Syneos Health Expands AI Ecosystem With Three New Platform Partnerships

Syneos Health has announced the continued expansion of its artificial intelligence (AI) ecosystem, detailing three platform partnerships designed to embed AI into core clinical development workflows.¹

The three partnerships each target a distinct layer of the clinical development stack.

Through a new collaboration with Causaly, Syneos is applying agentic, evidence-based scientific reasoning to accelerate protocol strategy development, feasibility planning, and competitive trial intelligence.

Causaly's platform surfaces evidence from a proprietary knowledge graph combining biomedical research and commercial insights. According to the company, the integration has reduced the time it takes to derive insights for study strategy and design by approximately 50%.

The partnership with Databricks focuses on the data infrastructure layer. By leveraging the Databricks Data and AI Platform, Syneos has developed a near real-time view of clinical operations that reduces the time from source data capture to review-ready insight from days to hours, enabling faster intervention and more efficient trial execution.

The Microsoft collaboration, which builds on a relationship that began in 2023, extends AI adoption through productivity and workflow tools. Syneos has used Microsoft Power Apps and other tools to develop more than 280 agents that integrate with Microsoft 365 Copilot to streamline workflows and support faster decision-making across the organization.

"When technology is applied precisely at critical decision points, teams can anticipate risk earlier to accelerate development," said Mike Montello, chief digital and information officer at Syneos Health, in a company press release.

Together, the three partnerships are designed to create what Syneos Health describes as a unified intelligence environment—connecting operational, clinical, and real-world data across the development lifecycle.

The company noted that all capabilities are deployed with human oversight and governance to ensure responsible use in regulated environments.

A broader conversation about AI and site readiness

The Syneos announcement reflects a pattern Applied Clinical Trials has been tracking closely: sponsor investment in AI is accelerating, but questions about how that technology reaches sites—and whether it actually fits their workflows—remain unresolved.

In a recent interview with ACT, Liz Beatty, co-founder and chief strategy officer at Inato, addressed that tension directly.²

Beatty argued that the industry has consistently made the mistake of building technology for sponsors rather than for sites.

"We need to stop asking sites to do something specific to my trial or my company, and instead think: how can I enable sites to use this technology to become more efficient and effective in clinical trials, which then helps my trial and my company—not the other way around," she said.

On where AI is delivering measurable enrollment impact, Beatty pointed to real-time patient data as the most significant shift. Rather than relying on feasibility questionnaires and sponsor-discounted estimates, AI tools can now identify which specific patients at a given site currently meet study criteria.

In a chronic obstructive pulmonary disease case study, sites using AI-driven patient assessment screened patients 33% faster than those that did not, and 100% of sites using the tool were able to successfully screen and enroll patients.

Looking ahead, Beatty pointed to a structural shift she sees gaining momentum: sponsors moving away from trial-by-trial site planning toward program or cross-asset planning, building deeper site partnerships across multiple studies.

"When sponsors do that, sites are actually three times more likely to share patient data in the context of a broader program," she said.

This represents a dynamic that could meaningfully change how enrollment bottlenecks are addressed before a trial even begins.

References

1. Syneos Health Advances AI-Powered Clinical Ecosystem to Optimize Trial Performance and Speed Decision-Making. News release. Syneos Health. August 18, 2026. Accessed August 18, 2026. https://www.syneoshealth.com/news/Syneos-Health-Advances-AI-Powered-Clinical-Ecosystem-to-Optimize-Trial-Performance-and-Speed-Decision-Making
2. AI-Enabled Sites and the Future of Trial Planning: Q&A with Liz Beatty, Inato. Applied Clinical Trials. August 7, 2026. Accessed August 18, 2026. https://www.appliedclinicaltrialsonline.com/view/ai-enabled-sites-future-trial-planning-liz-beatty-inato