# Scaling Agents in Healthcare & Life Sciences: Lessons from Madrigal Pharmaceuticals, Abridge, and Vizient

DevFeed: [Scaling Agents in Healthcare & Life Sciences: Lessons from Madrigal Pharmaceuticals, Abridge, and Vizient](<https://devfeed.tech/articles/scaling-agents-in-healthcare-life-sciences-lessons-from-madrigal-pharmaceuticals-abridge-and-vizient-78355.md>)

Original publisher: [Read original article](<https://www.langchain.com/blog/scaling-agents-in-healthcare-life-sciences-lessons-from-madrigal-pharmaceuticals-abridge-and-vizient>)

Author: Jess Ou

Published: 2026-09-16T15:55:03Z

Content type: article

Language: en

Sources: [LangChain Blog](<https://devfeed.tech/sources/langchain-blog.md>)

Topics: [LLM observability](<https://devfeed.tech/topics/llm-observability.md>), [Multi Agent Systems](<https://devfeed.tech/topics/multi-agent-systems.md>), [observability](<https://devfeed.tech/topics/observability.md>), [hierarchical agent systems](<https://devfeed.tech/topics/hierarchical-agent-systems.md>), [Deployment Strategies](<https://devfeed.tech/topics/deployment-strategies.md>), [supervisor agent pattern](<https://devfeed.tech/topics/supervisor-agent-pattern.md>), [Continuous integration](<https://devfeed.tech/topics/continuous-integration.md>), [AI Integration Strategies](<https://devfeed.tech/topics/ai-integration-strategies.md>), [ai security](<https://devfeed.tech/topics/ai-security.md>), [LLM security](<https://devfeed.tech/topics/llm-security.md>), [development-process](<https://devfeed.tech/topics/development-process.md>), [AI Chat](<https://devfeed.tech/topics/ai-chat.md>)

Tags: [a-b-testing](<https://devfeed.tech/tags/a-b-testing.md>), [access-controls](<https://devfeed.tech/tags/access-controls.md>), [agents](<https://devfeed.tech/tags/agents.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [audit](<https://devfeed.tech/tags/audit.md>), [authorization](<https://devfeed.tech/tags/authorization.md>), [automated](<https://devfeed.tech/tags/automated.md>), [data](<https://devfeed.tech/tags/data.md>), [healthcare-life-sciences](<https://devfeed.tech/tags/healthcare-life-sciences.md>), [manual-review](<https://devfeed.tech/tags/manual-review.md>), [resolved](<https://devfeed.tech/tags/resolved.md>)

## AI overview

The article describes how Madrigal Pharmaceuticals, Abridge, and Vizient operate AI agent systems in healthcare and life sciences. It highlights shared needs for observability, evaluation, governance, and cost control, then details their approaches to agent orchestration, production evaluation, deployment, and clinical or enterprise trust.

## Source excerpt

Agent programs in healthcare and life sciences are being built under a different set of constraints than those in most industries. There's plenty of upside if the constraints can be resolved. Success can mean hours of manual review compressed into minutes, data spread across a dozen systems finally queryable in one place, and clinicians getting time back from documentation. At the same time, the cost of a wrong answer can be higher here than almost anywhere else, which changes how teams build.