clinstead
AI agents

Agentic clinical operations.

Clinstead AI agents are not separate products. They are intelligent layers operating directly on the canonical model to reduce operational friction while maintaining clinical rigor.

Agents over structure. Not chat over chaos.

The framework

Observe → Recommend → Escalate.

Our agents follow a strict operational protocol designed for high-stakes clinical environments, ensuring human oversight is present where it matters most.

STEP 01

Observe

The agent maintains a continuous watch over the study's structured data, identifying patterns, anomalies and protocol deviations in real time.

STEP 02

Recommend

When a potential issue is detected, the agent drafts a recommendation — a query to a site, a structural adjustment, a resource reallocation.

STEP 03

Escalate

High-risk signals or complex clinical decisions are escalated to human leads (Lead CRA, PM, or Medical Monitor) with a full context brief.

Active agents

Eight agents over the operating model.

Each agent operates within a defined scope of the study — the data, the workflow, the audit trail, the participant journey — and routes high-risk decisions to humans.

Monitoring agent

sys_mon_01

Ranks sites by risk, detects monitoring triggers and prepares review queues.

Data management agent

sys_dm_02

Finds anomalies, prioritises cleaning work and recommends queries.

Query management agent

sys_qry_03

De-duplicates query candidates, routes queries and escalates stale items.

Reporting agent

sys_rpt_04

Drafts study status reports, site summaries and cleaning progress updates.

Participant management agent

sys_ptc_05

Detects missed tasks, dropout risk and rescue opportunities.

Amendment impact agent

sys_amd_06

Compares proposed versus active versions and shows affected forms, visits, sites, reports, integrations and participants.

Oversight agent

sys_ovs_07

Watches operational KPIs and surfaces deterioration before it becomes a crisis.

Integration agent

sys_int_08

Detects failed syncs, reconciliation issues and integration health problems.

Operating principles

The model. The rules. The audit. Humans.

Model

The model gives the agents context — protocol, forms, fields, logic, visits, queries, participants, amendments.

Rules

The rules give them boundaries — what they can read, draft, route and escalate; what requires human approval.

Audit

The audit trail gives them accountability — every recommendation, action and rationale is logged.

Humans

Humans keep control — high-risk study actions require human review and approval.

The point is not “AI-powered clinical trials.” The point is operational leverage — reducing the routine coordination burden that sits on trial managers, data managers, monitors and coordinators.

Human at the centre

Agents extend human capability — they do not replace it.