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Certificates: GMP - Good Manufacturing Practice" certificate
Statistics" certificate -
Examination: Praxisbezogene Projektarbeiten mit Abschlusspräsentationen
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Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 8 Weeks
GMP - Good Manufacturing Practice
Introduction to GMP (approx. 2 days)
EU GMP guidelines, AMG, AMWHV
Authorities, drug approvals, marketing authorization
Key persons
FDA, CFR 21
International regulations
AI in the pharmaceutical environment
SOP system (approx. 2.5 days)
Requirements for SOPs
Structure of SOPs
Document control and version management
Training system (approx. 1.5 days)
Employee qualification
Training planning and documentation
Effectiveness control
Deviation and CAPA management (approx. 2 days)
Deviations and CAPA
Requirements for deviation and CAPA management
Documentation of deviations
Error cause analysis
Corrective and preventive measures
CAPA process
AI-supported data analysis for root cause identification
Change management (change control) (approx. 1 day)
Requirements for change management
Notifiable changes, classification of changes
Risk management in the change process
Change management process
Validation and qualification (approx. 1.5 days)
Device, system and room qualification
Process, cleaning and method validation
Qualification and validation process
Qualification and validation documentation
Quality control (approx. 1 day)
Sampling and testing
stability
Dealing with OOS
Storage status
AI-supported evaluation of test data
Complaints management (approx. 0.5 days)
Complaints
Product recall
Audit management (approx. 0.5 days)
Audit types and audit process
Internal audit and FDA inspection
AI-supported data analysis for audit preparation
Supplier qualification (approx. 0.5 days)
Supplier qualification and evaluation
Review and trending (approx. 0.5 days)
Batch Record Review
Product Quality Review
Management Review
Industrial hygiene in the pharmaceutical industry (approx. 2 days)
Personnel hygiene
Hygiene requirements
Clothing and behavior
Production hygiene
Contamination prevention
Hygiene plans
Documentation (approx. 0.5 days)
GMP documentation and data integrity
AI-supported support for document review
Production rooms - clean rooms (approx. 1 day)
General requirements for production rooms
Requirements for premises including storage areas
Avoidance of cross-contamination
Project work (approx. 3 days)
To consolidate the content learned
Presentation of the project results
Statistics
Statistical basics (approx. 6 days)
Measurement theory basics (population and sample, sample types, measurement and scale levels)
Univariate descriptive statistics (frequency distributions, central measures, measures of dispersion, standard value, histograms, bar charts, pie charts, line charts and box plots)
Bivariate descriptive statistics (measures of correlation, correlation coefficients, crosstabs, scatter plots and grouped bar charts)
Basics of inductive inferential statistics (probability distribution, normal distribution, mean value distribution, significance test, Fisher's null hypothesis test, effect size, parameter estimation, confidence intervals, error bar charts, power analyses and determining the optimum sample size)
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Methods for comparing two groups (approx. 5 days)
z- and t-test for a sample (deviation from a specified value)
t-test for the mean difference between two independent/connected samples
Testing the effectiveness of actions, measures, interventions and other changes with t-tests (pretest-posttest designs with two groups)
Supporting significance tests (Anderson-Darling test, Ryan-Joiner test, Levene test, Bonnet test, significance test for correlations)
Nonparametric methods (Wilcoxon test, sign test, Mann-Whitney test)
Contingency analyses (binomial test, Fisher's exact test, chi-square test, cross-tabulations with measures of association)
Methods for comparing the means of several groups (approx. 5 days)
One- and two-factorial analysis of variance (simple and balanced ANOVA)
Multi-factorial analysis of variance (general linear model)
Fixed, random, crossed and nested factors
Multiple comparison methods (Tukey-HSD, Dunnett, Hsu-MCB, Games-Howell)
Interaction analysis (analysis of interaction effects)
Selectivity and power analysis for variance analyses
Introduction to Design of Experiments (DoE) (approx. 1 day)
Full and partial factorial experimental designs
Project work (approx. 3 days)
To consolidate the content learned
Presentation of the project results
Changes are possible. The course content is updated regularly.
After this course, you will be familiar with the requirements of a GMP system, the applicable regulations and the central processes of pharmaceutical quality management. You will understand the basics of SOP systems, CAPA, change management, audit processes, documentation, quality control, industrial hygiene and cleanroom requirements and be able to classify relevant technical terms with confidence.
You will also understand the basics of statistics, be able to process and evaluate data and present, explain and interpret statistical data analyses and results using graphics.
The course is aimed at science students, engineering graduates, production managers, quality officers and all employees in pharmaceutical production, technology, quality control and quality assurance. It is also aimed at all persons who are responsible for compliance with "Good Manufacturing Practice" and want to find out about the core GMP topics.
Users and specialists from social and market research, business administration (marketing, business intelligence), technical areas, production, quality assurance and research in the healthcare sector.
GMP knowledge is indispensable in almost all areas of the production of pharmaceuticals and active ingredients, as well as cosmetics, food and animal feed. Your newly acquired knowledge will open up numerous new opportunities for you in these sectors.
A sound knowledge of statistics is a valuable additional qualification that is in great demand in industrial research and development, in drug development, in the supervision of medical studies, in finance and insurance, in information technology or in public administration.Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.
Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).