Agentic Assistant

Agentic Assistant is a multi-agent AI assistant built natively into the Clinion EDC platform. It allows clinical trial teams — including sponsors, CROs, clinical operations, data management, and medical monitoring staff — to query protocol documents, operational metrics, and live clinical data through natural language, without requiring SQL knowledge or technical training. The assistant is available from the moment a study is created and requires no manual configuration.

Clinion serves sponsors and CROs running trials across more than 20 countries. Agentic Assistant is embedded directly in the Clinion EDC, meaning it accesses the same live data source that teams use for data entry, with no middleware, connectors, or synchronisation delays.

How It Works

1. Ask: The user types a question in plain natural language — no query syntax or special commands required.
2. Classify: An intent classifier determines whether the question relates to protocol knowledge, operational metrics, or clinical data.
3. Route: The question is routed to the appropriate specialised agent — Protocol Intelligence, Operations Insights, or Clinical Data — each with its own Retrieval-Augmented Generation (RAG) pipeline and data access layer.
4. Respond: The user receives a formatted answer with traceable sources. Results can be exported to Excel or saved as an image.

Protocol Intelligence

• Automatically generates a study-specific knowledge base when a protocol is uploaded, indexing eligibility criteria, endpoints, visit schedules, procedures, prohibited medications, SAE timelines, and amendment histories.
• Returns citation-backed answers with full traceability to the original protocol section.
• Supports questions such as summarising efficacy endpoints, listing assessment timepoints, extracting prohibited medications, and checking whether enrolled subjects have taken them.
• Protocol questions that previously required 15–20 minutes of manual document searching are answered in seconds.

Operations Insights

• Connects to an operational metadata RAG containing enrollment structures, visit schedules, deviation categories, site performance parameters, and operational KPIs.
• Dynamically calculates metrics including enrollment velocity, visit completion rates, query aging, site-level comparisons, and data entry lag from live EDC data.
• Returns results formatted as summaries, tables, or trend comparisons without requiring pre-configured dashboards or report requests.
• Supports follow-up questions to drill deeper into any metric, such as site-wise enrollment, screen failure rates, dropout trends, and protocol deviation categorisation by site.

Clinical Data Querying

• Uses an EDC metadata RAG that includes CRF structures, field definitions, visit and variable mappings, controlled terminology, and validation rules to convert natural language prompts into validated queries against live study data.
• Returns formatted tables, counts, and summaries without requiring SQL or database expertise.
• Supports complex queries such as fetching subjects with ALT/AST above three times the upper limit of normal who also reported adverse events within the same visit window, or counting subjects with Grade 3 or higher adverse events at a specific visit.
• Results are exportable to Excel with one click or saveable as images for reports and presentations.

Exportable Reports

• Data tables can be exported to Excel for further analysis.
• Responses can be saved as images for use in team meetings or monitoring reports.
• Users can build a library of saved queries that can be rerun as the study progresses.
• Every output is audit-traceable, linked to the user, timestamp, and underlying data source.

Role-Based Dashboard

• Provides a live study dashboard tailored to the user's role, displaying enrollment KPIs, data quality alerts, and operational risk flags.
• Dashboard data is updated in real time from the EDC.
• Users can identify items requiring attention and then use the assistant to investigate further.

Enterprise Compliance and Security

• Study-level data isolation ensures that one study's data, documents, and configurations are not accessible from another study.
• Role-based access controls restrict users to data they are authorised to view.
• All interactions are logged with a complete audit trail.
• Aligned with 21 CFR Part 11, EU Annex 11, HIPAA, and GDPR requirements.
• All data processing remains within the study's security perimeter.

Key Reported Benefits

• Data retrieval and report generation time reduced by over 80%, according to Clinion.
• Non-technical users can generate complex datasets directly without depending on data managers, programmers, or SQL experts.
• Clinical operations, data management, and medical monitoring teams share a single interface, reducing version conflicts across departments.
• All responses are drawn from validated data sources with audit traceability, supporting GxP and 21 CFR Part 11 alignment without additional compliance retrofitting.
• The modular agentic architecture is designed to support future expansion into predictive analytics, automated data quality checks, safety monitoring, and risk-based monitoring.

Agentic Assistant is built on Responsible AI principles covering accountability, transparency, privacy and security, reliability and safety, and fairness. It requires zero setup time for new studies — the knowledge base is generated automatically upon study creation in the Clinion platform, with no manual training, prompt engineering, or configuration needed.