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Certificates: GCP - Good Clinical Practice" certificate
Statistics" certificate -
Examination: Practical project work with final presentations
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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
GCP - Good Clinical Practice
Introduction and definitions (approx. 2 days)
Medical basics and terminology
Legal, regulatory and ethical framework conditions
Planning and organization of studies
Forms of studies, study methodology
Application to an ethics committee
GCP definitions/important GCP documents (approx. 3 days)
Legal basis and regulations in clinical research
National and international principles of pharmaceutical law/ICH-GCP
Declaration of Helsinki
ICH-GCP E6 (R2) regulations
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Introduction to clinical trials (approx. 4 days)
Resource planning
Distribution of tasks in the team
Investigator contract
Relevant documents: protocol, investigator's brochure, information, CRF, etc.
Responsibilities (sponsor, CRO, monitor, investigator)
Introduction to the processes of clinical data management (approx. 3 days)
Electronic recording, plausibility check and coding of study data
Medical statistics and biometrics (approx. 1 day)
Basic statistical concepts
Data management
Database management
Audits/inspections (approx. 2 days)
Informing study participants; §40 and 41 AMG
Documentation and reporting of adverse events
Adverse events: Definitions, reporting channels, reporting deadlines
Quality management of clinical trials
Completion of the clinical trial (approx. 2 days)
Close Out Visit
Archiving and final study reports
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.
You master the legal, ethical and administrative aspects of GCP as well as the specialist knowledge of clinical trials from planning to statistical evaluation.
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.
Science learners, math learners, IT learners, medical learners and people from medical-technical professions.
Professional knowledge and consistent adherence to prescribed standards are required to ensure high quality in clinical trials. With these newly acquired skills, you will be in high demand in the pharmaceutical industry or at a contract research organization.
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).