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ExpertAINews & ResourcesNewsExpert.ai and Springer Nature Partner to Transform Clinical Trials with AI-Driven Intelligence and Deep Domain Expertise
Expert.ai and Springer Nature Partner to Transform Clinical Trials
16 September 2025

Expert.ai and Springer Nature Partner to Transform Clinical Trials with AI-Driven Intelligence and Deep Domain Expertise

Strategic collaboration sets a new standard for accelerating drug development through AI-driven insights.

Expert.ai, a leading provider of enterprise artificial intelligence solutions for business value creation, and Springer Nature, a global leader in research publishing, today announced a strategic partnership aimed at transforming clinical trial design and operations. This collaboration combines Expert.ai’s Hybrid AI capabilities with Springer Nature’s deep domain expertise to deliver next-generation clinical trial intelligence for pharmaceutical and life sciences organizations.

Under a shared commitment to advancing AI-powered discovery, the partnership introduces “Clinical Trials Intelligence,” a dynamic framework of solutions to enable clinical teams to design, optimize and evaluate trials with greater precision, speed and confidence. By integrating Springer Nature’s proprietary drug information with Expert.ai’s rich indexed data set, the solution delivers actionable insights across the entire clinical trial life cycle. Powered by advanced natural language understanding and deep domain expertise, Clinical Trials Intelligence transforms unstructured data into strategic guidance — enabling faster feasibility assessments, more informed protocol design and smarter trial execution all while keeping scientific judgment and ethical standards at the core.

Built on a foundation of over 900,000 validated global clinical trials and enriched with real-world data from observational studies and scientific publications, Clinical Trials Intelligence empowers users to tackle key challenges in clinical research, including:

  • Patient and site identification
  • Eligibility criteria optimization
  • Real-world evidence integration
  • Competitive landscape analysis

“We are proud of this collaboration that marks a pivotal step in making clinical trials more precise, inclusive and data-driven,” said Christophe Aubry, Global Head of Life Sciences & Healthcare, Expert.ai. “This partnership brings together best-in-class tools, technologies, data and domain expertise to accelerate time to market for new therapies while improving trial outcomes and operational efficiency.”

Available through the EidenAI Suite, Expert.ai’s ecosystem of tools and industry-specific AI solutions, Clinical Trials Intelligence enables clinical teams to compare protocols in real time and refine study design based on outcomes and global trends, all in minutes, while improving alignment with patient populations and regulatory expectations.

Enriched by Springer Nature’s trusted AdisInsight data and subject matter expertise, the solution sets a new standard for how pharmaceutical and life sciences companies can streamline decision making, reduce trial risks and accelerate time–to market.

“Reflecting its ongoing dedication to innovation, Springer Nature is committed to unlocking the potential of AI to advance scientific discovery and drive meaningful progress in research. The partnership with Expert.ai aligns seamlessly with this vision, reinforcing a shared commitment to pushing the boundaries of what’s possible in science through innovation,” added Nicole Radewic-Pahl, Vice President Pharma Solutions at Springer Nature. By combining Expert.ai’s cutting-edge AI capabilities with our deep domain expertise, we empower researchers with insights that continuously evolve with the science.”

The new Clinical Trials Intelligence solution will be showcased at BioTechX USA 2025, held in Philadelphia on September 16-17, 2025.

Contact us to schedule a live demo session on site and learn how to:

  • Detect patient population and locations using real-world data
  • Match eligibility criteria based on demographic and clinical attributes
  • Integrate and classify scientific publications for disease-specific insights
  • Monitor competitors and assess trial strategies dynamically
  • Generate concise, outcome-based summaries to support regulatory submissions

Request a demo