nPhase raises $30M to build AI-native platform for drug trials

New capital for clinical data

nPhase, Inc. has announced the closing of a $30M Series D financing round. This investment was led by Viking Global Investors and marks the company's first institutional equity capital raise since 2017. The funding highlights a period of nearly a decade where the company grew through disciplined self-sufficiency.

The primary goal for this new capital is to accelerate the global expansion of the nPhase.ai clinical data platform. This enterprise-level software is designed to support the drug development lifecycle by unifying two critical components. It combines a Unified Data Management System (UDMS) with a Statistical Computing Environment (SCE).

By bringing these two systems together, nPhase aims to solve a major technological barrier in the pharmaceutical industry. Many current federal initiatives, such as ARPA-H’s SURPASS program, want to move toward continuous and adaptive clinical trials. However, the industry is currently hindered by fragmented data that is often processed in large, delayed batches.

Bridging data to submission

The nPhase.ai platform is built to create an unbroken and audited pipeline for clinical research. It connects electronic data capture (EDC) with regulatory biostatistical analysis. This includes the REDCap Cloud ecosystem, which is frequently used by academic, nonprofit, and mid-market research groups.

The system allows for continuous ingestion of raw trial data from various sources. This includes data from investigator sites, central laboratories, patient applications, and remote biosensors. By capturing this information as it is generated, the platform prevents the multi-month backlogs that typically occur during end-of-study data cleanups.

The technology also uses stream-based harmonization to standardize and validate clinical variables in near real time. This allows safety monitoring committees and study directors to track adverse events and protocol deviations instantly. It replaces the old method of retrospective batch transformations, where data is cleaned only after the study period ends.

Automating the heavy lifting

One of the most significant features of the nPhase.ai platform is its ability to compress submission workflows. The system automatically translates raw, standardized clinical data into regulatory-ready models known as CDISC ADaM. It also generates formal statistical tables, figures, and listings, which are essential for government approval.

Historically, these complex workflows have required four or more months to complete manually. The nPhase platform aims to compress that timeline down to just a few weeks. This speed is achieved by creating a governed, deterministic data fabric that serves as a foundation for advanced computing.

This foundation enables the use of agentic AI to handle the most labor-intensive and mechanical chores of clinical research. These agents can draft statistical code, flag discrepancies in source data, and track missing laboratory ranges. However, the system maintains human-in-the-loop oversight to ensure that formal biostatistical sign-offs remain under human control.

Modernizing life sciences

The investment from Viking Global Investors reflects a broader goal to modernize how the life sciences industry manages data. Levi Malik, a Principal at the firm, noted that nPhase combines a rare mix of clinical research experience and a clear vision for enterprise-scale AI. He stated, "We believe this combination positions the company well for its next stage of growth."

The platform is positioned to address the specific needs of large-scale drug development. By providing a unified system, it helps organizations move away from the

Overcoming federal barriers

The nPhase.ai platform is designed to tackle a major technological hurdle currently facing federal initiatives. Programs like ARPA-H’s SURPASS, which falls under the HHS “Operation TrialBlazer” initiative, aim to create continuous and adaptive clinical trials. These goals are often difficult to reach because the pharmaceutical industry remains constrained by fragmented data and slow, batch-processed workflows.

By providing a unified data fabric, nPhase helps these programs move toward a more modern model of research. The platform allows for a more fluid exchange of information that can support the rapid, iterative nature of these federal projects. This infrastructure helps bridge the gap between current data limitations and the vision for more agile drug development.

Real-time safety and oversight

The platform provides immediate visibility into critical safety metrics for those overseeing clinical studies. Safety monitoring committees and clinical study directors can use the system to track adverse event clustering and detect signals in real time. This instantaneous monitoring allows for quicker responses to potential issues during a trial.

In addition to safety tracking, the system helps directors identify protocol deviations as they occur. Instead of waiting for a final report to find errors, researchers can maintain constant oversight of the study's integrity. This level of transparency ensures that the data remains reliable and that patient safety is prioritized throughout the entire lifecycle of the research.