- Degree
- Master of Science in Clinical Research
- Course location
- Dresden
- Teaching language
- • English
- Languages
- English (100%)
- Full-time / part-time
- • part-time (study alongside work)
- Mode of study
- Fully on-site with voluntary online elements
- Programme duration
- 3 semesters
- Beginning
- Summer semester
- Tuition fees per semester in EUR
- 4,475 EUR
- Additional information on tuition fees
- The tuition fee for the whole MSc programme is 13,425 EUR.
Travel, living, and subsistence costs are not included in the tuition fees.
- Combined Master's degree / PhD programme
- No
- Joint degree / double degree programme
- No
- Description/content
- Module One – Basics of Clinical Research – Theory*
Introduction to Clinical Trials, Theory of Study Conduction Methods, Principles of Statistical Analysis, Designing a Clinical Trial, Principles of Trial Management and Study Types
• How to formulate a research question (FINER, PICOT)
• Select study population (inclusion/exclusion criteria)
• Randomisation
• Blinding methods and unblinding problems
• Statistical methods (data distribution and classification, statistical tests, sample size calculation, survival analysis, missing data imputation and meta-analysis)
• Data collection (electronic capture)
• Data monitoring (interim analysis, DSMB)
• Scientific reporting (include training in manuscript writing)
• Types of study designs and clinical study phases (observational studies, non-inferior and adaptive designs and randomised clinical trials, phase 0 to IV)
*Module One includes the content of the PPCR programme (https://site.ppcr.org/) – a recognition of the programme is possible.
Module Two – Advanced Clinical Research – Applications
Applied Biostatistics, Data Visualisation, Hands-On Workshop on R/RStudio
• Applied biostatistics and clinical practice
• Data visualisation, data and data sources
• R/RStudio hands-on workshop
Module Three – Innovations of Clinical Research
Scientific Presentation, Handling of Modern Media, Health Economic Outcome Research, Big Data and AI, Real-World Data / Real-World Evidence, Health Technology Assessment
• Scientific presentation
• Handling of modern media
• Health economic outcome research
• Big data and artificial intelligence (AI)
• Real-world data ("RWD") / real-world evidence ("RWE")
• Health technology assessment ("HTA")