Training in pharmaceutical analysis and Quality Control

Working in a highly regulated area such as pharmaceutical analysis and Quality Control, continuous education is an essential component of compliance as well as the basis for an efficient way of working in Quality Assurance and Quality Control. Knowing and understanding the scientific fundamentals and the regulatory and GMP requirements, and most notably their pragmatic interpretation belong together. They guarantee the data integrity, and thus the reliability of the decisions resulting from these data and information.

You can benefit from my long-standing expert and management career in pharmaceutical analysis and Quality Control, as well as in various Working Groups concerning the education and training topics listed below, which I can offer in various formats:

 

Training in pharmaceutical analysis and Quality Control

Classroom training

An educational training in your company or in a conference hotel is best suited for an efficient transfer of knowledge and a thorough discussion of extensive and complex topics.

Online training

A web-based training (for example via Web-Ex, Zoom, or Microsoft Teams) is more suitable for individual topics up to two to three hours. This type of training is also well suited for an individual coaching, in case you are interested to intensify your knowledge.

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Self-training with personal discussion

With this format, you enjoy complete flexibility to study the provided training presentation. Afterwards, you will ask questions and discuss details during a web-meeting made to your appointment.

Risk Management pharmaceutical analysis

In order to give you a first impression, I have compiled single topics as well as 2-day courses for each major aspect of pharmaceutical analytics and Quality Control. Please consider this as an initial orientation. With pleasure I will create jointly with you a training program tailored to your needs, do not hesitate to contact me.

 

+49 151 / 28 76 11 66

A) Pharmacopoeia
  1. Structure and rules (Ph.Eur., USP)
  2. Adjustments (Chromatography, USP <621>, Ph.Eur. 2.2.46)
  3. Analytical instrument qualification (USP <1058>)
  4. Reference standards (responsibilities, use, potential issues)
  5. System Suitability Tests
    1. Chromatography (USP <621>, Ph.Eur. 2.2.46)
    2. For various techniques (e.g. AAS, water determination, titration)
  6. Verification of compendial procedures
    1. USP <1226>
    2. Verification of API methods
    3. Verification or drug product methods
B) Lifecycle management in pharmaceutical analysis
  1. Overview (USP <1220> draft, EFPIA publications)
  2. Analytical Target Profile (ATP)
    1. Definition, ATP-Types
    2. MHRA/BP case study
    3. ATP – Workshop
  3. Stage1: Method design
    1. Analytical Control Strategy
    2. Method performance requirements (Method Target Profile)
    3. Method Target Profile – Workshop
    4. Method selection and optimisation
    5. Precision studies
    6. Risk assessment
    7. Robustness, DoE (overview)
  4. Stage2: Method Performance Qualification
    1. Stage2: Validation, verification, transfer
    2. Utilisation of data from Stage1
  5. Transfer
    1. Regulatory requirements & Guidelines
    2. Transfer process and strategies
    3. Design of transfer studies, acceptance criteria
    4. Deviations & OOS during transfer
    5. Transfer: Potential issues and pitfalls
  6. Verification of compendial procedures
    1. USP <1226>, Ph.Eur. draft
    2. Verification of API methods
    3. Verification or drug product methods
  7. Stage3: Ongoing Performance Verification
    1. Regulatory requirements
    2. Monitoring program for verification of performance
    3. Performance verification after changes
    4. Numerical control parameters
    5. Quality control charts (Shewhart, range, SD, combined, CUSUM, EWA)
    6. Risk assessment after changes
    7. Continuous improvements
    8. Workshop Stage 3
  8. Alternative methods (method comparison)
→ Example: 2-day course Lifecycle management in pharmaceutical analysis
Day 1 Day 2
The three stages of Analytical Lifecycle Management Analytical Control Strategy
Performance characteristics: Accuracy and precision Workshop: Analytical Control Strategy
Workshop: Understanding variability (statistical simulations) Stage 2: Method Performance Qualification
Analytical Target Profile Workshop: Replication level
Workshop: Establishing an ATP for example critical quality attributes Workshop: Use of data from method development
Stage 1: Method Design Stage 3: Ongoing Method Performance Verification
Workshop Method selection Workshop Routine Monitoring
Workshop Risk Assessment Workshop Change management
C) Pharmaceutical Quality Control
  1. Equipment Qualification
    1. USP <1058> (DQ, IQ, OQ, PQ)
    2. Continuous PQ
    3. Specific instruments (e.g. AAS, GC, LC, spectrometer, titrators)
  2. OOS
    1. Regulatory requirements (FDA, MHRA)
    2. Definitions (re-analysis, retest)
    3. Phases of the OOS investigation
    4. Establishment of warning (OOT) limits, trend tests, outlier tests
    5. Averaging, OOS and variability
    6. OOS-review, prevention strategies
    7. Workshop OOS and variability
    8. Workshop OOS investigations
  3. Reference standards (RS)
    1. Compendial standards (responsibilities, use, potential issues)
    2. Regulatory requirements to RS
    3. RS types, characterisation
    4. Storage and controls of RS
    5. Stability of RS
    6. Replacement batches, continuity of RS
    7. Laboratory reagents
    8. Measurement uncertainty and RS
    9. Stability of standard solutions
  4. Stability
    1. Regulatory requirements
    2. ICH Q1A, B, D
    3. Ongoing stability studies
    4. Q1E: Extrapolation of shelf-life/Retest Period
    5. Stress-stability, ANVISA-requirements
    6. Stability requirements for changes
    7. Trend tests, stability OOT (prediction interval, regression control chart, slope control chart, time point method, cluster approach)
→ Example: 2-day course Requirements to Quality Control Laboratories
Day 1 Day 2
Regulatory requirements for Quality Control and inspection topics Reference standards and laboratory reagents
Qualification of analytical instruments and data integrity Stability investigations
System Suitability Tests Investigating out-of specification (OOS) test results
Validation of analytical procedures Workshop: Investigating out-of specification (OOS) test results
Workshop: Avoiding mistakes in analytical validation Normal or not-normal?
Transfer of analytical procedures
D) Practical statistics in Quality Control and Quality Assurance
  1. Outlier tests (Grubbs, Dixon, Hampel)
  2. Comparison of data
    1. Simple and statistical comparison
    2. Equivalence tests
    3. Significance tests
    4. Random difference between means
    5. Workshop data comparison
  3. Error propagation
    1. Fundamentals of error propagation
    2. Measurement uncertainty (ISO)
    3. Workshop error propagation
  4. Error types (random and systematic errors) and their relationship
  5. Detection and Quantitation Limit
    1. Calculation from linearity
    2. Calculation from precision
    3. Calculation from signal-to-noise ratio
  6. Normal distribution (ND)
    1. Parameter of location and dispersion
    2. Graphical presentations (histograms, Box-Whisker, ND-plot)
    3. Log-normal distribution
  7. Significant places, rounding
  8. Six Sigma (overview)
  9. Trend tests
    1. Capability indices
    2. Trend test for normal distribution (accord. to Neumann, Wallis-Moore)
    3. Quality control charts (Shewhart, range, SD, combined, CUSUM, EWA)
    4. Quality control charts (Workshop)
    5. Trend tests, stability OOT (prediction interval, regression control chart, slope control chart, time point method, cluster approach)
    6. Establishment of alert limits (statistical, empirical)
  10. USP <1010> Analytical data – interpretation and treatment
  11. USP <1033> Biological Assay Validation
  12. USP <1210> Statistical tools for procedure validation
  13. Variability
    1. Precision levels (system precision, repeatability, intermediate precision, reproducibility)
    2. Calculation of precisions (analysis of variances, from stability)
    3. Optimisation of precision, replication strategy
    4. Workshop Optimisation of precision, replication strategy
    5. Concentration dependency of precision (Horwitz function)
    6. Precision requirements for assay (API, DP)
    7. Precision requirements for impurities (guard bands)
    8. Analysis of variances (one and two factor)
    9. Workshop one-factor analysis of variances
  14. Distribution of analytical data
    1. Normal (Gauss) distribution
    2. Log-normal distribution (Bioassays)
    3. Discrete data (attribute testing)
  15. Confidence intervals
    1. Simple confidence intervals
    2. Confidence interval of intermediate precision
    3. Decision rules
  16. Two-dimensional data
    1. Correlation
    2. Evaluation of response functions (residuals plot, sensitivity plot, statistical, intercept)
    3. Unweighted linear regression
    4. Weighted linear regression
    5. Calibration models (linear, non-linear, single-point calibration, multiple-point calibration, standard addition)
    6. Workshop calibration models
    7. Stability studies, statistical evaluation (ICH Q1E)
  17. Workshops
    1. Application workshop (selection of suitable tests for various questions)
    2. Statistics Quiz (multiple choice questions)
    3. Statistical simulations (dispersion of single data, means, standard deviations, confidence intervals, risk of OOS)
→ Example: 2-day course Fundamentals of statistics for Quality Control and Quality Assurance
Day 1 Day 2
Distribution of analytical data Comparison of data – significance and equivalence tests
Uncertainty of statistical parameters Comparison of data – point estimates
Normal or not normal? Workshop: Comparison of data
Workshop: Variability Linear regression
Error propagation and precision levels Workshop: Linear regression
Workshop: Error propagation & analysis of variances Workshop: Statistics quiz & final discussion
→ 2-day course Advanced statistics for Quality Control and Quality Assurance
Day 1 Day 2
Optimisation of precision (of the reportable value, replication strategy) Regression and calibration models
Workshop: Optimisation of precision (of the reportable value, replication strategy) Trending in stability
Precision requirements (acceptance criteria) Detection and Quantitation Limit
Concentration dependency of precision (Horwitz function) Workshop: Detection and Quantitation Limit
Workshop: Uncertainty of intermediate precision Attribute testing (discrete data)
Assessment of results including their uncertainty Application workshop
Trend analysis & monitoring of data
Workshop: Trend analysis & monitoring of data
E) Validation in pharmaceutical analysis and Quality Control
  1. Overview, regulatory requirements (ICH Q2, USP <1225>, FDA-Guidance)
  2. Lifecycle management of analytical procedures (USP <1220> draft, EFPIA publications)
  3. Linearity (calibration models)
    1. Calibration models (linear, non-linear, single-point calibration, multiple-point calibration, standard addition)
    2. Evaluation of response functions (residuals plot, sensitivity plot, statistical, intercept)
    3. Workshop calibration models
  4. Detection and Quantitation Limit (DL, QL)
    1. General and intermediate QL
    2. Calculation from linearity, precision, signal-to-noise ratio
    3. DL/QL Calculation from precision (Workshop)
  5. Precision
    1. Precision levels (system precision, repeatability, intermediate precision, reproducibility)
    2. Precision bioassay
    3. Calculation of precisions (analysis of variances, from stability)
    4. Optimisation of precision, replication strategy
    5. Workshop Optimisation of precision, replication strategy
    6. Precision requirements for assay (API, DP)
    7. Precision requirements for impurities (concentration dependency)
  6. Cleaning methods (regulatory requirements, acceptance criteria, recovery)
  7. Accuracy
    1. Recovery (content, impurities)
    2. Combined assessment of accuracy and precision
    3. Comparison (simple, significance and equivalence tests)
  8. Robustness
    1. Experimental Design (DoE, overview)
    2. Stability of quantitative solutions
  9. Specificity (chromatographic separations, peak purity, comparison)
  10. Workshops
    1. Design of validation studies (development of validation protocol)
    2. Evaluation and interpretation of validation data
    3. Efficient validation, avoiding mistakes (prevention is better than cure)
→ Example: 2-day course Validation of analytical procedures in pharmaceutical analysis and Quality Control
Day 1 Day 2
Regulatory requirements and guidelines, lifecycle concept Workshop: Evaluation of validation results for example methods
Validation characteristics: Precision, accuracy, and range Workshop: Discussion precision for example methods
Workshop: Variability Requirement-based acceptance criteria for precision
Validation characteristics: Specificity, linearity, detection and quantitation limit Determination and optimisation of precision
Workshop: Design of validation studies and acceptance criteria for example methods Workshop: Discussion accuracy for example methods
Utilisation of data from method development Acceptance criteria for accuracy
Maintenance of the validated status – ongoing performance verification Workshop: Discussion linearity (calibration models) for example methods
Requirements to calibration models
Workshop: Discussion detection and quantitation limit for example methods
Detection and quantitation limit

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