Agentic AI for Clinical Trials

Indication

Decentralized clinical trials (DCT) platform

Data source

Fleet of connected devices (CGMs, smartwatches, phones) and apps

Partnership availability

Open to sponsors, CROs and clinical sites for pilot studies

The platform

NeuTigers is building a multi-agent AI architecture for secure, intelligent and scalable decentralized clinical trials (DCTs). Cooperating AI agents take on the repetitive operational workload of a study end to end, while investigators keep the decisions:

1. Monitor clinical-trial participants — continuous multi-sensor data (ECG, PPG, activity, sleep, blood pressure, SpO2) from the participant's smartwatch and companion app, encrypted on upload.
2. Validate sensor files — a validation agent checks every incoming file against per-sensor rules; files pass or are rejected and logged.
3. Extract structured features — a feature-extraction agent computes ECG quality, heart-rate variability and other clinical features.
4. Local medical LLM interpretation — a medical LLM agent, hosted on-premises or in a private cloud, produces clinical interpretation, risk assessment and insights; no patient data leaves the host.
5. Surface findings and alerts — a study portal and dashboards for study teams, with email alerts on risk escalation.
6. Nightly longitudinal health summary — a summary-generation agent runs every night over all validated data and features, so a per-patient summary (trends and metrics, risk evolution, clinical insights, data-quality overview) is available to clinicians and study teams the next morning.

Validated data is stored in an encrypted secure data lake, with audit logs, access control and encryption throughout — compliant with HIPAA and GDPR.

Proven operational foundation

The platform is grounded in operational knowhow NeuTigers built running its own wearable-based studies. The SweetDeep™ study execution process illustrates it concretely:

• Visit 1 (half day) — informed consent, inclusion/exclusion screening, CGM installation, eCRF entry, and participant enrollment, training and instruction.
• Free-living data collection (6 full days) — participants live normally while wearing their devices, with daily check-ins on device wear and data compliance (BIA, ECG, blood pressure, meals, alcohol) and green/yellow/red data confirmation before sensor and questionnaire data upload.
• Visit 2 (half day) — CGM removal, additional biometrics, and biological testing for disease labelling.

Behind that process sits a full DCT operating capability:

• International hospital-clinic networks across 4 continents, with partnerships with major KOLs and principal investigators.
• HIPAA/GDPR-compliant cloud infrastructure for security and privacy, with real-time data monitoring tools for quality and compliance.
• Large cohorts of more than 2,000 participants.
• Management of a fleet of devices — CGMs, smartwatches, phones — and their apps.
• Coordination of clinical and engineering staff: MDs, nurses, DevOps and data science.

Current status

The multi-agent DCT platform is in development, built directly on this operational knowhow and on NeuTigers' Princeton-origin research in subject-efficient study design. This status describes the program's development stage; it does not imply regulatory clearance, approval or diagnostic status in any jurisdiction.

Collaboration need

We are looking for study sponsors, CROs and clinical sites interested in piloting secure, subject-efficient, decentralized study designs. Discuss this program with us.

Evidence

• SCouT — time- and subject-efficient clinical trials with the statistical power of resource-intensive designs (Princeton-origin research)
• SweetDeep decentralized clinical trial with AP-HP — real-world data collected in real-world conditions (arXiv publication, 2026)

Program status reflects the stage stated above; it does not imply regulatory clearance, diagnostic availability, or commercial deployment unless explicitly stated.

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