nPhase raises $30m in Series D funding led by Viking Global to expand AI clinical data platform

US clinical research technology company nPhase has raised $30 million in a Series D funding round led by Viking Global Investors, as it plans to expand its AI-native clinical data platform and develop agentic AI capabilities for pharmaceutical companies.

The financing will support the growth of nPhase’s enterprise clinical data business and accelerate development of its Statistical Computing Environment (SCE), Unified Data Management System (UDMS) and AI-enabled workflows across the clinical data lifecycle.

The company said the funding was its first equity capital raise since 2017. It has not disclosed a valuation or provided a detailed allocation of the proceeds.

Viking Global Investors, which manages more than $54 billion in capital across public and private investments, led the round. The investment firm said it sees an opportunity to modernise how the life sciences industry manages and uses clinical data.

Levi Malik, a principal at Viking Global Investors, said nPhase combines clinical research experience, knowledge of regulatory requirements and a strategy for deploying AI at enterprise scale.

Funding to accelerate nPhase’s enterprise platform

The investment follows nPhase’s September 2026 launch of nPhase.ai, an enterprise platform designed to connect clinical data management and statistical computing from the start of a clinical study through regulatory submission.

The platform brings together two principal components: UDMS, which manages and integrates clinical data from multiple sources, and SCE, which supports statistical programming and the preparation of regulatory submission materials.

Clinical trials generate data from a range of sources, including research sites, laboratories, patients and digital health devices. These systems can use different formats and processes, creating additional work for pharmaceutical sponsors when they need to consolidate, standardise and validate information.

nPhase says its platform is designed to bring these data streams into a governed environment, where information can be standardised and processed as it is generated. The company aims to reduce manual hand-offs and the need for extensive reconciliation towards the end of a study.

Its September platform launch announcement described the system as a way to connect clinical data management and statistical computing in a single workflow.

SCE targets faster regulatory submission preparation

A major focus of the funding is the expansion of nPhase’s Statistical Computing Environment.

The SCE is designed to transform raw clinical study data into standardised datasets, statistical analyses and other materials required for regulatory submissions. The system supports workflows involving clinical data standards, statistical programming and validation.

nPhase says its technology can reduce processes that typically take four or more months to a matter of weeks. The company has also claimed that its platform can generate submission-ready outputs at least four times faster while using fewer resources. These are company-reported performance claims rather than independently established industry-wide results.

The platform is built around standards developed by the Clinical Data Interchange Standards Consortium (CDISC), which are used to structure and exchange clinical research data.

According to nPhase, its SCE supports automated data mapping and statistical programming workflows, while maintaining traceability and audit records. The company’s product information also describes support for SAS, R and Python within a governed computing environment.

Agentic AI to automate clinical data workflows

The Series D investment will also accelerate nPhase’s development of agentic AI capabilities.

The company plans to use AI agents to perform operational tasks across the clinical data lifecycle, including identifying data discrepancies and preparing draft statistical programming work.

These capabilities are intended to reduce repetitive tasks and help clinical research teams process larger volumes of information. nPhase said human experts will retain decision-making authority over the work produced by the AI systems.

The distinction is important in clinical research, where data accuracy, traceability and regulatory compliance are central to the preparation of trial results and submissions.

The company’s platform materials describe governance, audit trails and human review as part of its approach to AI-enabled clinical workflows.

Viking Global identifies opportunity in clinical data technology

Viking Global’s investment reflects interest in technology businesses addressing operational challenges in the life sciences sector.

The investment firm said nPhase has an established foundation in clinical research and an understanding of regulatory requirements, which it considers important for enterprise AI adoption in the industry.

Viking Global reported managing more than $54 billion in capital across public and private investments as of 30 September 2026.

For nPhase, the new funding follows a period in which it has developed its clinical data management business without raising additional equity capital. The company said the Series D financing will support its next stage of expansion, including the development of its enterprise platform and AI capabilities.

Scott Climes, chief executive of nPhase, said the company had built a unified and governed data foundation for clinical research and would use the investment to expand intelligent workflows across the clinical data lifecycle.

AI adoption in clinical research creates demand for governed data

The funding highlights a growing technology requirement across pharmaceutical research: making clinical data usable for advanced analytics and AI applications.

Clinical trial information is generated across multiple systems and organisations. If data remains fragmented or inconsistent, it can be difficult to reuse across studies or incorporate into automated workflows.

Platforms that combine data management, standardisation, statistical computing and governance are seeking to address this challenge. Their potential value for pharmaceutical sponsors lies in reducing manual processing, improving data accessibility and supporting the preparation of regulatory submissions.

However, adoption in clinical research depends on more than automation. Systems must also provide reliable data provenance, validation, security and human oversight.

nPhase’s $30 million funding round will support its efforts to expand in this market. Its ability to convert its platform capabilities into wider enterprise adoption will be an important measure of the company’s progress.

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