Clinical Trial Management System

Part of the worlds-biggest-software-project initiative.

An AI-native, open-source platform for managing clinical trials from protocol design through regulatory submission.

The Clinical Trial Management System (CTMS) coordinates protocol management, patient enrollment, site activation, monitoring, and regulatory documentation for sponsors, CROs, and research sites. It targets the gap between expensive enterprise CTMS suites and lightweight site-only tools, and applies AI to the chronic problems of slow enrollment, manual monitoring, and document overhead.

Why Clinical Trial Management System?

Enterprise CTMS platforms (Medidata Rave, Veeva Vault, Oracle Clinical One) cost $500K–$2M+ per year and require 6–18 month implementations, putting them out of reach of emerging biotech, academic medical centres, and investigator-initiated trials.
The market is bifurcated: the only widely used non-commercial alternative, REDCap, is restricted by a Vanderbilt consortium licence to non-commercial academic use and cannot be embedded in commercial products.
OpenClinica Community Edition (LGPL-2.1) is the only practical open-source reference, but it lacks IRT/RTSM, AI features, and modern decentralised-trial support.
Roughly 80% of trials miss enrollment timelines, yet incumbents still rely on scheduled monitoring visits and manual TMF curation rather than continuous AI-assisted oversight.
Existing AI features in commercial tools (Medidata AI, Suvoda Sofia, Jeeva) are proprietary black boxes; regulators and sponsors increasingly need transparent, auditable AI decisions.

Key Features

Site, Subject, and Protocol Management

Site activation workflow with feasibility questionnaires, IRB/EC tracking, investigator delegation logs, and regulatory binders.
Subject enrollment management: screening logs, randomisation tracking, visit scheduling, and dropout capture.
Protocol deviation logging, ICH E6 category classification, and CAPA initiation.
Monitoring visit scheduling, findings capture, report generation, and follow-up tracking.
Role-based access control across sponsor, CRO, site coordinator, monitor, and investigator tiers.

Compliance and Regulatory Operations

21 CFR Part 11 and EU Annex 11 compliant audit trails and electronic signatures across all trial records.
ICH GCP E6(R3) workflow compliance.
eTMF document management mapped to the ICH TMF Reference Model milestone structure.
CDISC ODM data export for portability and regulatory submission support.
Safety reporting workflows aligned to ICH E2B(R3).

Financials and Site Operations

Site contract and budget templates with milestone payment tracking and CRO invoice reconciliation.
Investigational product accountability tracking.
Staff training and delegation logs.
Calendar-based visit scheduling with conflict detection and automated alerts for expiring documents.

Decentralised and Hybrid Trial Support

eConsent workflows for remote participants.
Telehealth visit capture and remote data ingestion via HL7 FHIR R4.
Wearable and remote monitoring device integration.
Patient-facing pre-screening flows mapped to protocol eligibility criteria.

AI-Assisted Analytics

AI-assisted patient eligibility screening from uploaded protocol inclusion/exclusion criteria.
Enrollment forecasting with predicted vs. actual trajectories by site and region.
Risk-based monitoring (RBM) scoring per site with automated review trigger alerts.
Natural language assistant for operational queries on enrollment status, supply levels, and visit windows.

AI-Native Advantage

AI capabilities are integrated into the core workflows rather than bolted on. The platform parses protocol eligibility criteria with LLMs and matches against EHR data via FHIR to surface candidate patients in real time, addressing the industry's chronic enrollment shortfall. AI agents continuously monitor decentralised data streams to flag protocol deviations, data anomalies, and safety signals between scheduled visits, while generative AI drafts and maintains TMF documents and informed consent forms from structured trial data. Predictive feasibility models score draft protocols for likely enrollment rate, site performance, and dropout risk before site activation, with transparent decision audit trails suitable for regulatory review.

Tech Stack & Deployment

The system is designed for self-hosted, cloud, and hybrid deployment so sponsors and CROs can satisfy data-residency and validation requirements. Standards adherence is a first-class concern: HL7 FHIR R4 for EHR integration, CDISC ODM and CDASH for data interchange, ICH E2B(R3) for safety reporting, and 21 CFR Part 11 / EU Annex 11 controls throughout. Integration is exposed through a REST API with connectors for EDC, IRT/RTSM, ePRO, telehealth, and wearable platforms. OpenClinica Community Edition (LGPL-2.1) is the recommended reference implementation for the EDC subsystem; REDCap must not be used as a code or data source due to its non-commercial licence.

Market Context

The global CTMS market was valued at approximately $2.35–2.44 billion in 2025 and is projected to reach $4.89–7.40 billion by 2030–2033, growing at a CAGR of 13–16% (Grand View Research; MarketsandMarkets; Straits Research). Enterprise CTMS pricing ranges from $500K–$2M+ per year for Veeva, Medidata, and Oracle, with implementation services often adding 50–100% of licence cost; mid-market and site-level tools span $5K–$300K per year. Primary buyers are pharmaceutical and biotech sponsors, CROs, academic medical centres, site management organisations, and medical device manufacturers running clinical studies.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.