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.

Regulatory Considerations
The Premarket Notification (510(k)) database is a critical component of the FDA's regulatory framework for medical devices. Its primary function is to house information on devices that have been cleared through the 510(k) pathway, which is the most common route to market for medical devices in the U.S.

A 510(k) submission's central requirement is to demonstrate "substantial equivalence" to a legally marketed predicate device. This means the new device is as safe and effective as a device already on the market. Clearance of a 510(k) does not denote "approval" in the same way as a Premarket Approval (PMA) application but rather confirms that the device meets the necessary criteria for marketing.

The database provides transparency and serves as an essential resource for manufacturers to identify potential predicate devices for their own submissions. For healthcare providers, patients, and researchers, it offers a way to verify the regulatory status and clearance basis for a specific device.

Findings
The traditional medical device regulatory paradigm is not designed for the adaptive nature of AI/ML technologies, which can learn and change after they are on the market. A key benefit of AI/ML is its ability to improve performance by learning from real-world data, but this also presents a unique regulatory challenge. To ensure patient safety and device effectiveness, a new, flexible regulatory framework is required that can accommodate these iterative improvements. Transparency and robust monitoring are essential to manage the risks associated with evolving algorithms.

Recommendations
The FDA proposes a "Predetermined Change Control Plan" (PCCP) to be included in premarket submissions. This plan would specify the anticipated modifications to the device (the "what") and the methodology for implementing and validating those changes (the "how"). The development of "Good Machine Learning Practice" (GMLP) is encouraged to ensure that AI/ML algorithms are developed and validated using best practices. Manufacturers should implement robust real-world performance monitoring to ensure that their devices remain safe and effective after deployment.

Regulatory Considerations
The FDA is developing a new regulatory framework tailored to the unique aspects of AI/ML-based SaMD, which will leverage a TPLC approach. The agency has issued an "AI/ML SaMD Action Plan" that outlines its multi-pronged approach, including issuing draft guidance on PCCPs and promoting the harmonization of GMLP. The FDA is actively collaborating with stakeholders to foster innovation while ensuring patient safety. The agency maintains a public list of authorized AI/ML-enabled medical devices to enhance transparency.

Findings
In a progressive neurodegenerative illness like Alzheimer's disease, slowing the rate of disease progression is considered a clinically meaningful outcome for patients and their caregivers.
The assessment of what constitutes a clinical benefit is highly dependent on the specific stage of AD being studied, the drug's mechanism of action, and the symptoms present in that patient population.
Direct input from patients and caregivers is critical for understanding disease burden and defining treatment benefits that are truly meaningful from their perspective.
The interpretation of score changes on Clinical Outcome Assessments (COAs) requires full context; an absolute point difference must be considered relative to the study's duration, the expected placebo decline, and the specific disease stage.
Evidence from biomarkers that show an effect on underlying disease pathology provides additional support and increases the persuasiveness of the changes observed on clinical endpoints.

Recommendations
Drug developers should implement multiple "fit-for-purpose" COAs that use different reporters (e.g., clinicians, observers) and methods to generate broad and diverse evidence of a drug's clinical benefit.
Sponsors should utilize both qualitative and quantitative methodologies to explore clinical meaningfulness, including assessing "meaningful within-patient change" throughout the development process.
Developers are encouraged to create and validate new COAs and leverage innovative approaches, such as digital health technologies, to better capture concepts that are relevant to patients, especially in the earliest stages of AD.
Throughout the drug development lifecycle, stakeholders should systematically collect and incorporate patient experience data to ensure that the perspectives, needs, and priorities of patients are meaningfully captured.

Regulatory Considerations
For a drug to gain approval, it must meet the regulatory standard of "substantial evidence of effectiveness," which is typically derived from adequate and well-controlled investigations designed to minimize bias.
The FDA defines clinical benefit as a clinically meaningful effect of a drug on how an individual feels, functions, or survives.
An assessment of clinical benefit is not limited to the primary endpoint; the consistency of findings across multiple endpoints (primary and secondary) is a key consideration during regulatory review.
The accelerated approval pathway may be used for serious conditions with unmet needs based on a surrogate endpoint, but traditional approval requires verification of clinical benefit in confirmatory trials.
The FDA's evaluation includes a benefit-risk analysis, which considers the severity of the disease and the availability of alternative therapies, recognizing that patients and physicians may accept greater risks for life-threatening illnesses.

Findings
Digital endpoints must not only support regulatory approval but also provide evidence that meets payer expectations for reimbursement and value-based care. The lack of early engagement with payers and health technology assessment (HTA) agencies is a key barrier to the adoption of digital clinical measures. Digital measures can enhance value-based care models by capturing patient-centered outcomes, reducing healthcare costs, and improving early disease detection. The scalability and generalizability of digital endpoints remain challenges, particularly for diverse populations and real-world healthcare settings. Technical and systematic barriers—such as data heterogeneity, stakeholder knowledge gaps, and inconsistent regulatory-payer alignment—are slowing the adoption of digital endpoint data for reimbursement decisions.

Recommendations
Pharma and medical product developers should engage early with payers and regulators to ensure digital endpoints align with reimbursement expectations. Payers and HTA bodies should establish clear evidence thresholds for digital endpoint validation, ensuring consistency in market access decisions. Digital endpoints should be validated against health-related quality of life (HRQoL) measures and patient-reported outcomes (PROs) to demonstrate clinical relevance. Real-world evidence (RWE) should be incorporated into clinical trials alongside digital endpoints to strengthen reimbursement applications. Stakeholders should prioritize scalable, patient-centered digital measures that capture disease progression over time and across different care settings.

Regulatory Considerations
Integrated Evidence Plans (IEPs) should be developed early to align digital endpoint evidence with regulatory and payer requirements. Digital endpoints should be assessed through multi-stakeholder collaboration, ensuring validation across pharmaceutical, regulatory, and reimbursement frameworks. Payers and regulators should work together to create aligned pathways for digital measure acceptance, reducing delays in market access. Data security, privacy, and interoperability must be addressed to support regulatory approval and patient trust in digital health solutions. The industry should leverage international regulatory-payer collaboration models, such as the HTA-EMA partnership and the FDA Payor Communication Task Force, to accelerate global digital endpoint adoption.

Findings
Patient experience data provides critical context for regulatory review by illuminating disease burden, unmet medical needs, and the aspects of a condition that matter most to patients.
A systematic approach is necessary to ensure patient experience data is robust enough for regulatory consideration, moving beyond anecdotal evidence to scientifically rigorous data collection.
Early engagement between sponsors and the FDA is a key factor for successfully incorporating patient perspectives into a drug development program.
The value of patient-reported outcomes (PROs) and other clinical outcome assessments (COAs) is highly context-dependent, varying significantly across different diseases and patient populations.

Recommendations
Drug sponsors should leverage the FDA's meeting process to discuss their strategies for collecting and submitting patient experience data early in the development lifecycle.
Sponsors should utilize the repository of meeting reports as a learning resource to understand best practices and common challenges in patient-focused drug development for specific conditions.
Patient advocacy groups should actively participate in these discussions to ensure the full spectrum of patient experiences is captured and communicated to both regulators and developers.
Researchers should develop and validate novel tools and methodologies for capturing and analyzing patient experience data that are meaningful for both clinical and regulatory purposes.

Regulatory Considerations
Patient experience data is a key component of the benefit-risk assessment, providing evidence that can inform regulatory decisions regarding a drug's approval and labeling.
The FDA's review of patient experience data is guided by a commitment to patient-focused drug development, as mandated by the 21st Century Cures Act and supported by user fee agreements like PDUFA.
The scientific rigor of data collection and analysis is paramount; for patient experience data to be influential, it must meet high standards of validity and reliability.
Transparency is a core principle, and the publication of these meeting reports is intended to provide clear examples of how patient input can be effectively integrated into regulatory submissions.

Findings
Cybersecurity is an integral part of medical device safety and effectiveness, and manufacturers are responsible for addressing it throughout the entire device lifecycle. The FDA considers a device's cybersecurity as part of its benefit-risk assessment for both premarket and postmarket activities. A lack of robust cybersecurity controls can lead to patient harm, compromised device functionality, and breaches of data privacy. The dynamic nature of cybersecurity threats requires ongoing monitoring, risk management, and timely implementation of mitigation strategies.

Recommendations
Manufacturers should build cybersecurity into devices from the design phase ("secure by design") and conduct a thorough risk analysis to identify and mitigate potential vulnerabilities. Premarket submissions should include comprehensive documentation of the device's cybersecurity controls, a risk management plan, and a plan for postmarket surveillance and response. Manufacturers should establish a robust postmarket surveillance program to monitor for, identify, and address new cybersecurity threats in a timely manner. Clear and informative labeling is essential to help users understand and manage cybersecurity risks.

Regulatory Considerations
The FDA has the authority to take action against devices with inadequate cybersecurity that pose a risk to public health. The agency recommends that manufacturers use the Q-submission process to discuss specific cybersecurity questions related to their device submissions. Compliance with recognized standards and best practices for cybersecurity is strongly encouraged. Manufacturers must report certain cybersecurity incidents to the FDA as part of their postmarket reporting requirements. The FDA collaborates with other government agencies and stakeholders to promote a coordinated approach to medical device cybersecurity.

Findings
The DHCoE works to strategically advance science and evidence for digital health technologies (DHTs).
Key areas of focus include Artificial Intelligence / Machine Learning (AI/ML) in Software as a Medical Device (SaMD), Cybersecurity, Augmented Reality (AR) and Virtual Reality (VR), and Wireless Medical Devices.
The DHCoE develops and publishes Guidances with Digital Health Content and maintains a Digital Health Policy Navigator to provide clarity on regulatory policies.
Digital health technologies are acknowledged as having the potential to facilitate decentralized clinical trial activities and allow for continuous or frequent measurements of clinical features remotely.
Programs and initiatives include the Software Precertification (Pre-Cert) Pilot Program, the Regulatory Accelerator, and the Diagnostic Data Program.
The center is also involved in international harmonization on device regulatory policy and standards.

Recommendations
The DHCoE recommends that stakeholders, including sponsors and DHT manufacturers, engage with the agency early to discuss the use of DHTs in drug development or for decentralized clinical trials (DCTs).
Stakeholders are encouraged to use the Digital Health Policy Navigator tool to assess whether a particular software function meets the device definition and is the focus of FDA oversight.
The DHCoE emphasizes the need for a patient-centered approach for AI/ML-enabled devices that considers issues like usability, equity, trust, and accountability, and promotes transparency.

Regulatory Considerations
The DHCoE's work includes innovating the regulatory paradigm for digital health, moving towards models that may include shifting scrutiny from the pre-market to the post-market phase and focusing on the capability of firms (Software Pre-Cert Pilot Program).
The FDA has committed, as part of PDUFA VII, to activities such as publishing a Framework for the Use of DHTs in Drug and Biological Product Development and establishing a DHT Steering Committee.
The center provides information to help determine the regulatory status of various digital health products, such as Software as a medical device (SaMD), mobile medical applications (MMA), and General Wellness products.
Submissions for products with device software functions must include recommended documentation for the FDA's evaluation of safety and effectiveness.
For questions regarding upcoming premarket submissions, stakeholders are directed to contact the appropriate review division through a Q-submission.

Findings
Cytokine Release Syndrome (CRS) is a common and potentially life-threatening adverse event of immunotherapies, particularly in Oncology, complicating patient care and increasing healthcare costs. Standard-of-care inpatient monitoring for CRS is manual, intermittent, costly, and restrictive, providing an incomplete view of the syndrome’s development and progression. The use of Digital Health Technologies (DHTs) for continuous, remote monitoring of vital signs (like heart rate, respiratory rate, skin temperature, SpO2, and activity) can capture early indicators of CRS up to two hours earlier than standard episodic monitoring. This ability to collect multivariate continuous data is valuable for informing robust model development for CRS risk prediction.

Recommendations
Investigators should deploy DHTs available today to monitor vital signs and symptoms currently observed in the hospital setting, but in an outpatient or home environment. The goal is to develop Early Warning Products that assess the probability of developing CRS, providing clinical decision support. Product developers should follow a strategic roadmap that outlines milestones for building products that are clinically relevant and commercially viable. Researchers should use a common set of digital clinical measures to gather high-quality datasets and ensure comparability across studies to build more robust predictive models. Predictive algorithms should be built on a robust reference measure for analytical validation and be clinically validated with sufficient data.

Regulatory Considerations
The resources are designed to help developers build products that are clinically appropriate, regulatory-acceptable, and commercially viable. Future regulatory submissions for CRS de-risking products will benefit from aligning with this industry-wide dialogue that is being built in collaboration with the FDA. Developing a robust CRS safety biomarker could enhance the safety profile of clinical trials, increase trial access, and streamline regulatory decision-making, possibly through a qualification pathway. Products that aim for a higher level of autonomy, such as a Diagnostic that redefines current CRS grading classes, may require very high clinical evidence and likely stringent regulatory review.

Key Principles (Findings)
The central principle of the DDT Qualification Programs is to create a formal pathway for the FDA to conclude that a specific tool is well-suited for a particular Context of Use (COU) in drug development. A key finding, as reflected in the program's design, is that qualification de-risks drug development by allowing a tool to be used in any regulatory submission for its qualified COU without needing to be re-validated each time. The program is designed to foster stakeholder collaboration, encouraging the development of tools that can benefit the entire research community, thereby reducing the burden on individual sponsors.

Program Activities (Recommendations)
The structure of the DDT programs serves as a series of recommendations for tool developers:
Engage Early and Collaboratively: The programs are designed to provide a framework for early and ongoing scientific collaboration with the FDA to facilitate the development of new tools.
Follow a Staged Process: Developers are guided through a multi-stage process, typically involving a Letter of Intent, a Qualification Plan, and a Full Qualification Package, to systematically build the evidence needed for qualification.
Seek Public Qualification: The ultimate recommendation is to achieve public qualification for a DDT, which makes the tool available for broad use and integrates it into the regulatory review process, expediting future drug development.

Regulatory Considerations
The DDT Qualification Programs are a formal regulatory framework established under the 21st Century Cures Act. A "qualified" DDT has a specific regulatory status; it can be relied upon to have a specific interpretation and application in drug development and regulatory review for its stated Context of Use (COU). This qualification is publicly available and allows the tool to be included in Investigational New Drug (IND), New Drug Application (NDA), or Biologics License Application (BLA) submissions without the FDA needing to reconsider its suitability. This creates a more efficient and predictable regulatory compliance pathway for sponsors who use the qualified tool.

Findings
The database provides a transparent and accessible way for the public to track the progress of various Drug Development Tools (DDTs) through the FDA's qualification pipeline. This includes biomarkers, clinical outcome assessments, and animal models. The information available, such as submission status and supporting documentation, offers insight into the types of tools being developed and the evidence required for their qualification. The platform reveals that a wide range of tools are in development across numerous therapeutic areas, highlighting active areas of research and innovation in drug development.

Recommendations
Stakeholders in the drug development ecosystem are encouraged to utilize this database to inform their research and development strategies. By reviewing the status of existing DDT submissions, sponsors can identify opportunities for collaboration, avoid duplicative efforts, and better understand the evidentiary requirements for tool qualification. Prospective tool developers should use the database to learn from successful submissions and to align their own development plans with FDA expectations.

Regulatory Considerations
This database is a direct implementation of the transparency provisions of the 21st Century Cures Act. The public availability of this information is intended to foster trust and collaboration in the DDT qualification process. By providing a clear view of the regulatory journey of various tools, the FDA aims to standardize the qualification process and encourage the development and use of novel, validated tools in drug development. Users of the database should be aware that the information reflects the status of a DDT at a particular point in time and that the qualification process is an iterative one.

Findings
Traditional, site-based clinical trials often create significant burdens for participants, which can hinder recruitment, retention, and the enrollment of diverse populations.
A lack of early and sustained patient engagement in trial design can lead to research protocols that are misaligned with patient needs and endpoints that are not meaningful to them.
The underrepresentation of diverse racial, ethnic, and other demographic groups in clinical trials limits the generalizability of study results and can perpetuate health disparities.
Emerging digital health technologies (DHTs) and real-world data (RWD) present significant opportunities to make clinical trials more efficient, patient-centric, and inclusive, but their adoption has been inconsistent.

Recommendations
Sponsors and research teams should engage patients and patient advocacy groups as active partners throughout the entire clinical trial lifecycle, from design to dissemination.
Decentralized clinical trial (DCT) elements should be incorporated to reduce patient burden, improve access for diverse populations, and enhance the quality of data collection.
Trial sponsors must develop and implement proactive strategies to enhance the diversity and inclusion of trial participants to ensure results are applicable to all patient populations.
Novel endpoints derived from DHTs should be developed and validated to capture more objective, real-world measures of how patients feel, function, and survive.
Multi-stakeholder collaboration between industry, academia, patient groups, and regulators is essential to address systemic challenges and improve the clinical trial enterprise.

Regulatory Considerations
Early and frequent communication with regulators, such as the FDA, is critical when implementing novel approaches like DCTs or developing new digital endpoints for pivotal trials.
Regulatory frameworks must support the use of innovative technologies and trial models while ensuring data integrity, reliability, and patient safety.
The use of a single Institutional Review Board (IRB) for multi-site trials is a key regulatory-supported mechanism for streamlining ethics review and increasing trial efficiency.
When using DHTs and decentralized methods, robust plans for data quality, privacy, and security are necessary to meet regulatory standards for trial data submission.