Clinical Trial

Agentic AI for Clinical Trial Site Intelligence

Q: What is agentic AI in clinical trials, and how is it different from traditional AI?

Agentic AI refers to AI systems made up of multiple specialized agents that can reason, plan, and act autonomously across complex clinical trial workflows. Unlike traditional AI models that perform single tasks in isolation, agentic AI coordinates site selection, enrollment forecasting, protocol feasibility, and data validation through an orchestrated network, all while maintaining transparency and human oversight.

Q: How does agentic AI improve clinical trial site selection?

Agentic AI improves site selection by integrating historical trial performance, real-world data, investigator experience, patient availability, and competing study load into a single intelligence layer. Sponsors can identify high-performing sites with adequate patient populations and operational capacity, reducing the risk of activating low-enrolling or underperforming sites.

Q: Can agentic AI help solve patient recruitment challenges?

Yes. Agentic AI addresses patient recruitment challenges by accurately estimating patient potential, validating claims, electronic health records, labs, and other real-world data sources, applying eligibility criteria, and forecasting enrollment timelines before trials begin. This enables precise patient matching and inclusive recruitment strategies.

Q: Is agentic AI compliant with regulatory and quality expectations?

When implemented correctly, agentic AI operates within regulatory, quality, and governance frameworks. Successful systems emphasize accuracy, explainability, data traceability, and human-in-the-loop oversight. FDA guidance on AI use in drug development has accelerated adoption, with leading pharmaceutical companies applying agentic and generative AI across trial planning, operations, and regulatory submission workflows.

Q: How is agentic AI applied in real-world clinical trial environments?

Agentic AI is deployed through a layered architecture that connects user-friendly interfaces with coordinated AI agents and unified data foundations. This approach enables clinical teams to ask complex questions and receive transparent, explainable outputs grounded in real-world data, supporting scalability, compliance, and operational impact.

Download White Paper

Reimagining site selection, enrollment, and trial execution with intelligent AI agents.

Clinical trials are becoming more complex, costlier, and competitive. Finding the right site to conduct a trial is tricky. Finding the patients to fill it can be even harder. Now throw fragmented data and manual decision-making on top of it.

All those challenges delay timelines. Worse, they increase risk.

This white paper explores how agentic AI, a new class of AI systems that plan, reason, and act autonomously, can transform clinical trial site intelligence across the trial lifecycle.

What you’ll learn:

How leading biopharma companies are applying generative and agentic AI for smarter site selection, faster enrollment, and higher trial performance
The five critical success factors for deploying agentic AI in clinical R&D
A practical, three-layer architecture for building scalable, compliant clinical AI solutions

Axtria’s Clinical Services team helps organizations design next‑generation agentic AI to optimize trials, starting with smarter site selection. Our AI agents are domain‑trained and fine-tuned explicitly for life sciences. And we bring advanced cloud solutions and combined decades of deep clinical understanding. Axtria’s Clinical Services enables sponsors to accelerate feasibility assessments, enhance site and investigator insights, forecast enrollment with confidence, and streamline trial operations, end‑to‑end.

Faster, better trials. It’s possible with Axtria’s agentic AI.