Agentic AI made for clinical trials
Unlock a better way to run trials. Agents help with the manual work, coordination, and day-to-day friction so teams can focus on moving studies forward and making faster decisions.
Built specifically for clinical development with deep GxP, regulatory, and operational expertise, Agent Platform helps run better trials so you can find cures faster.
Launch quickly. Operate intelligently.
1: Connect
Connect your clinical systems to Agent Platform to make faster sense of your data, eliminate manual stitching, and enable real-time data flow for faster decisions.
2: Assist
Use our pre-configured agents to automate filing, proactively identify site risks, generate pre-visit summaries, or build your own agent exactly to your trial’s protocols and needs.
3: Verify
Check your work and get going. Whether you want your agentic teammates to act autonomously or operate with a human in the loop, they move work forward in real time.
4: Evolve
Go beyond static systems with a platform that evolves continuously, with built-in verification and quality assurance designed for clinical development.
Connect your clinical and enterprise systems
Medable connects with the clinical and enterprise tools your organization already uses, right out of the box. Need more? Add the connectors your workflows demand.
- Prebuilt integrations for common clinical and enterprise systems
- Fast onboarding with minimal IT lift
- Flexible connectors that adapt to your workflows
- Secure, compliant data exchange across systems
Say hello to your new agents
Our team of agents for clinical monitoring, TMF management, and PI and audit readiness, make work easier than ever before.
Roadmap to adopting AI agents
The successful integration of AI agents in enterprise operations requires a balanced, deliberate approach. Drawing from recent research in Strategic Integration (SI) and agentic AI adoption within large enterprises, the following best practices help maximize value, manage change effectively, and mitigate common pitfalls. Medable Agent Studio specifically streamlines this process by providing robust tools, no-code simplicity, and built-in compliance and security standards.
The agentic revolution for clinical trials
The latest from Knowledge Center
eConsent regulations: What changed under FDA, ICH E6(R3), Part 11 and global regulations
Electronic informed consent, or eConsent, is no longer a novel approach to clinical research. Regulators around the world increasingly recognize electronic, remote and technology-enabled approaches to informed consent as part of modern clinical trial conduct.
But the regulatory environment has changed significantly.
The most important development is not a single new eConsent regulation. Instead, updates to Good Clinical Practice, electronic systems guidance and national clinical trial frameworks are changing how sponsors can design, document and manage informed consent.
ICH E6(R3) is central to that change. FDA issued E6(R3) as final guidance in September 2025, describing the revision as a modernization of GCP that embraces innovation in trial design, conduct and technology while emphasizing quality by design, participant protection and risk-based approaches. FDA subsequently withdrew its E6(R2) guidance in April 2026.
At the same time, regulatory developments in the United States, European Union, United Kingdom and Canada are providing clearer frameworks for electronic records, remote interactions and alternative ways of documenting consent.
For sponsors, CROs and clinical trial sites, the question is therefore changing. It is no longer simply, "Can informed consent be electronic?"
Increasingly, the question is: How can electronic informed consent be implemented in a way that protects participants, supports understanding, verifies identity where required, preserves reliable records and meets the requirements of every jurisdiction involved in a trial?
The age of agentic A complete guide on agents in clinical trials
A complete guide to AI agents in clinical trials, includingwhat they are, the infrastructure they need, where people stay in charge, and how to start. Discover how agentic AI is transforming clinical trials, and what's next. And, learn about ontologies, human-in-the-loop governance, build vs. buy, continuous validation/governance, and more.
What is a forward deployed engineer, and why do today's clinical trials need one?
What exactly is a forward deployed engineer?
If you have spent any time around AI and enterprise software this year, you have probably heard the term FDE, or forward deployed engineer. It sounds like a buzzword, but the role is why we’re able to solve real problems for our clinical trial clients in record time.
Frequently asked questions
Agentic AI refers to autonomous, goal-driven AI systems—often called “agents”—that can reason, plan, and act in complex environments with minimal human intervention. In clinical development, these agents can manage and optimize trial workflows such as protocol design, patient recruitment, site coordination, and regulatory documentation. Unlike traditional automation, which follows static rules, agentic AI adapts to new information, learns from trial progress, and proactively orchestrates tasks to keep studies on track and compliant.
AI agents help clinical trials run faster, more efficiently, and with greater quality. By automating repetitive tasks, adapting protocols in real time, and reducing human error, they streamline operations across sites while ensuring compliance and consistency. They also enable more patient-centric approaches by improving communication and engagement, ultimately making it easier to scale complex global trials with fewer resources.
Delivering trustworthy Agent recommendations requires two key elements:
The AI Model – We select and fine-tune models that are purpose-built for life sciences, trained on high-quality, relevant data. This ensures the model understands domain-specific language, context, and regulatory requirements, reducing the risk of inaccurate or irrelevant outputs.
The Agentic Environment & Verification Process – Agents operate in a controlled environment with rigorous validation checkpoints, business logic guardrails, and real-time monitoring. Every recommendation is subject to verification workflows and data quality checks before it’s surfaced to users, ensuring accuracy, compliance, and auditability.