GCP - Good Clinical Practice and Statistics

Free of cost

by funding

Based on the ICH-GCP quality standard, the course teaches regulatory knowledge, practical skills and the basics of artificial intelligence (AI) in this area. It also explains how to use a statistical program to identify correlations and verify observations.
  • Certificates: GCP - Good Clinical Practice" certificate
    Statistics" certificate
  • Examination: Practical project work with final presentations
  • Teaching Times: Full-time
    Monday 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.)
  • Language of Instruction: German
  • 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).

We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm
free of charge from all German networks.
Contact
We will gladly advise you free of charge. 0800 3456-500 Mon. - Fri. from 8 am to 5 pm free of charge from all German networks.