Under a new strategic collaboration, Bristol Myers Squibb will deploy Evinova’s AI-native Study Designer platform to optimize trial design, improve decision-making, and drive efficiencies across its global clinical portfolio.
Evinova has entered into a strategic collaboration with Bristol Myers Squibb aimed at applying artificial intelligence (AI) to improve the design and execution of clinical trials, the companies announced this week.1
As part of the agreement, Bristol Myers Squibb will deploy the Cost Optimizer module within Evinova’s Study Designer platform across its global development portfolio. The AI-enabled tool is intended to support insight-driven decision-making, identify productivity opportunities, and enable more efficient trial designs with the goal of accelerating timelines and improving experiences for sites and patients.
Evinova’s platform uses agentic AI to support study design and integrates standardized digital data flows aligned with USDM standards. According to the company, the system also incorporates governance controls and safeguards to support the responsible use of AI in clinical development and has been deployed at global scale, delivering multi-year cost savings for customers.
In a press release, Cristina Duran, president of Evinova said: “Drug development is changing rapidly, and life science companies need partners who bring both AI leadership and clinical development expertise to successfully drive transformation. Evinova, founded by pharma for pharma, combines AI innovation with deep industry insight to reimagine clinical development. We’re thrilled to collaborate with Bristol Myers Squibb to drive efficiencies in drug development and accelerate breakthroughs for patients.”
Bristol Myers Squibb framed the partnership as part of a broader effort to address long-standing inefficiencies in drug development.
“Transforming clinical development is not just an opportunity; it is an urgent necessity,” added Cristian Massacesi, MD, EVP, chief medical officer & head of development at Bristol Myers Squibb, in the press release. “For years, developing medicines has taken too long, cost too much money, and mostly resulted in failure. Digital tools and AI can help us overcome these limitations and lay the foundation for better health outcomes for countless individuals in the years to come. The decisions we make now will shape the future of medicine, accelerate progress and ensure that the benefits of scientific advancement reach those who need them most.”
Beyond trial design optimization, Evinova’s platform also includes its Unified Trial Solution, which connects study components such as electronic clinical outcome assessments, telehealth, and remote patient monitoring into a single digital environment. The company said the approach is designed to reduce operational friction for sponsors and sites while supporting data collection for novel endpoints and decentralized trial models.
Financial terms of the agreement were not disclosed.
Earlier in November, Evinova and the Tufts Center for the Study of Drug Development (CSDD) shared findings from a survey of 387 investigative site professionals through an Applied Clinical Trials feature
Key findings included:
Bristol Myers Squibb’s collaboration with Evinova comes on the heels of another new partnership with Microsoft to advance AI-driven early detection of lung cancer.2
Through the digital health collaboration, FDA-cleared radiology AI algorithms will be deployed via Microsoft’s Precision Imaging Network, part of Microsoft for Healthcare radiology solutions. The network is already used by more than 80% of US hospitals to share medical imaging and access third-party AI tools, enabling broad integration of AI into routine radiology workflows.
The AI capabilities can automatically analyze X-ray and CT images to help identify lung disease, including hard-to-detect lung nodules, supporting radiologists while helping reduce clinical workload. The tools are designed to surface potential lung cancer cases earlier and help triage patients into appropriate care pathways, including those for non-small cell lung cancer.
The collaboration also addresses care continuity challenges, particularly for patients with incidental findings who are frequently lost to follow-up. Workflow management tools are intended to track patients through diagnostic and care pathways and support more consistent follow-up.
A core objective of the initiative is to expand access to early detection in medically underserved populations, including rural hospitals and community clinics. Bristol Myers Squibb said the strategy aligns with its broader health equity goals by applying scalable AI technologies to support earlier diagnosis and improve outcomes in resource-limited settings.
1. Evinova and Bristol Myers Squibb Forge Strategic Collaboration to Optimize Clinical Development with Artificial Intelligence. News release. Evinova. February 9, 2026. Accessed February 10, 2026.
2. Bristol Myers Squibb Announces Collaboration with Microsoft to Advance AI-Driven Early Detection of Lung Cancer. News release. Bristol Myers Squibb. January 20, 2026. Accessed February 10, 2026.
