AI in Life Sciences

2025 pushed the life sciences industry into a new phase of AI adoption.
You saw the shift in three places.

R&D teams moved from experimenting with AI to depending on it for modeling and data interpretation.
Clinical and commercial teams embraced copilots, automated workflows, and faster access to information.
MedTech manufacturers invested heavily in AI-powered device intelligence, service automation, and predictive analytics.

The common thread was data.
Companies spent the year cleaning it, organizing it, and building the foundations needed to scale AI safely.
This included a renewed emphasis on FAIR data, better data governance, and new ways to combine scientific, operational, and commercial systems.

Automation also gained momentum.
Leaders used it to cut time spent on documentation, reduce manual processes, and tighten quality controls. The most successful organizations blended AI with strong operational discipline, domain expertise, and real-time data.

This roundup highlights the news, research, and platform advancements that caught our attention here at Smartbridge, and shows where life sciences is heading next.

FAIR Data Gets Real in 2025

Teams made meaningful progress turning scattered data into something findable, usable, and trusted. FAIR data principals (Findable, Accessible, Interoperable, and Reusable) became less of a theory and more of a working model for R&D and quality teams.

Articles and Resources

Salesforce Expands Its Life Sciences Footprint

Salesforce doubled down on industry-specific data integration, patient engagement, and commercial enablement. This gave MedTech and biopharma leaders new ways to unify systems without building everything from scratch.

Articles and Resources

AI for R&D and Pharma Innovation

AI continued reshaping how scientists explore new molecules, analyze results, and interpret complex datasets.
Teams shifted from pilots to production.

Articles and Resources

AI for Clinical and Healthcare Operations

AI copilots gained ground as documentation tools, assistants, and workflow accelerators. Care teams used them to retrieve information faster and reduce manual tasks that slow down decision-making.

AI in MedTech and Commercial Operations

MedTech manufacturers accelerated their use of AI to enhance device intelligence, strengthen service models, and improve commercialization. It became a core strategy, not a side experiment.

Articles and Resources