AI Agents designed for clinical trials
Agent Studio reimagines the clinical trial lifecycle by giving teams the power to build and deploy agents that automate manual work, remove bottlenecks, and accelerate trial outcomes.
Less friction. More progress.
Medable Agent Studio is a no-code platform for sponsors and CROs to design, deploy, and scale clinical development agents, from ready-to-go solutions to fully bespoke builds.
Connected to your systems
Take the difficulty out of data. Connect seamlessly across 13+ clinical and enterprise systems, eliminate manual stitching, and enable real-time data flow for faster decisions.
Clinical data and regulatory standards
Purpose-built for life sciences. Grounded in GxP, ICH, HIPAA, GDPR, and CDISC to support the rigor required in clinical development.
Human in the loop
You set the guardrails. Define how much control agents have, aligning automation with oversight and your team’s workflows.
Meet Agent Studio
- Quickly configure and deploy agents tailored to your specific clinical development needs
- Maintain human-in-the-loop oversight to ensure transparency and control
- Align with life sciences standards by incorporating SOPs, regulatory and validation requirements, and benchmarking against trusted sources
- Seamlessly integrate with life science systems (eCOA, Veeva EDC, IRT, CTMS) and enterprise platforms
“Every time I see [Agent Studio] I get more excited.”
Eliminate clinical trial white space with the right AI strategy
It has become clear that our industry has reachedthe limits of human-only clinical development. As clinical trials have become increasingly complex, the endeavors that people alone can perform are no longer sufficient to generate the momentum needed to address the growing burden of human disease. This has led to longer drug development timelines and significant delays for patients. One large are of lost time is “white space,” definied simply as unproductive time caused by manual, sequential processes and fragmented data systems. Thankfully, a solution lies in agentic AI and its abilities to perform series of tasks.
From platform to practice, meet your CRA Agent
The CRA Agent unifies data from across clinical systems, automatically surfacing insights and risks so monitors no longer need to log into multiple platforms. By handling routine tasks autonomously and keeping humans in the loop for critical safety oversight, it reduces tech burden, accelerates study timelines, and empowers CRAs to focus on data quality, patient safety, and site relationships.
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.
The latest from Knowledge Center
eCOA standards and KPIs to include in your next RFI
According to Gartner, a request for information, or a request for proposal, is defined as “both the process and documentation used in soliciting bids for potential business or IT solutions required by an enterprise or government agency. The RFI document typically outlines a statement of requirements (SOR) to be met by prospective respondents wishing to make a bid to deliver the required solutions. It might cover products and/or services to meet the given requirements.”
Yet, for anyone entering into a long-term business agreement, a well-written RFI can do so much more than just assess and collect vendor capabilities.
For the last decade, Medable has been transforming the capabilities of organizations across clinical research using the latest in new technologies. In this time, we’ve learned the best RFIs are able to define what success looks like, create alignment on measurable outcomes, and establish accountability on roles and responsibilities well before a contract is ever signed. When done correctly, it becomes a decision-making framework that offers clear vision to both organizations.
Recently, Medable received two RFIs around eCOA from top pharmaceutical organizations. They stood out to us because they were structured around performance, not promises, a distinction that makes all the difference.
How to successfully transition from paper COAs to eCOA
Electronic clinical outcome assessment (eCOA) systems have reshaped how patient-reported outcome measures are collected and managed in clinical trials. Clinical operations leaders are under more pressure than ever to ensure that the migration from legacy paper instruments to digital platforms not only improves trial efficiency but also preserves data integrity, supports regulatory acceptance, and enhances participant experience.
The transition from paper to electronic capture represents a paradigm shift toward more efficient, accessible, and reliable data collection. Done well, eCOA strengthens evidence generation while reducing burden for participants and sites alike. Done poorly, it risks measurement bias, loss of comparability, and regulatory challenges.
In this article, clinical operations leaders will find evidence-based best practices for migrating and implementing patient-reported measures as part of eCOA strategies. These recommendations are rooted in published industry guidance and emerging scientific consensus, and they reflect the evolving landscape of digital assessment technologies.
Paper COAs in 2026? It’s not “cheaper,” it’s riskier
eCOA’s time has come. The market is currently estimated to be worth $2.3 billion, with projections showing it reaching nearly $5 billion by 2030. Despite this, paper still plays a prominent role for some clinical trials today.
At first glance, paper may seem simple and familiar, even economical. However, in today’s regulatory and operational environment, paper COAs are not a risk averse choice when held to the standards of what sponsors, CROs, and regulators are looking for trial data to prove.