Building Agent Studio: How Medable Is Using Agentic AI to Accelerate Clinical Trials - podcast episode cover

Building Agent Studio: How Medable Is Using Agentic AI to Accelerate Clinical Trials

Mar 19, 20261 hr 6 minEp. 21
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Episode description

Guests

  • Luke Bates, Product Leader (Agent Studio), Medable
  • Jen Brown, Product Manager, Medable
  • Matt Schoolfield, Product Designer, Medable
  • Fiachra Matthews, Principal Architect, Medable

What we cover in this episode:

  • What Medable does: enabling global clinical trials across 100+ languages and accelerating drug-to-market timelines
  • The two agents built on Agent Studio—ETMF (document classification) and CRA (clinical data monitoring)—and the problems they solve
  • Why Medable chose a platform approach to agents instead of one-off builds
  • How Agent Studio works: models, skills, knowledge bases, MCP connectors, versioning, and trigger types
  • Three deployment models: Medable-built products, services-led custom builds, and self-serve platform access
  • RAG approaches at scale: embeddings vs. markdown hierarchies vs. just-in-time MCP retrieval
  • How they built a unified ontology layer to map terminology across 13 different clinical data systems
  • Why they built custom MCPs with an authentication and credentialing wrapper
  • Context window management with sub-agents and automatic tool filtering
  • Evaluation design in a GXP-regulated environment: golden datasets, production monitoring, and the challenge of human feedback as ground truth
  • How they document agent intent → specification → test evidence to satisfy regulatory bodies
  • The "full self-driving" vision for clinical trials and what it would take to get there

Resources & Links

  • Medable - Clinical trial platform powering Agent Studio

Chapters 00:00 Meet The Medable Team
01:14 Medable Mission And Scope
03:27 Agent Studio Platform Overview
06:29 ETMF Document Automation
08:47 CRA Agent For Monitoring
10:40 Clinical Trial Workflow Primer
14:34 Why Build A Platform
17:51 Learning AI As A Team
21:47 Early Days Of Agent Studio
23:15 How Agents Are Built
25:15 Customer Adoption And UX
30:00 Skills And MCP Standards
31:15 Scaling Context Retrieval
33:07 RAG Patterns And Tradeoffs
34:48 Ontology Data Layer Explained
38:01 Customer Friendly Agent Setup
42:19 MCP Security And Connectors
44:36 Tool Bloat And Subagents
50:44 Evals For Reliable Agents
54:40 Human Feedback Isn’t Truth
57:43 GXP Compliance For Agents
01:03:34 Full Self Driving Trials

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