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Insights on Agentic AI for Clinical Trials
Perspectives, deep-dives, and field notes from the Maxis AI team on agentic AI in regulated clinical operations.
Pillar Guide
Clinical Trial Execution Gap: Why It's Now a Cost, Timeline, and Compliance Problem
Detection has never been better, yet timelines slip, deviations repeat, and costs compound. Inside the execution translation gap — and the supervised execution layer that closes it.
Featured
Featured Blogs
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Clinical Trial Execution Gap: From Risk Signals to Action
Why detection alone does not close the gap — and how governed action paths, thresholds, and Execution Risk Indicators turn trial signals into accountable work.
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What Is a Clinical Trial Execution System and Why You Need One?
Systems of record versus systems of action: the orchestration, closed-loop verification, and unified oversight that define a real execution layer.
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Clinical Trial Operations Automation: A 3-Stage Maturity Model
From point automation to supervised orchestration — what each stage of clinical trial automation delivers, what it leaves unresolved, and where to start.
All
All Blogs
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What Are AI Agents in Clinical Trials?
A practical definition of governed, supervised execution systems — and how they differ from chatbots, rule-based automation, and predictive analytics.
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How Do AI Agents Work in Clinical Trials?
Inside the governed execution loop: observe, reason and plan, act, verify and audit — with the permissions, thresholds, and logging that keep it controlled.
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Agentic AI vs Generative AI in Clinical Trials
Content generation or workflow execution? A clear comparison of what each approach does well, where each breaks down, and how to choose.
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Human-in-the-Loop AI in Clinical Trials: Why It Matters
Assist mode, execute with approval, and bounded autonomy — the three oversight models that keep AI-supported actions reviewable and attributable.
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Agentic AI in Clinical Data Management: Modernizing Trial Data for Cleaner, Faster Insights
Governed agents for data cleaning, mapping, reconciliation, and database lock readiness.
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AI Agents for Patient Recruitment
From candidate discovery to enrollment: how governed agents reduce the invisible recruitment tax while eligibility and consent stay with human teams.
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Agentic AI for Pharmacovigilance: How AI Agents Accelerate Safety Case Processing & Signal Detection
How AI agents accelerate ICSR intake, coding, and continuous signal detection while safety scientists retain every medical and regulatory decision.
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AI-Enabled Risk-Based Monitoring: How AI Agents Strengthen Clincial Trial Oversight
How AI agents strengthen RBQM and site oversight through earlier risk detection, site risk scoring, and recommended actions validated by humans.
Pillar Guide
AI Agents in Clinical Trials: A Complete Guide
Use cases, ROI, FDA considerations, and an implementation roadmap for deploying governed AI agents across clinical operations in 2026.
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