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Your co-pilot for clinical monitoring
Medable’s CRA Agent is an AI-driven solution that automates and optimizes clinical trial monitoring by proactively identifying and prioritizing site risks, generating comprehensive pre-visit summaries, and providing actionable recommendations to enhance trial oversight and compliance.
We estimate that CRA agents can take on up to 90% of the tactical and administrative work the CRA handles on a daily basis — from sending site-specific emails and reminders to tracking responses and updating systems. That means we can focus our time on the strategic decisions that move trials forward, while standardizing and streamlining the tasks that used to consume most of our day.
Connected monitoring across systems
Perceive signals across the entire clinical data ecosystem by unifying CTMS, RTSM, EDC, labs, consent, and safety into one view. Turn manual checks into automated insights, instantly highlighting which sites are on track and where intervention is needed, saving valuable time, system-hopping, and manual data compilation.
Human-in-the-loop oversight
Easily identify risks and recommendations for best-next actions tied to your protocol, consent, and regulatory requirements. Stay assured with a transparent reasoning trail thatshows why each step is advised, enabling CRAs to collaborate confidently with sites, improve decision-making, enhance their compliance, all while freeing CRAs to focus on engagement and site-specific challenges.
Automated administrative tasks
Take advantage of automated routine tasks like drafting queries, sending emails, and updating CTMS/eTMF — always with human CRA oversight. Close the loop between planning and execution with real-time tracking that reduces administrative burden, ensures data consistency, and accelerates trial progress.
The latest from Knowledge Centers
What happened at ESMO AI & Digital 2025
The 2025 ESMO AI & Digital Oncology Congress, held in Berlin from November 12 to 14, highlighted the accelerating role of artificial intelligence across the oncology care continuum. Although imaging and pathology remain the most established fields for AI adoption, this year’s programming revealed a decisive shift toward workflow-integrated AI that enhances clinical operations, supports trial efficiency, and addresses the realities of patient monitoring.
Across three days of sessions, side-room conversations, and industry demonstrations, one theme was clear. AI is evolving from experimental add-on technology into a practical clinical teammate, but scaling its impact will require robust validation, seamless integration, and a sustained focus on clinician trust.
Vertical vs. horizontal: Why your Agentic AI should be built by clinical experts in life sciences
By now, most people are familiar with ChatGPT and other general-purpose AI tools such as Perplexity. These horizontal AI systems have become commonplace, assisting users with tasks like composing emails, summarizing information, or generating creative ideas. Their adaptability across a wide range of domains demonstrates the power of general intelligence and transfer learning.
However, in the high-stakes and highly regulated context of life sciences, it is important to ask whether such tools are suitable for clinical use. In this setting, a vertical agentic AI approach—purpose-built for specific domains—provides the precision, reliability, and compliance necessary for success. While both horizontal and vertical agentic AI play essential roles in the broader evolution of intelligent systems, it is the vertical approach that ensures the rigor and accountability demanded by life sciences applications.
Medable oncology solutions
Discover how Medable’s AI-powered oncology platform simplifies complex cancer trials by integrating eCOA, ePRO, and eConsent solutions—reducing trial time, improving patient retention, and enhancing data quality for faster, more efficient research.
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.