Zero-Visit Efficacy is transforming how sponsors measure treatment effects by using SaMD-driven virtual biomarkers to replace traditional in-clinic endpoints. In this article, explore the validation pathways, regulatory considerations, and trial designs that enable remote endpoints without sacrificing scientific rigor, participant equity, or safety.
What are SaMD-driven virtual biomarkers and why they matter
Software as a Medical Device (SaMD) can derive continuous, passive, or active virtual biomarkers from smartphones, wearables, and home sensors — for example, gait variability, speech markers, or composite activity scores. These measures can capture real-world performance more frequently and with less burden than episodic clinic visits, enabling true zero-visit efficacy assessments in many therapeutic areas.
Key advantages
- Higher-resolution data: frequent or continuous sampling reduces measurement noise and short-term variability.
- Lower participant burden: fewer site visits improves retention and generalizability.
- Cost efficiency: remote assessments cut travel, staffing, and site overhead.
- Real-world relevance: endpoints reflect daily function rather than artificial clinic performance.
Validation pathway: a staged approach to credibility
Regulators and clinicians require transparent evidence that a virtual biomarker reliably measures what it claims and links meaningfully to clinical outcomes. A staged validation framework — commonly expressed as verification, analytical validation, and clinical validation — offers a clear roadmap.
1. Verification
- Confirm software correctness and reproducibility across platforms, OS versions, and device models.
- Document unit testing, version control, and continuous integration practices for SaMD.
2. Analytical validation
- Quantify accuracy, precision, limits of detection, and robustness to real-world noise (different lighting, motion artifacts, signal dropouts).
- Use bench datasets and controlled comparator devices to estimate measurement error and bias.
3. Clinical validation
- Demonstrate that the virtual biomarker is associated with clinically meaningful outcomes (concurrent and predictive validity).
- Prefer prospectively designed bridging studies or embedded sub-studies in clinical trials to show concordance with established COAs or clinical endpoints.
Regulatory acceptance: pragmatic engagement and evidence strategies
Regulatory bodies are increasingly receptive to digital endpoints but expect rigorous, pre-specified evidence and risk mitigation. Early engagement through pre-submission or scientific advice meetings is critical to align on intended use, validation endpoints, and data standards.
- Define the SaMD’s intended use and risk classification up front and propose a validation package that includes technical, analytical, and clinical evidence.
- Plan for post-market surveillance and real-world performance monitoring to meet regulators’ expectations about ongoing safety and effectiveness.
- Provide transparent algorithm descriptions, data provenance, and reproducible analysis pipelines; when proprietary models are used, offer auditors’ access to validation results or independent third-party testing.
Trial designs that replace in-clinic measures
Replacing clinic endpoints requires careful trial design to preserve interpretability and statistical validity. Several approaches work depending on the therapeutic question and regulatory comfort level.
Design options
- Fully decentralized randomized controlled trials (RCTs): primary endpoint measured remotely by the SaMD.
- Hybrid trials: retain a smaller number of in-clinic assessments for anchoring while using remote biomarkers as primary or co-primary endpoints.
- Embedded validation cohorts: within a larger trial, a sub-cohort performs simultaneous clinic and remote measures to enable bridging analyses.
Statistical considerations
- Decide whether to pursue superiority or non-inferiority frameworks when replacing established endpoints, and pre-specify margins and estimands.
- Adjust sample size for increased measurement frequency and potential intra-subject correlation; continuous monitoring may increase power but requires appropriate alpha control.
- Plan robust missing-data strategies and sensitivity analyses for sporadic device non-use or signal loss.
Safeguarding equity, privacy, and safety
Zero-visit trials can widen access but also risk exacerbating disparities if not intentionally designed. Ethical deployment requires proactive measures to ensure representativeness and protect participants.
- Address the digital divide: provide devices, connectivity, or alternative assessment pathways for participants with limited access.
- Validate algorithms across diverse demographics and clinical subgroups to detect differential performance and remove biased features.
- Ensure privacy and security: encrypt data in transit and at rest, define data minimization, and articulate retention and sharing policies in consent forms.
- Maintain human oversight for safety-critical decisions; SaMD should augment, not fully replace, clinical judgment when risk is high.
Operational and analytical best practices
Successful zero-visit studies combine technical rigor with participant-centered operations.
- Lock or version-control algorithms pre-specified as primary endpoint scorers; if adaptive models are needed, predefine adaptation rules and validation steps.
- Use centralized data monitoring and automated quality metrics to detect sensor drift, non-compliance, or anomalous signals early.
- Publish validation protocols and statistical analysis plans before unblinding to increase transparency and reproducibility.
- Partner with diverse clinical sites, patient groups, and technology vendors early to streamline recruitment, onboarding, and technical support.
Case examples and practical lessons
Several programs have shown that virtual biomarkers can replicate or better capture clinically meaningful signals when properly validated. Common lessons include the importance of anchoring remote measures to clinical outcomes, pre-specifying handling of device failures, and ensuring diverse validation cohorts. Sponsors that treat SaMD validation as a parallel scientific program — not just a technical add-on — achieve faster regulator acceptance and higher confidence from clinicians and patients.
Conclusion: Zero-Visit Efficacy is now feasible when SaMD-driven virtual biomarkers are validated through structured verification, analytical and clinical validation; integrated into thoughtfully designed trials; and deployed with safeguards for equity, privacy, and safety. With early regulatory engagement and rigorous operational practices, remote endpoints can accelerate trials and make outcomes more representative of real life.
Ready to explore a zero-visit endpoint strategy for your next trial? Contact a digital clinical validation specialist to map a tailored pathway.
