Framework for Oversight of Digital Biomarkers in Clinical Trials

1. Introduction

Digital biomarkers are measurable physiological, behavioural, or biological indicators collected through digital technologies such as smartwatches, wearable sensors, mobile applications, smartphones, and connected medical devices. In clinical trials, they help researchers monitor patients’ health, disease progression, treatment effectiveness, and safety in real time.

Examples include heart rate, sleep patterns, gait speed, tremors, physical activity, and changes in voice that may indicate neurological disorders. Since digital biomarkers can influence clinical decisions and regulatory approval, their collection and interpretation require a robust oversight framework.

The framework aims to ensure scientific validity, patient safety, informed consent, data privacy, algorithmic reliability, and regulatory accountability.

2. Legal and Regulatory Framework

Oversight involves several interconnected legal and regulatory requirements:

Informed consent: Participants must understand what data will be collected, how it will be used, and whether continuous monitoring is involved.

Scientific validation: Digital biomarkers must demonstrate reliability, accuracy, and clinical relevance.

Data protection: Personal and health information must be protected against unauthorized access and misuse.

Device regulation: Wearables and software performing medical functions may be subject to medical-device requirements.

Research ethics: Institutional ethics committees must evaluate risks, participant rights, and the proportionality of data collection.

In India, relevant legislation includes the Digital Personal Data Protection Act, 2023, subject to its applicable commencement provisions, the New Drugs and Clinical Trials Rules, 2019, and applicable medical-device regulations. Internationally, the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the European Union's General Data Protection Regulation (GDPR) provide important regulatory reference points.

3. Essential Elements of the Oversight Framework

A. Scientific Validation and Reliability

Researchers must establish that a digital biomarker measures what it claims to measure. Validation should include analytical validation, clinical validation, and evaluation of its intended use.

For example, a smartwatch intended to measure tremor severity in Parkinson's disease should be tested against accepted clinical assessments. Researchers should evaluate measurement errors, device differences, missing data, and performance across different demographic groups.

B. Informed Consent and Participant Protection

Consent procedures should explain the purpose of monitoring, the frequency of data collection, potential risks, and the circumstances in which researchers may access participants' information.

Participants should also be informed about incidental findings, withdrawal procedures, data retention, and the limitations of automated alerts. Where continuous monitoring is used, consent should address the privacy implications of collecting data outside conventional clinical visits.

C. Data Privacy and Cybersecurity

Digital biomarkers can reveal sensitive information about sleep, movement, mental health, location, and daily routines. Therefore, sponsors should implement encryption, access controls, pseudonymisation, secure storage, audit logs, and retention limits.

Data-sharing agreements should specify responsibilities among sponsors, investigators, device manufacturers, and technology vendors. Cross-border transfers must comply with applicable legal requirements.

D. Algorithmic Transparency and Bias

Algorithms used to calculate digital biomarkers must be assessed for accuracy, reproducibility, and bias. Performance may vary according to age, skin characteristics, disability, disease severity, or device model.

Sponsors should document algorithm versions, software updates, training data limitations, and validation results. Material changes during a trial should undergo change-control review to determine whether revalidation or regulatory notification is necessary.

E. Continuous Monitoring and Safety Reporting

Digital systems may identify abnormal heart rhythms, reduced mobility, or sudden changes in physiological measurements. Trial protocols should define alert thresholds, responsible personnel, escalation timelines, and procedures for handling device failures.

Investigators must distinguish research measurements from clinically actionable findings and explain whether participants receive real-time monitoring. Serious adverse events must be handled according to applicable clinical-trial reporting requirements.

4. Important Case Laws and Their Relevance

Digital biomarkers are a relatively new regulatory field, and there is no single universally controlling judgment establishing a complete legal framework for them. Nevertheless, several judicial decisions provide important principles.

1. Montgomery v. Lanarkshire Health Board (2015)

The UK Supreme Court held that medical professionals must disclose material risks and reasonable alternatives relevant to a patient's decision.

Relevance: The principle supports meaningful disclosure when participants are asked to accept continuous digital monitoring, data-sharing risks, or automated decision-making. The judgment concerned clinical consent rather than digital biomarkers specifically.

2. Justice K.S. Puttaswamy (Retd.) v. Union of India (2017)

The Supreme Court of India recognised privacy as a fundamental right under Article 21 and the Constitution.

Relevance: Digital biomarker systems may collect intimate health and behavioural information. The constitutional principles of privacy, autonomy, and proportionality support safeguards against excessive collection, unauthorized disclosure, and unjustified surveillance. Their precise application depends on the actors and circumstances involved.

3. Samira Kohli v. Dr. Prabha Manchanda (2008)

The Supreme Court of India emphasised the requirement of valid consent for medical treatment and explained that consent to one procedure does not automatically authorize a substantially different procedure.

Relevance: Researchers should obtain consent that specifically covers the nature and scope of digital monitoring rather than relying on vague authorization for clinical research. The case concerned medical treatment, not digital-data processing.

4. Google Spain SL v. AEPD and Mario Costeja González (2014)

The Court of Justice of the European Union addressed search-engine responsibilities and the protection of personal data in relation to information appearing online.

Relevance: The decision illustrates the importance of controlling the processing and accessibility of personal information. In digital-biomarker trials, sponsors should establish clear rules for data access, disclosure, retention, and lawful secondary use. The case was not a clinical-trial judgment.

5. S. and Marper v. United Kingdom (2008)

The European Court of Human Rights held that the blanket retention of fingerprints and DNA profiles from persons who had not been convicted violated Article 8 of the European Convention on Human Rights.

Relevance: The judgment highlights the risks of disproportionate retention of sensitive personal information. Trial sponsors should justify retention periods, restrict secondary use, and establish secure deletion procedures consistent with legal and scientific obligations.

5. Institutional Oversight and Accountability

An effective framework should assign clear responsibilities to each stakeholder.

Sponsors: Validate devices, maintain risk-management systems, oversee vendors, and document data governance.

Investigators: Monitor participant safety, assess clinically significant findings, and maintain trial records.

Ethics committees: Review consent, privacy risks, recruitment practices, and proposed changes to monitoring.

Regulators: Assess compliance with clinical-trial, medical-device, and data-protection requirements.

Independent auditors: Review data integrity, algorithm changes, cybersecurity controls, and protocol compliance.

Periodic audits should assess data completeness, device accuracy, algorithm drift, participant complaints, and adverse events. Corrective action should be documented and implemented whenever material risks are identified.

6. Conclusion

Oversight of digital biomarkers in clinical trials requires an integrated framework combining scientific validation, informed consent, privacy protection, cybersecurity, algorithmic accountability, and continuous safety monitoring. Judicial decisions such as Puttaswamy, Samira Kohli, and Montgomery offer important principles for protecting autonomy and privacy, although none directly establishes a comprehensive digital-biomarker regime.

Ultimately, digital biomarkers should be used in clinical trials only when their measurement is scientifically justified, their risks are proportionately controlled, and participants' rights are protected throughout the research process. This approach strengthens public trust, improves the reliability of trial results, and supports responsible innovation in digital medicine.