2 Day Seminar on Statistical Elements of Implementing ICH Quality Guidelines

DUBLIN, Nov. 13, 2023 /PRNewswire/ -- The "Statistical Elements of Implementing ICH Quality Guidelines" training has been added to  ResearchAndMarkets.com's offering.

Most organizations have programs and procedures but they contain holes or fall short in the implementation of the tools and techniques used to apply proper statistical reasoning and analysis to ICH guidelines. Statistics can help you to better understand, implement, and track processes covered by the ICH guidelines?

This 2-day seminar explores the unique challenges facing quality functions of pharmaceutical and biotechnology companies. Attendees will learn practical implementation solutions as well as best practice descriptions that will allow management to effectively assess, manage and mitigate risk of poorly designed studies. Participants will learn statistical methods related to ICH guidelines and will discover how regulatory agencies, such as the FDA expect organizations to meet these guidelines.

This seminar will provide attendees with an understanding of the fourteen ICH Quality guidelines as relates to statistical guidance and analysis. The course will provide tools, techniques and insight that will allow participants to immediately begin implementation of the information learned within their organization/firm.

LEARNING OBJECTIVES:

Upon completion of the course, you will be able to:

• Compare FDA requirements to ICH guidelines.
• Perform comparative analyses and regression analysis.
• Know the difference between confidence and tolerance intervals.
• Calculate the appropriate sample size.
• Calculate the probability of risk.
• Design and perform statistical tests for comparisons, stability, validation, impurities

Key Topics Covered:

DAY 1

• Introduction to Clinical Project Management: Overview of project management; roles and responsibilities of the clinical project manager; establishment of project teams.
• Strategic Project Planning: Review of the project charter; risk identification to clinical research projects; development of a project plan; creation of the work breakdown structure in a project.
• Process Mapping as a Planning and Management Tool.
• Effective Schedule Management: Defining project scope; creation of realistic schedules; identification of critical path to a project; effectively managing change orders and out of scope to your project.

DAY 2

• Costs Estimation, Creation and Management of Budgets: Effective project budget planning and tracking.
• Outsourcing Strategies. Vendor Management and Oversight: Qualification, selection, and oversight of vendors in clinical research projects.
• Tracking Projects: Risk, Cost and Change Management. Development and Implementation of Quality Control and Risk Management Systems and Key Performance Indicators.
• Project Closure: Effectively closing a project and lessons learned.
• Group work on the Case study
• Case Study: Quality by Design (QbD) and Risk-Based Quality Management (RBQM) Techniques Applied to the Planning and Execution of a Clinical Trial.
• Discussion of the Case study and Closing remarks

SEMINAR OBJECTIVES

Day 1: ICH review and Statistics Fundamentals

Review ICH Quality Guidelines (Q Series)

• Q1 Stability Testing
• Q2 Analytical Validation
• Q3A-3E Impurities
• Q4 Pharmacopoeias
• Q5A-5E Quality of Biotechnological Products
• Q6A-6B Specifications
• Q7 Good Manufacturing Practice
• Q8 Pharmaceutical Development
• Q9 Quality Risk Management
• Q10 Pharmaceutical Quality System
• Q11 Development and Manufacture of Drug Substances
• Q12 Lifecycle Management
• Q13 Continuous Manufacturing of Drug Substances and Drub Products
• Q14 Analytical Procedure Development
• Developing a Quality Risk Management Plan

Fundamentals of Statistics

• Normal Distribution
• Descriptive and Summary Statistics
• Graphical Techniques
• Null Hypothesis Statistical Testing
• Confidence and Tolerance Intervals
• Statistical vs. Meaningful Significance

Day 2: Statistical Tests and Applications to Industry

Statistical Analyses

• Comparative Statistics
• Regression Analysis
• Sample Size (Power Analysis)
• Discussion/Questions

Application to Industry

Design of Experiments (DOE)

• Setting Specifications/Thresholds/Acceptance Criteria
• Stability/Shelf-Life Testing
• Assay Validation
• Impurities
• Discussion/Questions

For more information about this training visit https://www.researchandmarkets.com/r/g89ige

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