AI Governance for Clinical Trials Training Course

Name: AI Governance for Clinical Trials and Research Training Course
Availability: InStock

Govern AI-supported trial design, recruitment, monitoring, safety, data, vendors, and research decisions through traceable controls.

AI Governance for Clinical Trials Training Course

At a glance

Duration: 5 days
Format: Classroom
Cities: Istanbul, Nice, Paris, Abu Dhabi, Manama, Accra and more
Next session: 5 – 9 October 2026, Istanbul
Average fee: 5,800 €

Home
Our Categories
AI Governance for Clinical Trials and Research Training Course

Download Brochure (PDF) Print PDF

Overview

AI Governance for Clinical Trials and Research Training Course is a five-day advanced course for clinical research managers, trial operations leaders, governance personnel, coordinators, data teams, assurance specialists, and sponsors, who leave with a Clinical Research AI Control Framework. Participants connect responsible AI in clinical research, clinical trial AI governance, protocol feasibility support, participant recruitment controls, and AI-assisted trial monitoring to data quality, human oversight, traceability, equity, and accountable decisions. Agile Leaders Training Center provides training in AI governance for clinical trials.

Who Should Attend

Clinical research leadership personnel responsible for study portfolios, operating models, and research outcomes
Trial operations personnel responsible for feasibility, sites, recruitment, monitoring, and delivery controls
Research governance personnel responsible for ethics, accountability, participant protection, and oversight
Clinical data personnel responsible for data quality, lineage, representativeness, and controlled analysis
Quality assurance personnel responsible for evidence, deviations, vendors, audits, and corrective actions
Research sponsorship personnel responsible for decisions, resources, risk acceptance, and external providers

The course assumes participants can manage clinical research processes and risk decisions, and it leaves out model coding, statistical programming, healthcare diagnosis, and medical device engineering.

Departments and Industries

The course supports clinical research governance across pharmaceutical development, biotechnology, contract research, academic research, healthcare institutions, and digital-health services.

Clinical development and trial operations
Research governance and ethics support
Clinical data management and biostatistics oversight
Quality assurance and risk management
Safety, medical monitoring, and participant protection
Research technology and vendor management

Learning Objectives

By the end of this course, participants will be able to:

Analyze clinical-research use cases and define accountable AI boundaries
Evaluate data fitness, representativeness, bias, and traceability
Apply controls to feasibility, recruitment, monitoring, and safety support
Build human-review, vendor, change, and incident governance
Prioritize performance, equity, quality, and participant-protection evidence
Build a clinical research AI control framework

Course Agenda

Day 1: Research Context and Accountability

Clinical Research AI Use-Case Inventory
Context-of-Use and Decision-Impact Canvas
ICH E6(R3) Quality and Accountability Mapping
Participant Rights and Human-Oversight Matrix
AI Governance Roles and Escalation Charter

Day 2: Data, Bias, and Trial Design Support

Protocol Feasibility Evidence Map
Site and Population Representativeness Review
Clinical Data Fitness and Lineage Checklist
Bias, Equity, and Subgroup Impact Assessment
AI-Assisted Trial Design Decision Record

Day 3: Recruitment, Monitoring, and Safety

Participant Identification and Recruitment Control Grid
Consent, Privacy, and Data-Minimization Review
Risk-Based Monitoring Prioritization Method
Safety Signal Triage and Human Review Route
Clinical Operations Exception and Override Log

Day 4: Assurance, Vendors, and Lifecycle Control

AI Vendor Due-Diligence Questionnaire
Performance, Drift, and Representativeness Dashboard
Model and Workflow Change-Control Register
Documentation Traceability and Audit-Evidence File
AI Incident Review and Corrective-Action Protocol

Day 5: Clinical Research Governance Practice

Suggested Exercise: Screen a Clinical Research AI Use Case
Suggested Exercise: Evaluate Data and Population Fitness
Suggested Exercise: Govern Recruitment and Monitoring Support
Suggested Exercise: Review Vendor, Change, and Incident Evidence
Capstone Exercise: Clinical Research AI Control Framework

Practical Exercises

The course uses suggested activities that turn clinical-research AI decisions into traceable governance artifacts.

Suggested activity: define context of use, decision impact, accountable roles, participant safeguards, and escalation points
Suggested activity: evaluate feasibility evidence, data lineage, population representation, subgroup effects, and design assumptions
Suggested activity: control recruitment, consent, monitoring priorities, safety-signal review, exceptions, and human overrides
Suggested activity: assemble vendor evidence, performance measures, change records, incident actions, and audit traceability

FAQs

Who suits AI governance for clinical trials, and what does the course assume?

AI governance for clinical trials suits research managers, trial operations leaders, governance personnel, coordinators, data teams, assurance specialists, and sponsors. The course assumes experience managing clinical research processes and risk decisions.

How does clinical trial AI governance differ from healthcare AI model validation?

Clinical trial AI governance controls research uses, participant impacts, trial workflows, vendors, human decisions, changes, incidents, and evidence, while healthcare AI model validation concentrates on evaluating a model's technical and clinical performance.

How should AI support participant recruitment in clinical trials?

AI recruitment support should use defined eligibility logic, fit-for-purpose data, fairness checks, privacy controls, documented exclusions, human confirmation, participant-sensitive communication, and monitoring for unequal access or burden.

What evidence supports AI-assisted trial monitoring?

AI-assisted trial monitoring requires traceable data, documented risk indicators, explainable priorities, reviewable alerts, human decisions, override records, performance checks, and evidence that monitoring remains proportionate to participant and data risks.

How should clinical research teams govern AI vendors and changes?

Clinical research teams should define responsibilities, assess vendor controls and data handling, establish performance and change thresholds, review updates before use, preserve version and decision records, monitor incidents, and maintain exit and continuity plans.

Conclusion

Participants take back a Clinical Research AI Control Framework linking use cases, data, participant safeguards, trial operations, vendors, human review, changes, incidents, evidence, and accountability. It changes how research teams move from isolated AI pilots to controlled lifecycle decisions. The framework supports traceability, proportionate oversight, equitable research practice, and auditable management action.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

Download Brochure (PDF) Print PDF

Showing 21-40 of 76 events

Location	Dates	Duration	Mode	Price
Vienna	Week 52, 2026 21 – 25 December 2026	5 Days	Onsite	€5,700
London	Week 53, 2026 28 December 2026 – 1 January 2027	5 Days	Onsite	€5,700
Riyadh	Week 53, 2027 3 – 7 January 2027	5 Days	Onsite	€5,700
Tbilisi	Week 02, 2027 11 – 15 January 2027	5 Days	Onsite	€5,000
Porto	Week 02, 2027 11 – 15 January 2027	5 Days	Onsite	€5,700
Vienna	Week 04, 2027 25 – 29 January 2027	5 Days	Onsite	€5,700
Abu Dhabi	Week 04, 2027 25 – 29 January 2027	5 Days	Onsite	€4,700
Zanzibar	Week 04, 2027 31 January – 4 February 2027	5 Days	Onsite	€5,500
Cairo	Week 05, 2027 1 – 5 February 2027	5 Days	Onsite	€4,100
Marbella	Week 05, 2027 7 – 11 February 2027	5 Days	Onsite	€5,700
Dubai	Week 06, 2027 8 – 12 February 2027	5 Days	Onsite	€4,500
Phuket	Week 06, 2027 14 – 18 February 2027	5 Days	Onsite	€6,000
Casablanca	Week 07, 2027 15 – 19 February 2027	5 Days	Onsite	€4,100
London	Week 08, 2027 22 – 26 February 2027	5 Days	Onsite	€5,700
Muscat	Week 08, 2027 28 February – 4 March 2027	5 Days	Onsite	€5,700
Zoom	Week 09, 2027 1 – 5 March 2027	5 Days	Online	€1,500
Manama	Week 09, 2027 7 – 11 March 2027	5 Days	Onsite	€4,700
Sharm El-Sheikh	Week 10, 2027 8 – 12 March 2027	5 Days	Onsite	€4,100
Chicago	Week 10, 2027 14 – 18 March 2027	5 Days	Onsite	€12,000
Geneva	Week 11, 2027 21 – 25 March 2027	5 Days	Onsite	€6,200

Frequently asked questions

What does this course cover?

OverviewAI Governance for Clinical Trials and Research Training Course is a five-day advanced course for clinical research managers, trial operations leaders, governance personnel, coordinators, data teams, assurance specialists, and sponsors, who leave with a Clinical Research AI Control Framework. Participants connect responsible AI in clinical research…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

AI Governance for Clinical Trials Training Course