Act on Portfolio Risk Across Clinical Programs. Built for R&D Leaders
Clinical portfolios generatecontinuous risk signals, but structured resolution across workflows remainsconstrained.
Agentic AI for pharma R&Dintroduces a governed execution layer that acts on these signals, enablingearlier intervention and more predictable portfolio outcomes.
A Day in
the Life of a CMO
Your day starts with fragmented updates - CRO reports, safety signals, and enrollment delays across programs.Despite multiple dashboards, there is no single view of what requires action now. The challenge is not visibility.
It is acting early enough. By the time signals are confirmed, critical time is already lost. Agentic AI for pharmaR&D is designed to address this execution gap.
The Pressures CMOs &
R&D Heads Feel Every Day
The Pressures CMOs &
R&D Heads Feel Every Day
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Industry Reality
~10–15% of drug candidates reach market
10–15 years and ~$1–2B per drug
6,000+ active clinical candidates
Why Maxis AI Is Built for This Role
Maxis AI delivers a supervised execution layer - an AI Workforce embedded within clinical workflows. It continuously monitors operational, safety, and enrollment signals and executes defined workflows under expert oversight. Unlike analytics tools, Maxis ensures signals are not just identified but acted upon within governed processes.
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From Pain to Outcome: How Maxis AI Works for You
| Pain Point | AI Capability | Outcome |
|---|---|---|
| Fragmented trial updates across multiple CROs create blind spots in portfolio oversight | Supervised AI agents continuously aggregate and monitor operational, safety, and enrollment signals across all studies | Unified, real-time portfolio visibility - risks detected months earlier, not quarters late |
| Manual analytics and reporting cycles delay critical go/no-go decisions | Automated progress reporting and protocol compliance checks with human-in-the-loop validation | Unified, real-time portfolio visibility - risks detected months earlier, not quarters late |
| Late-phase program failures that could have been avoided with earlier signals | AI Workforce flags CRO performance gaps, slow enrollment, and emerging safety signals under defined governance controls | $15M–20M potential cost avoided per program through early adjustment |
All You Need to Know
It continuously monitors signals and executes workflows under expert oversight.
Catching a late-phase failure signal 4–6 months sooner can save tens of millions in sunk costs and protect pipeline value.
Yes. Maxis AI operates as an AI Workforce across multiple clinical programs, with integrated system connectivity, coordinated execution, and full audit traceability.
Analytics platforms identify risks. Maxis AI resolves them executing defined workflows under human supervision, not just surfacing insights.
Manpower-based monitoring no longer scales with pipeline complexity. Maxis AI aligns execution capacity with output, not headcount.
Looking for Agentic AI for clinical trials?
Explore our Agentic AI Platform to see how AI agents are transforming study startup, data management, oversight, and regulatory submissions.