticosteroid treatments.
Correlations with existing clinical outcome assessments (6MWT, NSAA, and 4SC) validate SV95C’s construct validity.
Patients and caregivers support the use of wearable devices in clinical trials, emphasizing reduced burden and improved trial attractiveness.
Recommendations
Use SV95C as a primary endpoint in DMD clinical trials to monitor maximal stride velocity in real-world conditions.
Incorporate SV95C alongside traditional endpoints to ensure comprehensive assessment of therapeutic efficacy.
Establish training protocols for patients and caregivers to optimize compliance with device usage.
Expand normative data for SV95C in younger and more diverse patient populations.
Conduct further research on meaningful change thresholds (MCTs) to refine clinical relevance.
Regulatory Considerations
Ensure SV95C is included as a primary endpoint with supporting secondary endpoints (e.g., muscle strength assessments) for consistency.
Validate wearable devices used for SV95C measurement to meet regulatory standards for accuracy and reliability.
Address variability and standardize protocols for data collection to ensure regulatory compliance.
Collect additional longitudinal data to strengthen the predictive value of SV95C for regulatory submissions.
Incorporate privacy and data security measures to comply with data protection regulations, including anonymization and encryption.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Digital biomarkers: Redefining clinical outcomes and the concept of meaningful change
MCID represents the smallest change that someone living with Alzheimer’s disease would identify as important, but faces several universal application challenges. Alzheimer’s disease progresses differently for each individual, complicating the establishment of universal standards that account for individual-level issues. The disease is gradual and evolving, with what is perceived as clinically meaningful varying significantly at early and late disease stages. People living with Alzheimer’s disease and caregivers may have differing perspectives on treatment benefits, making it challenging to establish appropriate MCID. Current Alzheimer’s trials rely on various tests to evaluate cognitive and functional impairments, but these tests often lack sensitivity to early-stage changes and are affected by variability in rater rankings. Digital biomarkers offer promising approaches for detecting real-time, objective clinical differences and improving patient outcomes through continuous monitoring, individualized assessments, and artificial intelligence learning for complex analytical predictions.
Recommendations
Digital biomarkers and advanced health technologies should be leveraged to enable continuous monitoring and individualized assessments that can better capture meaningful change in Alzheimer’s disease. The primary focus must remain on outcomes that truly matter to people living with Alzheimer’s disease and their caregivers, ensuring that the principle of clinical meaningfulness is not lost as new technologies are introduced.
Regulatory Considerations
Important considerations around standardization, accuracy, and integration into current clinical frameworks must be addressed as digital biomarkers are adopted. As new technologies are introduced alongside evolving regulatory frameworks, maintaining focus on clinically meaningful outcomes for patients and caregivers is essential.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Digital health technology derived measures: Biomarkers or clinical outcome assessments?
Limited number of drugs approved using DHT data for labeling claims.
Lack of clarity on definitions and regulatory pathways for DHT-derived endpoints.
Challenges in global studies due to varying definitions among regulatory authorities.
Fine line between using DHT-derived measures for therapy response and quality of life assessments.
Recommendations
Create clear definitions for DHT-derived tools and measures.
Define specific evidentiary criteria for DHT-based tools.
Leverage precompetitive public-private partnerships to advance DHT development.
Utilize existing regulatory pathways like the iSTAND pilot program.
Regulatory Considerations
Need for harmonized global definitions and pathways for DHT-derived measures.
Use of existing programs like the iSTAND pilot program to integrate new digital measures.
Clear guidance from FDA and EMA for qualifying biomarkers or COAs in drug development.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
A Hierarchical Framework for Selecting Reference Measures for the Analytical Validation of Sensor-Based Digital Health Technologies
The quality of evidence for the analytical validation of sensor-based digital health technologies (sDHTs), which is the evaluation of algorithms converting sensor data into a clinically interpretable measure, is often inconsistent and insufficient. The existing V3+ framework codifies the overall evaluation process, which includes verification, usability validation, analytical validation, and clinical validation. To improve the scientific rigor of analytical validation, a hierarchical framework for selecting reference measures is needed because not all potential reference measures are of equal quality. The framework classifies reference measures based on attributes that contribute to reduced measurement variability, with defining and principal measures being the most rigorous due to objective data acquisition and the ability to retain source data.
Recommendations
The proposed framework sequentially moves the investigator through four steps: (1) Compile preliminary information, including the digital clinical measure, context of use (COU), algorithm requirements, and sensor verification evidence . (2) Select an existing reference measure, develop a novel comparator, or identify a set of anchor measures, prioritizing measures with the highest scientific rigor (defining → principal → manual → reported) . (3) Consider the impact of the data collection environment to determine if the analytical validation study can be conducted in the intended use environment with the highest-order measure, or if in-lab validation is necessary, ensuring the results are generalizable . (4) Describe the rationale for key study design decisions to encourage transparency for evaluators, regulators, and payers . Investigators must justify passing over a higher-ranked reference measure, generally only acceptable if the higher-ranked measure poses unacceptable risk or is not applicable to the context of use.
Regulatory Considerations
The principles of the framework for analytical validation apply regardless of the regulatory status of the sDHT (regulated medical device, low-risk general wellness apps, or research product) or its intended use (clinical care or clinical research). The framework is intended to help investigators support the most rigorous claims regarding sDHT performance, which is important for acceptance by evaluators, peer-reviewers, regulators, and payers. The categorization of the digital clinical measure as a digital biomarker or an electronic clinical outcome assessment also does not change the framework’s applicability.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Quick Guide on Intended Use and Indication for Use for Digital Health Products
The use of Intended Use and Indication for Use is crucial for digital health products to ensure the product is used appropriately and effectively to meet the needs of the intended population. This information helps establish clear expectations for a product’s performance and safety, facilitates regulatory approval, and ensures compliance. The Intended Use provides a general description of the digital health product’s purpose or function. The Indication for Use describes the disease or condition the device will diagnose, treat, prevent, cure, or mitigate, including a description of the patient population. A change in a product’s indication for use from general to specific usually results in a narrower indication concerning function, target population, or disease entity. Levels of specificity for diagnostic and therapeutic products can be categorized, ranging from the identification of a physical parameter (most general) to the identification of an effect on the clinical outcome (most specific).
Recommendations
The Intended Use statement should include the name of the product, the medical purpose, and what it is trying to do for the user. The Indication for Use statement should include the name of the product, the specific condition or disease state it is addressing, the patient population being targeted, what the product features do, whether other technology components are used with the product, and whether it is for “prescription” or “over-the-counter” use. Developers should characterize the users (e.g., by age, knowledge, or language) and describe the usage context (e.g., hospital ward, emergency room, web-based app). The Indication for Use statement should clearly state the product’s clinical capabilities and what it is not intended for (e.g., not intended to provide a diagnosis or replace traditional methods).
Regulatory Considerations
The information provided in the Intended Use and Indication for Use statements is used to inform the product’s design and development, as well as to guide regulatory decisions about its approval and marketing. Defining these statements facilitates the regulatory approval process and helps ensure compliance with relevant regulations and standards. The FDA defines the levels of specificity as a qualitative ranking of the proposed indications for use. The document provides examples of FDA’s “Indications for Use” from submissions, such as the use of an Atrial Fibrillation History Feature, illustrating the necessary detail for regulatory submissions like a 510(k).
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
Digital biomarkers: Convergence of digital health technologies and biomarkers
Digital biomarkers should align with the FDA-NIH definition of biomarkers as indicators of biological processes, avoiding conflation with COAs, which measure patient-reported or observed outcomes.
Digital biomarkers can consolidate data from multiple DHTs to derive context-rich health indicators, enhancing population baselines and patient-specific insights.
Applications include detecting atrial fibrillation via wearable sensors, monitoring tremors in Parkinson’s patients, and assessing gait in Huntington’s disease, each emphasizing specific biomarker categories (e.g., diagnostic or monitoring).
Inconsistent use of the term “digital biomarker” may impede communication between developers and regulators, complicating evidence requirements for medical product evaluation.
External factors, such as pollen counts for asthma or UV exposure for photosensitivity, can complement digital biomarkers, offering comprehensive health insights.
Recommendations
Standardize the term “digital biomarker” within the healthcare and regulatory communities to improve consistency in research and medical product evaluations.
Foster collaboration across the healthcare ecosystem to ensure DHTs are integrated effectively into clinical workflows and regulatory frameworks.
Explore opportunities to combine digital biomarkers with environmental data to enhance predictive and preventative healthcare applications.
Encourage ongoing validation of digital biomarkers through robust analytical and clinical studies to build confidence in their utility and regulatory acceptance.
Incorporate patient-centric design principles into DHTs to ensure usability and relevance across diverse patient populations.
Regulatory Considerations
Align digital biomarker definitions with FDA guidance to ensure clarity in regulatory submissions and evaluations.
Validate digital biomarkers with evidence that demonstrates analytical validity, clinical validity, and clinical utility for their intended use.
Include considerations for patient privacy and data security, especially when integrating external environmental data into digital biomarker systems.
Develop frameworks for evidence generation that address both individual patient and population-level health insights, enabling broad regulatory and clinical applications.
Establish clear pathways for incorporating digital biomarkers into the regulatory review process, including guidance on how to demonstrate reliability and relevance.
Some summaries are generated with the help of a large language model; always view the linked primary source of a resource you are interested in.
For reference: review the relevant regulatory guidances
Regulatory spotlight
Features essential guidance, publications, and communications from regulatory bodies relevant to this section. Use these resources to inform your regulatory strategy and ensure compliance.