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Validation of technological processes in the pharmaceutical industry


Some basic information about the module

Cycle of education:
2022/2023
The name of the faculty organization unit:
The faculty Chemistry
The name of the field of study:
Chemical Technology
The area of study:
technical sciences
The profile of studing:
The level of study:
second degree study
Type of study:
full time
discipline specialities :
Technology of medicinal products, Chemical analysis in industry and environment , Organic and polymer technology, Polymer materials engineering, Product and ecological process engineering
The degree after graduating from university:
Master of Science (MSc)
The name of the module department :
Department of Biochemistry and Bioinformatics
The code of the module:
7032
The module status:
mandatory for the speciality Technology of medicinal products
The position in the studies teaching programme:
sem: 2 / L15 / 1 ECTS / Z
The language of the lecture:
Polish
The name of the coordinator:
Barbara Dębska, DSc, PhD, Eng.
semester 2:
Marcin Jaromin, MSc, Eng.

The aim of studying and bibliography

The main aim of study:
The aim of the course is to gain knowledge about the validation of industrial processes and statistical tools used in the process of validation

The general information about the module:
The module is implemented in the 2nd semester and includes 15 hours of exercises. The module ends with a pass.

Teaching materials:
Materiały dydaktyczne opublikowane na stronach Zakładu Informatyki Chemicznej

Bibliography required to complete the module
Bibliography used during lectures
1 B. Dębska, B.Guzowska-Świder Statystyka i opracowanie wyników Oficyna wydawnicza Politechniki Rzeszowskiej. 2011
Bibliography to self-study
1 J. Czermiński, A. Iwasiewicz, Z. Paszek, A. Sikorski Metody statystyczne w doświadczalnictwie chemicznym WNT, Warszawa. 1984
2 S. Ł. Achnazarowa, W.W. Kafarow Optymalizacja eksperymentu w chemii i technologii chemicznej WNT, Warszawa. 1982
3 B. Dębska, B. Guzowska-Świder kurs Statystyka www.e-chemia.pl. 2011

Basic requirements in category knowledge/skills/social competences

Formal requirements:
Basic knowledge of statistics and results elaboration

Basic requirements in category knowledge:
Basic knowledge of statistics

Basic requirements in category skills:
computer literacy

Basic requirements in category social competences:

Module outcomes

MEK The student who completed the module Types of classes / teaching methods leading to achieving a given outcome of teaching Methods of verifying every mentioned outcome of teaching Relationships with KEK Relationships with PRK
MEK01 Is able to plan, optimize and evaluate the experiment. lab written test, observation of performance, written report K-W02+
K-U08+
K-U14+
 P7S-UW
P7S-WG
MEK02 He can use statistical tools in the validation process. He can analyze the critical process parameters lab written test, observation of performance, written report K-W03+++
K-U07++
K-U14+
 P7S-UW
P7S-WG
MEK03 He can perform an analysis of the homogeneity and stability testing facilities. He can perform an analysis of the effectiveness of process changes based on the control charts. lab written test, observation of performance, written report K-U01+
K-U14+
 P7S-UW

The syllabus of the module

Sem. TK The content realized in MEK
2 TK01 Design of experiments C01 MEK01 MEK02
2 TK02 Statistical tools in the validation process. Descriptive statistics. Normality tests. Rejecting outliers. C02 - C03 MEK02 MEK03
2 TK03 Linearity validated processes and methods. Linear Regression. The limit of detection and quantification. Analysis of critical process parameters. Selectivity, accuracy, reproducibility, recovery, range of methods. The release profiles. C04 - C05 MEK02 MEK03

The student's effort

The type of classes The work before classes The participation in classes The work after classes
Laboratory (sem. 2) The preparation for a Laboratory: 5.00 hours/sem.
 contact hours: 15.00 hours/sem.
Advice (sem. 2) The participation in Advice: 5.00 hours/sem.
Credit (sem. 2) The written credit: 1.00 hours/sem.

The way of giving the component module grades and the final grade

The type of classes The way of giving the final grade
Laboratory Computer laboratory: credit on the basis of the tasks performed
The final grade The average of the grades obtained in individual laboratories.

Sample problems

Required during the exam/when receiving the credit
(-)

Realized during classes/laboratories/projects
(-)

Others
(-)

Can a student use any teaching aids during the exam/when receiving the credit : no

The contents of the module are associated with the research profile no