Knowledge Center
Is Data Readiness Slowing Down AI in Clinical Trials? How Agentic AI Enables Immediate Impact
Most sponsors and CROs say their data isn't ready for AI. But agentic AI does not require a perfect data environment to begin delivering value. It can be deployed compliantly across siloed platforms, interpreting and reconciling differences in real time. In this 60-minute session, learn how AI agents deliver measurable value safely across clinical trials, reduce cognitive and operational burden, and enable teams to generate impact now while strengthening data foundations over time.
Latest Blogs
What to look for in an AI clinical trial platform: A buyer's guide
Discover what to look for from artificial intelligence tools in the clinical trial market.
Which AI and agentic AI clinical trial vendors integrate best with existing systems?
Artificial intelligence is reshaping clinical trial operations in 2026. Sponsors and CROs are no longer evaluating standalone tools. They are choosing platforms that can connect with existing systems, automate complex workflows, and scale without disrupting ongoing studies. This guide breaks down the vendors best positioned to integrate with the clinical trial infrastructure you already have.
What happened at ASCO 26?
With 44,000+ oncology professionals in attendance, ASCO 2026 may have been the most consequential in recent years. From a standing ovation for pancreatic cancer to the first positive sarcoma trial in history, here's everything that mattered at Chicago's McCormick Place this week.
White papers, Case studies & reports
From three meetings to one removing bottlenecks with AI-enabled eCOA
Discover how AI-enabled eCOA and agentic workflows reduce clinical trial startup time, translation cycles, and meeting overhead—cutting eCOA build timelines from 16–20 weeks to under 8 weeks.
Case study: Scaling global vaccine mega-trials for a top-5 pharma
Learn how Medable enabled a top-5 pharma to scale vaccine mega-trials with near-100% enrollment, real-time safety data, and >90% diary compliance.
Case study: ICON and Medable drive 85% eConsent adoption in U.S. menopause study
How do you drive adoption in a complex women’s health study? See how ICON and Medable reached 85% eConsent uptake across 1,200+ participants with a smarter, site-first approach.
On-Demand Webinars
Is Data Readiness Slowing Down AI in Clinical Trials? How Agentic AI Enables Immediate Impact
Most sponsors and CROs say their data isn't ready for AI. But agentic AI does not require a perfect data environment to begin delivering value. It can be deployed compliantly across siloed platforms, interpreting and reconciling differences in real time. In this 60-minute session, learn how AI agents deliver measurable value safely across clinical trials, reduce cognitive and operational burden, and enable teams to generate impact now while strengthening data foundations over time.
The AI Pilot Trap and How Clinical Trial Leaders Can Escape It
Most AI pilots in clinical trials fail to scale beyond proof of concept. Learn practical strategies for moving from isolated experiments to enterprise adoption.
Scientific Research
Assessing the financial value of decentralized clinical trials
Deployment of remote and virtual clinical trial methods and technologies, referred to collectively as decentralized clinical trials (DCTs), represents a profound shift in clinical trial practice. To our knowledge, a comprehensive assessment of the financial net benefits of DCTs has not been conducted
Development of a mobile health app (TOGETHERCare) to reduce cancer care partner burden: Product design study
Research looking at mobile apps and how they may provide a meaningful access point for all stakeholders for symptom management.
Guides
eCOA, AI, and Agentic AI: A practical overview and guide
Combining artificial intelligence (AI) and agentic AI with electronic Clinical Outcome Assessment (eCOA) systems fundamentally enhances how clinical trial data is collected, interpreted, and acted upon. At its core, eCOA captures structured data directly from patients, clinicians, or observers, such as symptom severity, quality of life, or functional outcomes. Modern platforms expand this further by supporting a full range of assessment types, including electronic patient-reported outcomes (ePRO), clinician-reported outcomes (eClinRO), observer-reported outcomes (eObsRO), and performance outcomes (ePerfO).
eCOA vs ePRO: Understanding the differences in clinical trials
Digital data capture has become essential to modern clinical research. Sponsors and research organizations increasingly rely on electronic outcome assessment tools to collect high quality patient data, reduce manual errors, and improve regulatory compliance.
Two terms appear frequently in this space: eCOA (electronic Clinical Outcome Assessment) and ePRO (electronic Patient Reported Outcome).
These terms are closely related. However, they are not interchangeable.
Common missteps when deploying eCOAs in clinical trials
Sometimes when teams deploy eCOA (electronic Clinical Outcome Assessment) in clinical trials, challenges can arise with operational planning, protocol design decisions, or workflow alignment. Below are some of the most common missteps observed across sponsors, CROs, and investigative sites.
1. Treating eCOA as a late-stage add-on
Many teams wait until protocol finalization or even after startup to plan eCOA implementation.
Why this causes problems
- Instrument licensing or translations may not be ready
- Build timelines get compressed
- Protocol schedules may not align with electronic workflows
Best practice
Plan eCOA during protocol design, especially when selecting instruments and defining visit schedules.