Findings
The FDA classifies CDS software as Non-Device CDS only if it meets four specific criteria related to data inputs, information display, HCP support, and independent reviewability. Software functions that analyze medical images, signals from IVDs, or patterns from signal acquisition systems remain regulated as medical devices. Non-Device CDS must be intended for health care professionals and not for patients or caregivers. Automation bias and the time-critical nature of decision-making are key factors in determining whether an HCP can truly review the basis of a recommendation independently. If software provides a specific diagnostic or treatment directive rather than a list of options, it generally fails to meet the exclusion criteria.

Recommendations
Developers should ensure that software intended as Non-Device CDS provides a plain language description of the underlying algorithm and the data used for validation. The software or labeling must clearly identify the intended HCP user, the patient population, and the required input medical information. To support independent review, the software should highlight the source of its clinical recommendations, such as specific clinical practice guidelines or peer-reviewed studies. Developers are encouraged to use usability testing to verify that HCPs can understand the basis of recommendations without relying primarily on the software’s output. For multiple function products, developers should follow the FDA’s policy for assessing products that contain both device and non-device functions.

Regulatory Considerations
The FDA applies a risk-based approach to software oversight, focusing on functions that acquire or analyze complex medical data like ECG waveforms or genomic sequences. Software intended for time-sensitive or critical medical decisions is typically regulated as a device because the user lacks the time to independently verify the recommendation. The agency intends to exercise enforcement discretion for certain software functions that provide only one clinically appropriate recommendation if all other non-device criteria are met. Sponsors may use the Q-Submission process to discuss alternative approaches or clarify the regulatory status of specific software functions. Existing digital health policies continue to apply to software functions that meet the device definition, including mobile medical applications.

Findings
General wellness products are defined by two factors: they are intended only for general wellness use and present a low risk to user safety. The FDA categorizes wellness uses into those relating to a general state of health (e.g., weight management, physical fitness, sleep) and those relating to chronic diseases where lifestyle choices are well-accepted to play a role in health outcomes. Products are not considered low risk if they are invasive, implanted, or involve technologies like lasers or radiation that require specific regulatory controls. Software functions intended for maintaining a healthy lifestyle that are unrelated to the diagnosis or treatment of a disease are explicitly excluded from the statutory definition of a medical device.

Recommendations
Manufacturers should ensure that claims for general wellness products are limited to sustaining or improving general health functions or encouraging healthy lifestyle choices for living well with chronic conditions. Disease-related claims must be supported by peer-reviewed scientific publications or official statements from healthcare professional organizations. Labeling and marketing communications must be consistent with and not exceed the product's stated intended use. For products using non-invasive sensing to estimate physiologic parameters, manufacturers should validate these outputs if they mimic values used clinically. If a product includes notifications to see a doctor, these should not name specific diseases or characterize outputs as pathological.

Regulatory Considerations
For products meeting the low-risk general wellness criteria, the FDA does not intend to enforce requirements such as registration and listing, premarket notification, or Quality Management System regulations. The FDA may coordinate with the Consumer Product Safety Commission to determine jurisdiction over specific products. If a product targets the diagnosis, screening, or management of a disease through alerts or clinical thresholds, it is generally not considered a general wellness product and is subject to standard medical device regulations. Industry members may contact the Digital Health Center of Excellence or use the Q-Submission process to discuss alternative approaches or clarify the regulatory status of a specific product.

Findings
Existing guidelines lack pragmatic application and systematic approach for device selection.
Device choice is dependent on measurement objectives, user population, and available resources.
Current frameworks do not systematically consider verification, validation, feasibility, and protocol design.
Rapid obsolescence of digital devices due to technological advancements.
Need to incorporate social/psychological factors into device selection.

Recommendations
Develop a practical guide with a systematic approach for selecting wearable devices.
Use five core criteria: continuous monitoring capability, device suitability and availability, technical performance, feasibility of use, and cost evaluation.
Prioritize feasibility of use to ensure user needs are incorporated into the selection process.
Adapt guide criteria to accommodate novel innovations.
Foster clarity and transparency in decision-making among researchers, HCPs, and device users.

Regulatory Considerations
Follow FDA guidance for digital health technology usage in clinical investigations.
Consider CTTI recommendations for improving clinical trial quality and efficiency.
Use ePRO Consortium's factors for device suitability in regulatory trials.
Apply international guidelines for specific measurements when available.

Findings
Product development firms are hesitant to increase DHT use despite regulatory support.
Conventional hardware-based technologies are preferred over newer digital tools.
Operational barriers contribute to the low adoption of DHTs in product development trials.

Recommendations
Reduce operational barriers to facilitate DHT adoption.
Provide additional regulatory clarity to encourage DHT use.
Encourage the incorporation of more DHTs and patient-centric endpoints in clinical trials.

Regulatory Considerations
The FDA's guidance on DHT use is evolving and not yet fully formalized.
There is a need for harmonization between US and non-US regulatory agencies.
The impact of recent regulatory support may take years to be fully realized.

Findings
There is widespread confusion among digital health developers regarding the complex and evolving regulatory landscape, with many uncertain about whether their products require regulation or which pathway to pursue. This lack of a clear regulatory strategy acts as a significant barrier to market access, investor confidence, and user trust. The heterogeneity of the digital health sector, coupled with varying international requirements, further complicates the path to market for innovators, hindering the scalability of effective solutions.

Recommendations
Digital health innovators should proactively integrate a tailored regulatory strategy into their core business plan, viewing it as a commercial differentiator rather than a hurdle. Developers are encouraged to utilize resources like DiMe’s regulatory pathway tools to navigate the U.S. and global landscapes effectively. Early and continuous engagement with regulators and collaborative efforts across the industry are essential to ensure products are developed to meet both market needs and regulatory standards, ultimately accelerating the delivery of high-quality digital health solutions to patients.

Regulatory Considerations
A comprehensive policy framework is necessary for the successful integration of digital health technologies, encompassing regulatory authorization, value assessment, and reimbursement. Developers must understand the nuances of different regulatory classifications, such as Software as a Medical Device (SaMD), and their specific evidentiary requirements. Greater international harmonization of regulatory standards is crucial for enabling global scalability. Regulatory bodies should continue to develop agile frameworks that can accommodate the rapid pace of innovation in digital health while ensuring patient safety and product effectiveness.

Findings
There is a need for comprehensive validation and verification processes for DHTs.
Ensuring data security and privacy is a significant concern.
Usability issues for diverse populations need to be addressed.
There is a lack of clarity on whether certain DHTs meet the definition of a device under the FD&C Act.
The guidance does not establish legally enforceable responsibilities.

Recommendations
Ensure DHTs are fit-for-purpose for clinical investigations.
Implement robust data security measures to protect participant information.
Conduct usability evaluations to ensure DHTs can be used by intended populations.
Engage with FDA early to discuss the use of DHTs in clinical investigations.
Develop a risk management plan to address potential issues with DHT use.

Regulatory Considerations
Verification and validation should be addressed regardless of device classification.
Sponsors should ensure compliance with data protection and privacy regulations.
FDA evaluates DHT data based on endpoints, medical products, and patient populations. Sponsors can engage with FDA’s Q-Submission Program for feedback on DHT usage in clinical trials.
Sponsors should understand the legal implications of using DHTs in clinical investigations.
The guidance provides recommendations but does not establish legally enforceable responsibilities.

Findings
There is a notable lack of reports on the use of digital health technology in pediatric patients.
Challenges exist in selecting the design, metrics, and types of sensors best suited for disease evaluation.
False positive detection remains problematic in seizure detection using DHTs.
There is a lack of information on the use of DHTs in infants.
Unique design challenges for pediatric DHTs arise from size, anatomy, physiology, activity levels, and cognitive development.

Recommendations
Further research and evaluation are needed to realize the full potential of remote monitoring in pediatric trials.
Creative approaches, including machine learning, should be employed to identify optimal measurement methods.
Training for caregivers is necessary to ensure DHTs are worn correctly and data are complete.

Regulatory Considerations
Confirming the reliability and clinical relevance of DHT measurements is essential.
Ensuring privacy and confidentiality of patient data must be prioritized.

Findings
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).

Findings
The review includes 275 studies, with neurology, musculoskeletal disorders, and cardiology as the most common therapeutic areas.
The studies focused on sensor performance (48%), algorithm development (86%), operational feasibility (46%), and software development (9%).
Gaps in reporting included insufficient details on software used (27%), comparator measures (17%), and participant demographics (e.g., age and gender were missing in 9% and 15% of studies, respectively).
Sixty-seven percent of the studies used wearable sensors, while others incorporated smartphones, tablets, cameras, and implantable devices.
The lack of methodological and reporting standards across studies hinders reproducibility and broader applicability.

Recommendations
Develop methodological and reporting standards to improve consistency across feasibility studies.
Include comprehensive participant demographic data, including sociodemographics and health indicators, to ensure inclusivity and generalizability.
Conduct small feasibility studies to validate sensors, optimize algorithms, and identify operational challenges before launching full-scale trials. Use the database created from this review to inform trial design and technology selection, ensuring alignment with specific research goals.
Encourage collaboration among investigators, sponsors, and regulators to standardize methods and share insights to avoid redundant studies.

Regulatory Considerations
Align sensor verification and algorithm validation processes with regulatory requirements for reliable clinical endpoints.
Ensure secure and ethical data transfer, storage, and sharing practices for compliance with privacy regulations.
Address barriers to participation for underrepresented populations by assessing and reporting equity-related data during feasibility studies.

Findings
Advantages of MCTs: Investigators highlighted streamlined study operations, remote data capture, and higher-quality, real-time data collection as key benefits. MCTs were also noted for their potential to reduce participant burden by enabling remote participation.
Challenges of MCTs: Investigators reported increased operational challenges, such as device setup, maintenance, and troubleshooting. They also noted time burdens for staff and uncertainties regarding data quality, including potential biases and technical malfunctions.
Support Needs: Investigators emphasized the need for technical support, comprehensive training for staff and participants, and adequate budgetary planning to address additional costs associated with MCTs.
Participant Considerations: While MCTs offer convenience and engagement opportunities for participants, challenges include the intrusiveness of data capture, technology adoption barriers, and potential negative impacts of real-time data access on participant behavior.
Recommendations: Investigators stressed the importance of collaborative relationships between sponsors and sites, user-friendly technology selection, and participant-centric trial designs.

Recommendations
Improve Training and Support: Sponsors should provide hands-on training for staff and participants, including troubleshooting support and device-specific materials.
Plan Budgets Appropriately: Include funds for device procurement, staff time, and technology management in trial budgets.
Enhance Technical Support: Sponsors should establish centralized technical support systems to address technology-related issues during trials.
Select Participant-Friendly Technologies: Prioritize devices that are intuitive, minimally intrusive, and suitable for the target population's needs.
Engage Stakeholders Early: Collaborate with investigators, participants, and sponsors during trial planning to align expectations and address potential challenges.

Regulatory Considerations
Data Security: Ensure data collected by mobile technologies comply with privacy and security regulations, and communicate these measures to IRBs.
Device Validation: Validate devices for the intended trial context to ensure reliability and minimize technical risks.
Participant Communication: Clearly inform participants about how their data will be used and provide transparency regarding data access.

Findings
Digital health technologies (DHTs) enable the creation of novel endpoints that can represent the patient experience more objectively and accurately than traditional measures.
Endpoints derived from DHTs may be more meaningful to patients, healthcare providers, and other stakeholders.
The CTTI pathway for developing novel endpoints is applicable across various chronic conditions, with specific case studies developed for Duchenne Muscular Dystrophy, Diabetes, Parkinson's Disease, and Heart Failure.

Recommendations
A systematic approach should be used to identify and develop key novel endpoints from digital health technologies.
Development should focus on creating measures that are meaningful to patients.
Stakeholders—including patients, regulators, and investigative site personnel—should be engaged early and often in the planning process.
Biostatisticians and data scientists should be involved in key decisions regarding protocol design, data collection, and analysis.
Novel endpoints should be incorporated as exploratory endpoints in existing clinical trials and observational studies to gather evidence

Regulatory Considerations
Developers are advised to engage with regulators like the FDA early and frequently when planning the development of a novel endpoint.
There are established processes for interacting with the FDA, and resources are available to guide developers through these interactions.
The principles of adaptive trial design are the same for studies using mobile technologies as they are for traditional clinical trials.

Findings
The term "clinically validated" is frequently used in marketing but lacks a clear, standardized meaning, leading to confusion. The rapid development of BioMeTs has outpaced the creation of systematic, evidence-based evaluation frameworks, creating a knowledge gap. Existing validation standards from software, hardware, and clinical development are often applied in silos and are not fully sufficient for modern BioMeTs. Evaluating a BioMeT requires assessing the entire "data supply chain," from the sensor hardware (verification) and data processing algorithms (analytical validation) to its performance against a meaningful clinical concept (clinical validation).

Recommendations
The digital medicine field should adopt the V3 (Verification, Analytical Validation, Clinical Validation) framework as a foundational evaluation standard for all BioMeTs to ensure they are fit-for-purpose. Technology manufacturers, clinical trial sponsors, and researchers should transparently report their V3 processes and results to overcome "black box" approaches and build a common evidence base. Technology manufacturers are primarily responsible for verification , while the entity developing the algorithm (e.g., manufacturer or sponsor) is responsible for analytical validation. The sponsor or clinical team using the BioMeT for a specific purpose is responsible for clinical validation in that context of use.

Regulatory Considerations
The V3 framework is designed to inform and align with the current regulatory landscape, although the regulatory pathway for a specific BioMeT depends on its intended use and marketing claims, not just its underlying technology. The 21st Century Cures Act and the concept of Software as a Medical Device (SaMD) have created new regulatory paradigms that decouple software from specific hardware. BioMeTs used to support drug development may follow a tool qualification pathway, while those marketed as standalone medical devices are subject to device clearance or approval processes. Stakeholders should engage with regulatory agencies early to determine appropriate validation approaches.