Bristol Myers Squibb Reinforces Its Research Stack

Over the past week, Bristol Myers Squibb disclosed two research partnerships. One involves applying AI to the analysis of immune data from clinical trials. The other extends a decades-long research collaboration that underpins discovery and development activities.

The company, which operates a broad global R&D organization, has been expanding its use of artificial intelligence across drug discovery, clinical research, and data analysis, positioning analytics as a core part of its research model.

Applying AI to Clinical Immune Data

The first announcement was a collaboration with Immunai, a biotechnology company that develops machine-learning systems for immune system analysis. Under the agreement, Bristol Myers Squibb will use Immunai’s AMICA-OS platform to analyze single-cell and multi-omic immune data generated in its clinical trials.

According to the companies, the collaboration is intended to support patient stratification, biomarker identification, and analysis of mechanisms of action across Bristol Myers Squibb’s clinical programs. The agreement is not tied to a specific asset and is designed to be applied across studies where immune data is collected.

Immunai’s platform aggregates immune datasets and applies machine-learning models to identify patterns across patient populations. This type of analysis is commonly used in immunology and oncology research to examine variability in treatment response and to inform subsequent trial design.

Bristol Myers Squibb has previously stated that artificial intelligence is being integrated into multiple stages of research and development. Greg Meyers, executive vice president and chief digital and technology officer, said in a McKinsey interview that technology now operates “on the same footing as R&D,” describing how digital systems are embedded into core scientific workflows rather than used as peripheral tools.

The Immunai collaboration follows other AI-related partnerships by Bristol Myers Squibb, including work in drug discovery and translational research. In this case, the focus is on interpreting immune data generated during clinical trials rather than on generating new drug candidates.

Extending a long-term external research partnership

Several days later, Bristol Myers Squibb announced that it had extended its research collaboration with Syngene International through 2035. The partnership began in 1998 and supports a range of research and development activities across Bristol Myers Squibb’s pipeline.

Under the agreement, Syngene provides services spanning discovery sciences, translational research, pharmaceutical development, manufacturing support, clinical trial operations, and data and information technology. The collaboration includes work conducted at the Biocon Bristol Myers Squibb Research and Development Center in Bangalore, which was commissioned in 2009.

The Bangalore center employs several hundred scientists who work on Bristol Myers Squibb research programs across therapeutic areas including oncology, immunology, cardiovascular disease, and fibrosis. The extended agreement establishes a long planning horizon for staffing, infrastructure, and research execution.

Bristol Myers Squibb has used dedicated external research centers as part of its global R&D model for more than two decades. The Syngene partnership functions as a long-term, integrated research arrangement rather than a short-term services contract.

Company statements around the extension emphasized continuity across research and development stages rather than individual programs. The agreement does not specify assets and applies broadly to supporting research activities over time.

Recent context within Bristol Myers Squibb’s R&D approach

Bristol Myers Squibb leadership has consistently described data, modeling, and artificial intelligence as tools used to inform research decisions earlier in development. Robert Plenge, executive vice president and head of research, has referred to this framework as “Predict First,” describing it as the use of predictive analytics to help prioritize programs before advancing them further.

Plenge has said the approach is applied across discovery and development, particularly in areas such as immunology and oncology where biological systems are complex and clinical outcomes can vary significantly between patients.

The Syngene extension reflects the operational side of that strategy. The agreement secures external research capacity across multiple stages of development through 2035, formalizing more than 25 years of collaboration. According to public disclosures, the partnership spans discovery, translational research, pharmaceutical development, manufacturing support, and clinical operations.

Greg Meyers has said that digital capabilities, including analytics and AI, are integrated into how research teams operate rather than treated as standalone initiatives. In public comments, he has framed these systems as part of the same operational layer as R&D itself.