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

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Mar 19, 2026

Guest

Fiachra Matthews

Fiachra Matthews, principal architect building Agent Studio infrastructure. Jen Brown, product manager improving trial workflows like ETMF and CRA. Luke Bates, product leader shaping platform strategy. They discuss Agent Studio’s platform approach, ETMF and CRA agents, RAG and context strategies, unified ontology mapping, MCP connectors, evaluation for GxP, and the vision for automating clinical trials.

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ADVICE

Make Agents Purpose Built Per Customer

Treat agents as purpose-built and per-customer because every trial is different and customers require isolated, configurable environments.
Build platform primitives so future agentic solutions reuse capabilities and speed delivery.

INSIGHT

Team Learned Agents By Doing Hands-On Experiments

Medable's team learned AI by experimentation and self-learning rather than formal ML backgrounds; internal culture encouraged rapid experiments.
Cross-functional roles (product, design, engineering) upskilled through reading papers, videos, and hands-on prototypes.

INSIGHT

Unified Ontology Eases Cross-System Retrieval

Medable is building an AI data layer that maps diverse systems into a unified ontology to simplify retrieval and cross-system queries.
They balance vectorized static data versus just-in-time MCP retrieval and layering summaries/hierarchies for context management.

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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