From Code to Impact: MLOps, LLMOps, & GenAI Ops in Biopharma and Beyond

Industrial Problems Seminar

Lanhui Wang
Gilead Sciences

Abstract

Machine learning is changing everything in biopharma—from speeding up drug discovery to improving patient care. But a brilliant model in a notebook is just the start. To turn that code into real-world results that help patients or drive business, you need robust operational frameworks.

This talk will introduce you to MLOps, LLMOps, and GenAI Ops—the essential systems that enable machine learning to scale in high-stakes, regulated industries like healthcare. You'll learn:

• How MLOps pipelines make projects reproducible, accelerate development, and help teams meet strict compliance standards.
• Why LLMOps is critical for ensuring your large language models are transparent and trustworthy when deployed to a wide audience.
• How the emerging field of GenAI Ops unlocks new possibilities, from sifting through scientific literature for insights to generating marketing content and other commercial applications. This includes frameworks like the Model Context Protocol (MCP), which standardizes how AI applications connect to and use external data sources and tools, making it easier to build secure, context-aware systems.

Join us to see how these powerful tools are turning models into meaningful impact—whether it’s helping scientists find the next life-saving therapy or empowering business teams to make smarter, data-driven decisions.