Expertise & Capabilities

Quality by Design for the Life Cycle of an Analytical Procedure (3.0 days): The pharmaceutical industry relies on analytical procedures for the combined practices of process and formulation development, process validation, and manufacturing, as well as both in-process and final-product testing. These test methods not only need to be validated but reliable and fit for its intended use. This course provides a systematic approach to the lifecycle of analytical procedures that begins with procedure design and development, continues in procedure performance qualification (validation), and is maintained in continued procedure performance verification. Specifically, the course provides the approaches outlined in both ICH Q2 (R2) and ICH Q14.

Quality by Design for the Life Cycle of an Analytical Procedure

• Apply the statistical tools for QbD throughout the lifecycle of an analytical outlined in both ICH Q2 (R2) and ICH Q14.
• Reference legal and regulatory documents reference requirements for both method robustness studies and analytical
• Describe the methods of method robustness studies and principles of analytical validation referenced by those
• Use risk assessments to determine what factors should be evaluated in method robustness studies.
• Be able to construct and analyze both screening and response surface designs including determination of MODRs and PARs for method robustness studies.
• Set analytical procedure validation requirements that are fit for their intended

Outline:

1. Introduction to AQbD

• AQbDprinciples to include stages
• Accuracy and precision
• Regulatory references, ICH Q2 (R2), and ICH Q14
• Statistical tool needed for validation under ICH Q2 (R2)

2. JMP and Basic Statistical Preliminaries

• Introduction to JMP
• Descriptive statistics
• Statistical intervals
• The importance (or non-importance) of the normal distribution assumption with interval estimators

3. Stage 1: Preliminaries

• Types of studies
• Case study (bioassay)
• Definition of ATP and TMU
• Selection of TMU based on process specifications
• Fixed and random effects models for precision and method robustness studies

4. Stage 1: Method Robustness Studies

• Steps to design of experiments (DOE) to include use of risk assessments consistent with ICH Q14
• Screening designs for method robustness studies
• Response surface designs for method robustness studies including MODRs and PARs

5. Stage1: Qualification Study

• Designs with random effects
• Development of replication strategy
• Confidence interval on the intermediate precision for the reportable value

6. Stage 2: Planning the Validation/Procedure Performance Qualification (PPQ) Study

• Hypothesis testing to demonstrate fit for purpose.
• Power and sample size calculations for the experimental design to be used in the validation study

7. Stage 2: Execution of the Validation/Procedure Performance Qualification (PPQ) Study

• Reporting confidence interval on intermediate precision standard deviation (using the case problem)
• ICH examples

8. Stage 3: Method Transfers

• Model and notation
• Equivalence testing
• Setting criteria
• Test of non-inferiority
• Combined approach to demonstrate accuracy and precision (consistent with ICH Q2 (R2)

9. Stage 3: Analytical Control and Continued Verification

• • System suitability and analytical control
  • Continued verification