Certified AI Bioethics & Regulatory Compliance Specialist (CAIBRCS) Certification Program by Tonex
Biomedical AI is reshaping diagnostics, therapeutics, and population health. CAIBRCS equips professionals to design and operate AI systems that meet ethical expectations and regulatory requirements worldwide. You will learn how FDA, EMA, and the EU AI Act intersect with HIPAA and GDPR, and how these frameworks guide lifecycle decisions for clinical AI. The program emphasizes defensible governance for genomic and patient data, with practical methods for consent, provenance, and risk management.
We cover explainability, transparency, and robust documentation so models remain trustworthy across updates. Cybersecurity is addressed as a core safety obligation: you will align privacy, access controls, and model integrity with security-by-design. You will also learn to audit pipelines, track changes, and respond to findings with traceable actions. Graduates are prepared to lead cross-functional compliance programs, evaluate vendor claims, and support submissions and inspections. The result is safer AI, fewer surprises, and faster, compliant innovation.
Learning Objectives:
- Interpret FDA, EMA, and EU AI Act requirements for clinical AI.
- Map HIPAA and GDPR obligations to data and model workflows.
- Identify and mitigate bias, safety, and consent risks.
- Govern genomic and patient datasets with provenance and quality controls.
- Implement explainability, audit trails, and change management.
- Integrate cybersecurity controls into AI risk management.
- Establish an AI governance operating model and metrics.
- Prepare documentation for reviews, filings, and inspections.
Audience:
- Regulatory Affairs and Compliance Leaders
- Clinical AI Product Managers
- Data Protection Officers and Privacy Counsel
- Health IT Architects and Solution Owners
- Bioinformatics and Data Science Leads
- Quality, GxP, and Clinical Operations Professionals
- Cybersecurity Professionals
- Vendor Managers and Procurement Teams
Program Modules:
Module 1: Bioethics Foundations for Biomedical AI
- Core principles: autonomy, beneficence, non-maleficence, justice
- Human oversight and accountability structures
- Consent models for AI-enabled care and research
- Equity for pediatrics, rare disease, and underserved groups
- Dual-use, misuse, and harm minimization strategies
- Ethical risk registers and review boards
Module 2: Global Regulatory Landscape (FDA, EMA, EU AI Act, HIPAA, GDPR)
- FDA SaMD/ML-enabled device guidance and PCCP
- EMA expectations and MDR/IVDR alignment for AI
- EU AI Act risk classes, obligations, and provider roles
- HIPAA Privacy/Security Rule mapping to AI pipelines
- GDPR lawful bases, DPIAs, and data subject rights
- Cross-border transfers, SCCs, and adequacy decisions
Module 3: Data Governance for Genomic & Patient Data
- Sensitivity of omics data and dynamic consent models
- De-identification limits and re-identification risks
- Data minimization, purpose limitation, retention
- Data quality, lineage, and metadata standards
- Federated learning and privacy-enhancing techniques
- Data sharing agreements and DUAs that hold up
Module 4: Risk, Bias, Consent, and Clinical Safety
- Bias detection metrics and mitigation strategies
- Fairness across demographic and clinical subgroups
- Informed consent in AI-driven trials and care pathways
- Safety cases, clinical validation, and performance drift
- Adverse impact assessment and documentation
- Security controls for data/model confidentiality and integrity
Module 5: Auditability, Traceability, and Explainability
- Model cards, datasheets, and technical documentation
- End-to-end audit logs and version traceability
- Explainability for clinicians and regulators
- Post-market surveillance and change control
- Algorithmic impact assessments and recordkeeping
- GxP/CSV expectations for AI systems
Module 6: Operational Compliance and Governance Execution
- AI governance operating model, RACI, and decision rights
- Vendor due diligence and third-party risk controls
- Continuous monitoring, KPIs, and reporting
- Incident response, breach notification, and remediation
- Submission readiness and inspection playbooks
- Program roadmaps and maturity assessments
Exam Domains:
- Regulatory Strategy and Filing Readiness
- Algorithmic Fairness and Bias Assessment
- Health Data Governance & Stewardship
- Model Risk Management and Validation
- Clinical Safety and Post-Market Monitoring
- Ethical Decision-Making in AI-Enabled Care
Course Delivery:
The course is delivered through lectures, interactive discussions, structured workshops, and project-based learning, facilitated by experts in Certified AI Bioethics & Regulatory Compliance Specialist (CAIBRCS). Participants gain access to online resources, curated readings, case studies, and guided practice materials.
Assessment and Certification:
Participants are assessed via quizzes, targeted assignments, and a capstone project. Upon successful completion, learners receive a Tonex certificate in Certified AI Bioethics & Regulatory Compliance Specialist (CAIBRCS).
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified AI Bioethics & Regulatory Compliance Specialist (CAIBRCS) Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to lead compliant, ethical biomedical AI? Enroll with Tonex and build trustable systems that pass scrutiny and scale safely. Let’s get you certified.