Domino Data Lab and EPAM have formed a strategic partnership aimed at helping life sciences organisations move AI applications from experimental environments into validated production across biopharmaceutical research and development.
The collaboration combines Domino’s enterprise AI platform with EPAM’s engineering and life sciences expertise. The companies will focus on deploying governed analytics and GxP-validated AI models within existing enterprise technology environments.
Addressing barriers to life sciences AI adoption
Life sciences companies are increasingly exploring artificial intelligence across drug discovery, clinical development and data analysis. However, moving experimental models into regulated production environments remains challenging.
According to Domino, fragmented legacy systems, GxP revalidation requirements and governance are among the barriers organisations face when scaling AI.
The partnership will see EPAM’s integration teams work alongside Domino specialists to integrate AI capabilities into existing IT architectures. This includes modernising legacy code and supporting compliance requirements during deployment.
“Pharma’s AI opportunity doesn’t live in one function, and every team it touches has its own systems, timelines, and compliance requirements,” said Greg Killian, Senior Vice President and Global Head of Life Sciences and Healthcare at EPAM.
“EPAM and Domino are built for that complexity, helping organisations move AI into validated production no matter which team is building it.”
Partnership targets AI across biopharma R&D
The companies plan to support several applications across the biopharmaceutical lifecycle, including discovery and target identification.
Researchers could use AI agents, large language models and machine learning pipelines to analyse large genomic datasets and support candidate selection.
The partnership will also target statistical computing. Domino and EPAM intend to provide governed environments where biostatisticians and statistical programmers can work across SAS, R and Python during analysis and regulatory submission workflows.
Real-world evidence and governed analytics
Real-world evidence is another focus. The companies plan to support analysis of large and heterogeneous real-world datasets through secure, standardised analytics environments.
Domino’s existing life sciences platform supports workflows spanning discovery, preclinical research, clinical development, manufacturing and commercial operations.
The company also provides infrastructure designed to support GxP compliance, including the development, validation and operation of computerised systems used in regulated environments.
“Life sciences leaders don’t want AI that only works for one pilot,” said Ricky Mann, Chief Solutions Officer at Domino. “Pairing EPAM’s implementation experience with Domino’s platform lets leaders scale AI solutions enterprise-wide, not just within a single function.”
Moving AI from pilots into production
The agreement reflects a broader industry focus on moving artificial intelligence beyond individual proof-of-concept projects and into governed operational environments.
For pharmaceutical and biotechnology organisations, this requires AI infrastructure to operate alongside established regulatory, data governance and validation processes.
Domino and EPAM said their combined approach is intended to support this transition across multiple functions rather than restricting AI deployment to individual research teams.
More information about Domino’s work in the sector is available through its life sciences platform.
