OVERVIEW

Welcome to the Future of Clinical Data Management training.​

Real-world EDC systems, query management, and database operations

Available in two formats: 3-Month Accelerator | 6-Month Deep Dive

Fully online. Self-paced. Start immediately.

This program trains you to manage clinical trial data, operate Electronic Data Capture (EDC) systems, execute query workflows, and perform database operations the way they're actually practiced in contract research organizations, pharmaceutical companies, and clinical trial data management units worldwide.

You'll work inside simulated clinical data environments where you handle real trial data scenarios, use industry-standard EDC platforms, and execute data management procedures under realistic regulatory conditions. By the end, you can demonstrate documented competence in the core functions clinical data management operations need from day one.

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What You'll Actually Learn

Foundations of Clinical Data Management

You start with CDM fundamentals: understanding what clinical data management is, the clinical trial data lifecycle from collection to lock, key CDM roles and responsibilities, Good Clinical Data Management Practices (GCDMP), introduction to EDC systems, AI applications in data research, data documentation essentials (CRFs, DCFs, logs), regulatory standards for CDM (ICH, FDA), MedDRA basics for data coding, and introduction to the ZANE Omega Data Management Lab.

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Case Report Form (CRF) Design & Build

You'll master CRF creation: CRF design principles and structure, paper versus eCRF comparison, building eCRFs in EDC systems (OpenClinica simulations), AI-assisted CRF validation, CRF annotation standards, designing data entry fields with logic, handling CRF amendments, CRF testing and quality checks, ensuring patient data privacy (GDPR/HIPAA compliance), and the CRF approval process.

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Electronic Data Capture (EDC) Systems

You'll operate EDC platforms: EDC systems overview (Medidata Rave, OpenClinica), EDC setup and configuration, data entry in EDC systems, AI-powered EDC data validation, user roles and access management in EDC, maintaining EDC audit trails, handling EDC errors and troubleshooting, EDC integration with other systems (CTMS), EDC reporting basics, and EDC system validation (21 CFR Part 11 compliance).

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Data Cleaning & Query Management

You'll execute data quality workflows: data cleaning overview and principles, Source Data Verification (SDV), AI-driven discrepancy detection, query generation processes, query resolution workflows, manual versus automated queries, data cleaning metrics and tracking, handling missing data, query escalation procedures, and query closure with documentation.

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MedDRA Coding & SAE Reconciliation

You'll code and reconcile safety data: MedDRA coding overview and hierarchy navigation, coding adverse events to MedDRA terms, AI-assisted coding accuracy validation, SAE (Serious Adverse Event) reconciliation basics, complex case coding with multiple events, SAE narrative validation using NLP tools, AI-powered SAE discrepancy detection, managing MedDRA version updates, tracking SAE reporting timelines, and building SAE reconciliation dashboards.

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Edit Check Programming & Validation

You'll program data validation rules: edit check programming overview and logic, building edit checks in EDC systems, AI-generated edit check suggestions, testing edit checks in simulations, handling edit check failures, creating dynamic adaptive checks, edit check documentation standards, ensuring regulatory compliance in checks, scaling edit checks for multi-site trials, and tracking edit check performance metrics.

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Data Reconciliation & Integration

You'll synchronize data across systems: data reconciliation overview and workflows, lab data reconciliation, AI-powered discrepancy resolution, cross-system data integration (EDC with CTMS), SAE versus AE log reconciliation, external data integration from third-party sources, reconciliation reporting, handling reconciliation errors, data mapping standards, and maintaining reconciliation audit trails.

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Database Lock & Regulatory Reporting

You'll execute database closure: database lock overview and process, pre-lock data cleaning procedures, AI-assisted lock validation, lock documentation standards, regulatory reporting basics and preparation, handling post-lock queries, audit preparation for locked databases, managing post-lock data updates, formatting data for regulatory submissions, and tracking lock performance metrics.

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Data Quality & Audits

You'll ensure quality and audit readiness: data quality standards and metrics, AI-powered quality assurance validation, audit preparation overview and checklists, handling audit findings with CAPA development, AI-based audit trail validation, mock CDM audit simulations, regulatory compliance in CDM (FDA/EMA alignment), tracking data quality KPIs, continuous quality monitoring with AI alerts, and post-audit reporting.

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Advanced AI in Clinical Data Management

You'll integrate cutting-edge technology: AI for automated data cleaning, Natural Language Processing (NLP) for data query analysis, predictive analytics for forecasting data issues, AI-driven edit check automation, blockchain for data integrity and audit trails, AI ethics in CDM and bias auditing, real-world evidence analysis in CDM, AI for global data integration, future CDM trends including digital twins, and integrating AI with EDC and CTMS systems.

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Cross-Functional CDM Operations

You'll coordinate across trial teams: cross-functional CDM overview and team roles, CDM-clinical team coordination, CDM-regulatory integration for submissions, AI-assisted team communication, multi-site data management, generating CDM metrics for stakeholders, handling cross-functional queries, data sharing standards and compliance, cross-functional audit preparation, and scaling CDM operations.

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Capstone Integration & Career Preparation

You'll complete the full CDM lifecycle: comprehensive CDM lifecycle review, advanced CDM simulation strategies, building CDM portfolios with documented work, interview preparation for CDM roles, professional networking in clinical data management, AI-driven career planning and advancement, case studies of CDM success, handling CDM crises and data issues, understanding emerging CDM regulations, and final CDM capstone simulation leading a multi-site trial data lock.

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Systems You'll Use

Training includes hands-on work with the tools and systems used in clinical data management operations:

• EDC platforms (Medidata Rave, OpenClinica, Oracle Clinical simulations)

• AI-assisted query builders

• Discrepancy detection and tracking systems

• MedDRA autocoding tools

• CRF design and building platforms

• Edit check programming engines

• Data reconciliation automation tools

• Database lock validation systems

• Audit trail management tools

• Statistical analysis tools for data quality

• Cross-system integration platforms (EDC-CTMS)

• NLP systems for query and narrative analysis

• Predictive analytics for data issue forecasting

AI tools are integrated throughout—you'll learn to use them for automated discrepancy detection, query generation, coding validation, and edit check logic. This mirrors how modern clinical data management professionals actually work.

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Career Outcomes

Graduates are prepared for these clinical data management roles:

• Clinical Data Coordinator / Associate

• Data Management Executive

• Query Management Specialist

• SAE Reconciliation Analyst

• Data Coding & Review Specialist

• Clinical Data Quality Officer

• eCRF Build Specialist

• Edit Check Programmer (Entry-Mid level)

• Database Administrator (Clinical Trials)

• Data Validation Analyst

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Contract research organizations, pharmaceutical companies, biotechnology firms, and clinical trial data management service providers actively recruit candidates with documented CDM competencies. This training provides that documentation.

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Ready to start? Enroll now and begin immediately.