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Who should attend Laboratory, Medical and Device Performance and Validation following Regulatory and ICH Statistical Guidelines
Quality Managers, Quality Professionals, Assay Development Scientists, Research Scientists, Clinical/Laboratory Data Analysts, Laboratory Data Managers
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Seminar Summary:

In this two day workshop seminar one will learn the different regulatory agencies expectations of the quantification and development of a sound statistical monitoring of process control that are accepted, effective, and efficient. (see full course description)

 
 
 

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Training Course Syllabus:


Laboratory, Medical and Device Performance and Validation following Regulatory and ICH Statistical Guidelines - Understanding the Statistical Considerations for Quantitative ICH Guidelines: 2-Day Hands-on Workshop

By: Dr. Al Bartolucci, Emeritus Professor of Biostatistics, University of Alabama

Course Description:

This course is designed to introduce to individuals the understanding and interpretation of the statistical concepts with reference to certain quantitative ICH Guidelines that apply across laboratory (drug development) and clinical development (drug/device) procedures such as analytical methods in validation and acceptance criteria in calibration procedures, risk management and process monitoring as well as dealing with uncertainties and other relevant issues. It is not a course in statistics but introduces the participant to a hands on approach to the statistical techniques one uses, how they are applied and reasonably interpreted and understood. One will address the various challenges facing pharmaceutical and biotechnology companies when it comes to quantifying results in a meaningful interpretable manner through tabulations and graphical presentations.

In this two day workshop seminar one will learn the different regulatory agencies expectations of the quantification and development of a sound statistical monitoring of process control that are accepted, effective, and efficient. Participants will become familiar with the important aspects of the statistical methods and learn how organizations are expected to apply these guidelines.


Learning Objective:

Upon completing this course participants should be able to:
• Evaluate linear and other quantitative measurement procedures.
• Distinguish the difference between confidence and tolerance intervals
• Evaluate the sensitivity of the sample size in given procedures.
• Evaluate laboratory/clinical data results based on risk management and design space issues
• Interpret alternative approaches to statistical process control in reference to data distributional formats
• Discuss relevant FDA requirements and ICH guidelines

Agenda

Day One (8:30 AM - 4:30 PM)
Registration Process: 8:30 AM – 9:00 AM
Session Start Time: 9:00 AM

Lecture 1: Course Motivation and Overview of ICH Methodology (Including Q2A, Q2B, Q8 and Q9)

Lecture 2: Introduction to the simple regression model

  • Interpreting the slope and intercept in validation procedures
  • Residual analysis and error detection
  • Stability and Potency issues
  • Lecture 3: Outlier strategies using the linear model in calibration methods

  • Imputation techniques for missing data
  • Outlier strategies for non-normal or ranked data
  • Consequences of outlier elimination/substitution
  • Updated extreme variance detection strategies
  • Sample size and analysis issues
  • Lecture 4: Confidence and tolerance bounds on risk models

  • Parametric and non-parametric (non normal data) procedures
  • Exact computational techniques
  • DAY 02(8:30 AM - 4:30 PM)

    Lecture 1: Discussion of risk management in general

  • Traditional risk management strategies in clinical settings
  • Predictive models in risk assessment
  • Discussion of the Design Space
  • Risk Management in pre-analytical phase of laboratory testing
  • Lecture 2: Introduction to validation of models in hazard assessment and risk management

  • Demonstration of laboratory Validation procedures
  • Bivariate models and confusion matrices and derived statistics
  • ROC plot
  • Lecture 3: Statistical process laboratory control and capability

  • Normal and non-normal data procedures
  • Evolutionary Operations Process
  • Lecture 4: Confidence and tolerance bounds on limits of risk

    Seminar Summary:

    In this two day workshop seminar one will learn the different regulatory agencies expectations of the quantification and development of a sound statistical monitoring of process control that are accepted, effective, and efficient. (see full course description)

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