This course provides technicians and other life-science professionals with a practical, regulatory-aligned introduction to Quality Risk Management (QRM) as applied to pharmaceutical, biologic, and medical product manufacturing. Participants learn regulatory expectations (21 CFR, ICH Q9, ICH Q10), core QRM principles, structured risk assessment methodologies, and how risk management integrates into the Pharmaceutical Quality System (PQS). Emphasis is placed on applying risk tools such as risk matrices and FMEA to real-world scenarios, linking risk assessment to decision-making, and developing clear, defensible documentation aligned with regulatory expectations. The course also introduces the role of artificial intelligence (AI) in QRM, including its use in data analysis, risk detection, and decision support, along with key considerations for validation, oversight, and data integrity in regulated environments. The course concludes with a final module on facilitating risk assessments, emphasizing the facilitator’s role in preparing for assessments, managing discussion dynamics, addressing bias and scoring disagreements, capturing rationale, and supporting clear, defensible team decisions.
- Manufacturing/Production Operators
- Team Leaders and Supervisors
- Quality Control Personnel
- Quality Assurance Personnel
- Process Development Scientists
- Validation/Engineering Personnel
- Technical Support Staff
- Introduction to Quality Risk Management
- Regulatory Drivers and Global Expectations
- Core Principles of QRM (ICH Q9 Foundations)
- The ICH Q9 Quality Risk Management Framework
- Risk Assessment Methodologies
- Working with Risk Matrices and FMEA
- Applying QRM in GMP Systems
- Documentation and Defensibility
- AI as a Quality System Tool for QRM
- Facilitating Risk Assessments
By the end of the course, students will be able to:
- Define and correctly use key Quality Risk Management terminology, including hazard, harm, risk, severity, probability, detectability, risk control, and residual risk.
- Explain FDA and ICH expectations for risk management, including the roles of ICH Q9 and ICH Q10 within GMP-regulated environments.
- Describe and apply the formal QRM process, including risk assessment, risk control, risk communication, and risk review.
- Apply and justify the use of structured risk assessment tools such as Risk Ranking & Filtering, risk matrices, and FMEA to real-world manufacturing and quality scenarios.
- Interpret, evaluate, and critique risk scoring approaches (e.g., RPN, S×P, and S×O×D models), including their strengths, limitations, and appropriate use.
- Integrate QRM into key quality systems, including deviations, CAPA, change control, validation, and supplier management.
Delivered in-person in a classroom or lab setting.
A combination of online and in-person components.
Delivered online with a live instructor at a scheduled date and time.
This course provides technicians and other life-science professionals with a practical, regulatory-aligned introduction to Quality Risk Management (QRM) as applied to pharmaceutical, biologic, and medical product manufacturing. Participants learn regulatory expectations (21 CFR, ICH Q9, ICH Q10), core QRM principles, structured risk assessment methodologies, and how risk management integrates into the Pharmaceutical Quality System (PQS). Emphasis is placed on applying risk tools such as risk matrices and FMEA to real-world scenarios, linking risk assessment to decision-making, and developing clear, defensible documentation aligned with regulatory expectations. The course also introduces the role of artificial intelligence (AI) in QRM, including its use in data analysis, risk detection, and decision support, along with key considerations for validation, oversight, and data integrity in regulated environments. The course concludes with a final module on facilitating risk assessments, emphasizing the facilitator’s role in preparing for assessments, managing discussion dynamics, addressing bias and scoring disagreements, capturing rationale, and supporting clear, defensible team decisions.
- Manufacturing/Production Operators
- Team Leaders and Supervisors
- Quality Control Personnel
- Quality Assurance Personnel
- Process Development Scientists
- Validation/Engineering Personnel
- Technical Support Staff
- Introduction to Quality Risk Management
- Regulatory Drivers and Global Expectations
- Core Principles of QRM (ICH Q9 Foundations)
- The ICH Q9 Quality Risk Management Framework
- Risk Assessment Methodologies
- Working with Risk Matrices and FMEA
- Applying QRM in GMP Systems
- Documentation and Defensibility
- AI as a Quality System Tool for QRM
- Facilitating Risk Assessments
By the end of the course, students will be able to:
- Define and correctly use key Quality Risk Management terminology, including hazard, harm, risk, severity, probability, detectability, risk control, and residual risk.
- Explain FDA and ICH expectations for risk management, including the roles of ICH Q9 and ICH Q10 within GMP-regulated environments.
- Describe and apply the formal QRM process, including risk assessment, risk control, risk communication, and risk review.
- Apply and justify the use of structured risk assessment tools such as Risk Ranking & Filtering, risk matrices, and FMEA to real-world manufacturing and quality scenarios.
- Interpret, evaluate, and critique risk scoring approaches (e.g., RPN, S×P, and S×O×D models), including their strengths, limitations, and appropriate use.
- Integrate QRM into key quality systems, including deviations, CAPA, change control, validation, and supplier management.
Delivered in-person in a classroom or lab setting.
A combination of online and in-person components.
Delivered online with a live instructor at a scheduled date and time.