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Certificates: GCP - Good Clinical Practice" certificate
Certificate "Statistics and data analysis" -
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
GCP - Good Clinical Practice
Introduction and definitions (approx. 2 days)
Medical basics and terminology
Legal, regulatory and ethical framework conditions
Overview of the EU Clinical Trials Regulation (EU-CTR)
CTIS - function and classification in the European study approval procedure
Planning and organization of studies
Types of studies, study methodology
Application to an ethics committee
Overview of digital tools and AI applications in clinical research
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 (R3) regulations
Interaction of ICH-GCP, EU-CTR and CTIS in the regulatory environment
Limits and regulatory requirements for the use of AI in clinical trials
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)
Actors involved in the CTIS process
Basic procedure for study approval via CTIS
Digital infrastructure of clinical trials
Support of study planning by AI (e.g. literature search, protocol design)
Introduction to the processes of clinical data management (approx. 3 days)
Electronic recording, plausibility checks and coding of study data
AI-supported data checking, plausibility checks and coding
Data quality and automation in clinical data management
Medical statistics and biometrics (approx. 1 day)
Basic statistical concepts
Data management
Database management
Audits/inspections (approx. 2 days)
Informing study participants; legal basis according to §40-42e AMG
Documentation and reporting of adverse events
Adverse events: Definitions, reporting channels, reporting deadlines
Quality management of clinical trials
Transparency requirements and public study information in the context of CTIS
AI-supported document review and quality control
Completion of the clinical trial (approx. 2 days)
Close Out Visit
Archiving and final study reports
Final notification and study status in the European context (CTIS overview)
Project work (approx. 3 days)
To consolidate the content learned
Presentation of the project results
Statistics and data analysis
Statistical basics (approx. 6 days)
Measurement theory basics (population, sample, sample types, measurement, scale levels)
Univariate descriptive statistics (frequency distributions, central measures, measures of dispersion, standardization, histograms, bar charts, pie charts, line charts, box plots)
Bivariate descriptive statistics (measures of correlation, correlation coefficients, crosstabs, scatter plots, grouped bar charts)
Basics of inductive inferential statistics (probability distributions, normal distribution, sampling distribution of the mean, significance test, null hypothesis test, significance level, effect size, parameter estimation, confidence intervals, error bar charts, power analysis, sample size)
Data preparation and data cleansing with suitable software
Descriptive analysis
Visualization of statistical results
AI-supported analysis and interpretation of statistical results
Methods for comparing two groups (approx. 5 days)
z-test, t-test for one sample
t-test for independent and related samples
Pretest-posttest designs with two groups
Supporting significance tests (Anderson-Darling test, Ryan-Joiner test, Levene test, Bonett 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, measures of association)
Interpretation of test results
AI-supported interpretation of results
Basics of regression analysis (approx. 2 days)
Linear regression
Model interpretation
AI-supported model interpretation
Correlation analysis
Methods for comparing the means of several groups (approx. 3 days)
One-factorial and two-factorial analysis of variance (ANOVA)
Post-hoc analyses
Interpretation of group differences
Multi-factorial analysis of variance (general linear model)
Fixed, random, crossed and nested factors
Multiple comparison methods (Tukey-HSD, Dunnett, Games-Howell)
Interaction analysis
Power analysis for variance analyses
Introduction to Design of Experiments (DoE) (approx. 1 day)
Full factorial 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).