TriNetX Unveils Conversational AI Interface and Enhanced API Capabilities

Success achieved in reducing trial costs and timelines drives 2026 platform enhancements designed to democratize clinical research analytics.

CAMBRIDGE, Mass., Jan. 22, 2026 /PRNewswire/ -- TriNetX, driven by its vision of a connected world where data and intelligence power improved human health, today announced results demonstrating its TriNetX LIVE™ platform is transforming how pharmaceutical companies design and execute clinical trials. Uniting clinically rich real-world data (RWD) with artificial intelligence (AI) capabilities, the platform has enabled measurable reductions in costly protocol amendments and dramatic improvements in site identification efficiency, results that are now driving the next generation of platform innovation.

In early 2026, the company will launch AI capabilities that allow researchers to query its global network using natural language, eliminating technical hurdles that have historically limited access to sophisticated RWD analytics. These capabilities are currently in Beta with select customers, enabling early feedback and refinement ahead of the full launch.

The announcements cap a landmark year in which TriNetX earned triple industry recognition: spots on The Healthcare Technology Report's Top 50 Healthcare Technology Companies and Top 25 Healthcare Software Companies lists, plus Best of Show finalist at SCOPE Europe, while expanding its global network by millions of patients.

2025 Growth Powers 2026 Innovation

TriNetX's network and research impact grew substantially in 2025, resulting in the following total scale:

• 280+ million patients across the global federated network (up from 273 million)
  
  
• 10,000+ clinical trial sites identified and mapped (up 57.5% year-over-year)
  
  
• 220+ healthcare organizations spanning four continents
  
  
• 1,400+ peer-reviewed publications across oncology, cardiology, neurology, and ophthalmology supported—double the 2024 total, bringing the cumulative count to 2,500+

"These numbers represent accelerated hope for patients waiting for treatment," said Steve Kundrot, Chief Operating Officer at TriNetX. "Every data point connects to a real human outcome. Trials fill faster, cancers are detected earlier, and therapies reach patients months or years sooner."

AI Applications Address Industry's Biggest Challenges

With clinical-development costs averaging approximately $708 million per approved drug (2024 JAMA Network Open analysis) and protocol amendments delaying trials by roughly 260 days on average (2023 Tufts CSDD study), pharmaceutical companies are turning to AI-powered RWD platforms to compress timelines and reduce waste. In 2025, TriNetX delivered concrete results across four critical areas.

Fewer protocol amendments: Leveraging RWD and AI, the company helped clients reduce costly protocol amendments by up to 50%, keeping trials on track and accelerating patient access to new treatments.

Reimagined site identification: Instead of starting with known sites and searching for patients, TriNetX identifies the right patients first, then finds the sites where they're already receiving care. In one collaboration with a major pharmaceutical company, this approach achieved a 63% site acceptance rate with an average response time of just nine days.

Smarter recruitment: Machine learning models for inflammatory bowel disease predicted trial enrollment conversion rates for Crohn's disease could jump from 33% to 85%, enabling sponsors to target and engage patients more efficiently.

Earlier disease detection: An AI model for pancreatic cancer, developed with leading research institutions, can predict who is at risk of developing the disease within the next 18 months. By identifying 87 predictive features and generating customizable risk thresholds, the model supports tailored clinical decision-making, from sending high-risk patients directly to imaging, to serving as a standalone early detection tool, or casting a broader net followed by biomarker testing. Researchers are now validating the model on a prospective cohort of six million patients.

2026 Platform Enhancements: Making Clinical Research Analytics Accessible to All

In the coming months, TriNetX will release its most ambitious enhancements yet to TriNetX LIVE™, designed to make sophisticated clinical research analytics accessible regardless of technical expertise.

Conversational AI Interface: Researchers will ask complex questions in natural language and receive sophisticated analyses instantly. With no query-building expertise required, they remain focused on science, not syntax. The capability is powered by TriNetX's proprietary clinical ontology and taxonomy, accessing data sourced directly from TriNetX's live global provider network. This ensures insights are continuously refreshed and fully traceable.

Enhanced API Capabilities: New Application Programming Interface (API) connections will allow partners to send study queries directly from their existing systems to TriNetX via codes or natural language, receiving real-time patient counts, feasibility data, and site intelligence, all seamlessly integrated within current workflows. By removing data silos, accelerating study planning, and supporting enterprise-wide digital initiatives, these capabilities are paving the way toward Agentic AI-level integration, bringing truly intelligent, autonomous data-driven decision-making closer to reality.

"We're removing the roadblocks between researchers and insights," said Kundrot. "When a scientist can ask questions in plain language and get sophisticated analyses instantly, we fundamentally change who can participate in clinical research and how quickly treatments can reach patients."

Pharmaceutical companies and clinical researchers can request a demo of TriNetX's AI-powered platform capabilities here.

About TriNetX, LLC

TriNetX makes complex, real-world health data easy to use. Data is sourced directly from our growing global network of over 8,000 healthcare provider locations. TriNetX customers select the data source, types, and breadth of data they need; the data access methods they desire; and the types of software, human and machine intelligence they wish to apply – and combine these to solve their business objectives. Visit TriNetX at www.trinetx.com or follow TriNetX on LinkedIn to learn more.

Media Contact
TriNetX
Karen Tunks
Email: [email protected]

SOURCE TriNetX