The training course “Statistical tools for pharmaceutical quality control” wish to provide useful tools for understanding and making the best use of statistical tools in the field of pharmaceutical quality control and R&D. The language of the course makes it suitable even for those who do not have strong university statistical backgrounds (such as chemists, pharmaceutical chemists, and biologists) and is structured in three parts.
The first introduces the main basic concepts of statistical methods accompanied by practical computational and application examples.
The second part is devoted to comparing multiple sets of measurements – the need that most often arises in quality control, method validation, quality assurance, research and development, etc. Again, the topic is addressed in both its theoretical and practical-application aspects.
The last part, finally, focuses on linear regression and correlation. Regression analysis is certainly the most widely used approach to make predictions or explain (or just summarize) the relationship between the response and its predictors. Its use is indispensable both in the laboratory and in all other areas of chemical-pharmaceutical and pharmaceutical quality.
Key points of the training
- Theoretical-practical indications
- Main statistical methodologies that can be used: In analytical validation studies, in analytical support for manufacturing process development, in pharmaceutical analytical transfer, In the analysis of process data
- Theoretical part of Statistics combined with examination of common practical cases using simple spreadsheets
09:00 – 13:00 SESSION COURSE DAY 1
09:00 – 13:00 SESSION COURSE DAY 2
- Descriptive Statistics vs. Inferential Statistics
- Notions of Probability and probability function
- Main discrete (Binomial and Poisson) and continuous (Normal or Gaussian and Student’s t-distribution) probability functions with practical application examples
- The Normal distribution
- Concept of confidence interval and how it is calculated
- Hints at Prediction and Tolerance intervals
- Outliers: statistical tests to detect their presence (e.g., Grubbs, Dixon) and possible operational approaches (e.g., Winsorization, Trimming)
- Normality tests (Anderson-Darling, Kolmogorov-Smirnov, Shapiro-Wilk) and data transformation techniques
COMPARISON OF MULTIPLE SETS OF MEASUREMENTS
- Null and alternative assumptions: errors of species I and II
- Significance of difference between means: Student’s t-test (one-sided and two-sided test; dependent or independent samples); ANOVA test (fully randomized model: one-way, two-way)
- Significance of difference between variances: F-test, Bartlett’s test, Cochran’s test
- The alternative to significance tests: equivalence tests
- Components of variance for precision estimates
- Method of least squares
- Linearity tests (lack-of-fit, Mandel’s test)
- Analysis of residuals and influence of data (Bias and Leverage)
- Interpretation of ANOVA test on linear model
- t-test for intercept and slope
- Linear regression and comparison of calibration models (traditional tests vs. Akaike Information Criterion (AICc), TOST for bias)
Personnel involved in the pharmaceutical sector:
- Analytical Development
- Quality check
- Conformity and Quality Assurance
- Research and development
- Regulatory Affairs
The course will be carried out through live lectures. Practical examples will be showcased, providing delegates with real life examples to be applied in their daily job life.
For online trainings the access link will be sent 2-3 days before the start of the training.
5% discount for registrations within 1 month before the start of the training, 10% discount for registrations within 2 months before the start of the training. VAT not included. Please inquire for discounts for multiple registrations. Discounts are not cumulative.
In order to cancel enrolment to an event, please email email@example.com within 2 weeks before the starting date of the event. Once this term will be expired, the entire fee will be charged.
It is possible to replace a participant attendance without additional cost, simply by contacting firstname.lastname@example.org. It is asked to notify the participant replacement request within 5 days before the starting date of the course/event, specifying the full name and surname of the enrolled participant as well as the full name and surname of the substitute.
If the minimum number of participants is not reached, Pharma Education Center reserves the right to cancel or schedule the event for another date. Formal communication will be given within 5 days before the event date. In this case Pharma Education Center will refund the registration fee in full and without additional charges. Alternatively, the participant can request a spendable coupon for participating in another PEC event scheduled in the current year.
Pharmaceutical Consultant QC / QA, data analysis and technical reports - Coworker at CPA Italy
Riccardo has a degree in Chemistry from the University of Milan and a postgraduate specialization diploma in Chemical and Analytical Methodologies from the Milan Polytechnic. He has gained decades of work experience (in Italy and abroad) in the chemical-pharmaceutical and pharmaceutical sector where I held various roles in the Quality area including that of QP. In his functions he has often made use of Statistical Methods for the management of events such as: process and QC investigations (e.g. OOS/OOT), validation of analytical methods, management of responses to deficiencies from Regulatory Authorities and Customers, validation/monitoring of production processes and Quality Control, rationalization/optimization of QC processes, data analysis for Annual Product Quality Reviews, etc.
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