FDA Real-Time Clinical Trials: What Medical Device Manufacturers Need to Know About the 2026 Pilot

The FDA's Real-Time Clinical Trial Initiative

On April 28, 2026, the FDA announced a groundbreaking initiative to implement real-time clinical trials — allowing the agency to monitor clinical study data as it is generated rather than waiting for periodic submissions. FDA Commissioner Marty Makary called it "the first ever real-time clinical trial" and framed it as a challenge to the assumption that it takes 10 to 12 years for a new drug to come to market.

While the initial pilot focuses on pharmaceutical trials with AstraZeneca and Amgen, the implications for medical device clinical investigations are significant. The technology platform, regulatory framework, and data infrastructure being built now will extend to device trials. FDA Chief AI Officer Jeremy Walsh estimated the approach could reduce "20, 30, 40% of overall clinical trial time."

This guide explains what the initiative is, how it works, what it means for medical device manufacturers, and how to prepare.

Why Real-Time Trials Matter: The Dead Time Problem

According to Commissioner Makary, approximately 45% of the drug development process — the period between initiation of a Phase 1 trial and submission of a regulatory application — is "dead time." During this period, no active research takes place. Instead, investigators and staff complete paperwork and perform administrative tasks that are not always necessary.

For medical devices, the clinical investigation timeline is typically shorter but still suffers from the same structural inefficiency:

• Site-to-sponsor data flow: Clinical sites collect data, sponsors analyze it, then submit it to FDA — a serial process with built-in delays
• Protocol amendments: Changes require sequential review cycles between sponsors, sites, and regulators
• Safety signal detection: Adverse events are reported retrospectively, not in near-real time
• End-of-study submissions: FDA receives a complete data package only after the trial concludes, delaying review

Real-time trials address each of these bottlenecks by enabling continuous data flow from clinical sites to sponsors to the FDA simultaneously.

How the Real-Time Trial Platform Works

The Technology: Paradigm Health

The FDA is collaborating with Paradigm Health, whose AI-powered platform automates data collection and analysis. The platform enables:

• Direct EHR integration: Clinical data is pulled from electronic health records at trial sites
• Cloud-based data sharing: FDA reviewers can access pre-specified efficacy and safety endpoints in near-real time through a secure cloud environment
• AI-powered signal detection: Automated analysis flags safety signals and efficacy trends as data accumulates
• Continuous monitoring: Sponsors and regulators maintain a continuous view of safety and efficacy throughout the trial

Kent Thoelke, founder and CEO of Paradigm Health, described the impact: "Clinical trial data can be analysed for key signals in near real time and shared with trial sponsors and the FDA in days, rather than months."

The First Two Trials

The initial proof-of-concept involves two pharmaceutical trials:

These proof-of-concept studies will serve as the foundational groundwork for a broader pilot program.

The Broader Pilot Program

The FDA has released a Request for Information (RFI) seeking public input on the pilot program design. Key details:

• Comment deadline: May 29, 2026
• Selection criteria: To be outlined in July 2026
• Participant selection: August 2026
• Scope: AI-enabled technologies to improve efficiency, speed, and quality of decision-making in early-phase clinical trials

The RFI specifically asks about:

• Using AI for safety monitoring in clinical trials
• AI-assisted medication dose selection
• Identifying safety signals in real time
• Improving patient recruitment (a common bottleneck)
• Metrics and criteria to measure program success

Implications for Medical Device Clinical Investigations

While the initial pilot focuses on pharmaceutical trials, the FDA has been explicit that real-time trials are a step toward its "ultimate goal" of facilitating continuous trials across all product types. For medical device manufacturers, this has several implications:

Device Clinical Investigations Will Follow

The FDA's Center for Devices and Radiological Health (CDRH) is part of the same modernization initiative. The infrastructure being built — cloud-based data sharing, AI-powered signal detection, real-time regulatory access — will extend to device trials. Device manufacturers who understand the framework now will be better positioned to participate in future device-specific pilots.

IDE Studies Could Be Accelerated

For devices requiring Investigational Device Exemption (IDE) studies, real-time data monitoring could:

• Reduce time to market by eliminating the gap between study completion and data submission
• Enable adaptive trial designs where endpoints or sample sizes are modified based on accumulating data
• Facilitate earlier safety signal detection — potentially preventing adverse events rather than reporting them after the fact
• Streamline de novo and PMA submissions by providing FDA reviewers with continuous data access

Early Feasibility Studies (EFS) Stand to Benefit Most

Early feasibility studies — which allow sponsors to evaluate device safety and effectiveness in a small number of subjects early in development — are the medical device equivalent of the Phase 1/2 trials in the pharmaceutical pilot. These studies are characterized by:

• Small patient populations
• High uncertainty
• Iterative device modifications
• Close sponsor-FDA interaction

Real-time data sharing is ideally suited for EFS because it enables the kind of continuous dialogue between sponsors and FDA reviewers that iterative device development requires.

Software and AI-Enabled Device Trials

For SaMD and AI-enabled medical devices, real-time trials address a fundamental challenge: the algorithm may evolve during the study. Traditional clinical trial frameworks assume a static investigational product. Real-time monitoring allows:

• Continuous performance tracking of adaptive algorithms
• Near-real-time bias detection across demographic subgroups
• Immediate flagging of performance degradation or drift
• Faster evidence generation for PCCP (Predetermined Change Control Plan) validation

A 2026 analysis in Nature Medicine highlighted this tension: the very feature that makes AI valuable in clinical trials — its capacity to improve with new data — is the feature that makes it most dangerous to trial validity. Real-time monitoring provides the infrastructure to manage this risk.

What Medical Device Sponsors Should Do Now

1. Respond to the RFI (Deadline: May 29, 2026)

The FDA is actively seeking input on the pilot program design. Device manufacturers should submit comments addressing:

• How real-time data monitoring could work for device clinical investigations
• Specific challenges for device trials (e.g., endpoint variability, sham-controlled designs, learning curve effects)
• AI applications in device trials (e.g., automated image analysis for endpoint adjudication, predictive modeling for patient recruitment)
• Metrics for success specific to device development timelines

2. Assess Your Clinical Data Infrastructure

Real-time trials require digital-ready clinical data systems. Evaluate your current infrastructure:

• EHR integration: Can your clinical sites export structured data in real time?
• Electronic data capture (EDC): Is your EDC system capable of continuous data streaming, or does it rely on batch uploads?
• Cloud readiness: Do you have secure cloud infrastructure that could support FDA data access?
• Data standardization: Are your endpoints, case report forms, and adverse event coding (MEDDEV/MedDRA) standardized across sites?

3. Design Trials for Continuous Review

Traditional device trials are designed for end-of-study analysis. Real-time trials require a different approach:

• Pre-specify interim analyses with statistical boundaries for early stopping
• Define real-time endpoints that can be meaningfully assessed as data accumulates (not just final composite endpoints)
• Build adaptive elements into protocols that allow modifications based on accumulating evidence
• Plan for continuous safety monitoring rather than periodic DSMB reviews

4. Prepare for Dual Data Submission

Initially, the FDA will collect trial data through both the traditional regulatory process and real-time monitoring. Sponsors should be prepared to maintain parallel data streams:

• Standard submissions (IDE reports, 510(k) or PMA modules) continue as normal
• Real-time data is an additional layer, not a replacement (at least during the pilot phase)
• At pilot conclusion, the FDA will assess what worked and how to integrate the approach permanently

5. Engage CDRH Early

CDRH leadership has signaled interest in extending real-time trial capabilities to devices. Manufacturers planning IDE studies in 2026-2027 should:

• Raise real-time trial participation in pre-submission (Q-submission) meetings
• Ask about device-specific pilot opportunities
• Discuss data infrastructure requirements with their FDA review team

The Continuous Trial Vision

The FDA's real-time clinical trial initiative is part of a broader shift toward what the agency calls continuous trials — moving away from discrete development phases toward a seamless process where data flows continuously from first-in-human through post-market surveillance.

For medical device manufacturers, this vision aligns with several existing trends:

This is not a distant vision. The FDA is building the infrastructure now, and device manufacturers who invest in digital-ready clinical data systems will be the first to benefit.

Timeline

Key Takeaways

The FDA's real-time clinical trial initiative is the most significant change to clinical trial conduct in decades. While the initial pilot focuses on pharmaceutical products, the technology platform and regulatory framework are being built to serve all product types, including medical devices.

Device manufacturers who act now — by responding to the RFI, investing in digital clinical data infrastructure, and engaging CDRH early — will be positioned to participate in device-specific pilots as they emerge. Those who wait for a formal device announcement may find themselves behind competitors who have already built the necessary infrastructure.

The era of waiting until the end of a study to tell the FDA what happened is ending. The future is continuous: data flows in real time, safety signals are caught as they emerge, and regulatory decisions are made on accumulating evidence rather than retrospective analysis.