Models for Biological Systems
Course, Master's level, 3FB207
Expand the information below to show details on how to apply and entry requirements.
Autumn 2025
Autumn 2025,
Uppsala, 100%, On-campus, English
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 2 October 2025–2 November 2025
- Language of instruction
- English
- Entry requirements
-
150 credits in biomedicine, pharmaceutical science, drug development, natural science and/or technology. Previous studies must contain 5 credits of statistics or probability theory. Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Selection
-
Higher education credits (maximum 285 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- First tuition fee instalment: SEK 18,125
- Total tuition fee: SEK 18,125
- Application deadline
- 15 April 2025
- Application code
- UU-39209
Admitted or on the waiting list?
- Registration period
- 24 September 2025–1 October 2025
- Information on registration from the department
Autumn 2025
Autumn 2025,
Uppsala, 100%, On-campus, English
For exchange students
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 2 October 2025–2 November 2025
- Language of instruction
- English
- Entry requirements
-
150 credits in biomedicine, pharmaceutical science, drug development, natural science and/or technology. Previous studies must contain 5 credits of statistics or probability theory. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
- Registration period
- 24 September 2025–1 October 2025
- Information on registration from the department
Expand the information below to show details on how to apply and entry requirements.
Spring 2026
Spring 2026,
Uppsala, 100%, On-campus, English
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 20 February 2026–24 March 2026
- Language of instruction
- English
- Entry requirements
-
150 credits in biomedicine, pharmaceutical science, drug development, natural science and/or technology. Previous studies must contain 5 credits of statistics or probability theory. Proficiency in English equivalent to the Swedish upper secondary course English 6.
- Selection
-
Higher education credits (maximum 285 credits)
- Fees
-
If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.
- First tuition fee instalment: SEK 18,125
- Total tuition fee: SEK 18,125
- Application deadline
- 15 October 2025
- Application code
- UU-89209
Admitted or on the waiting list?
Spring 2026
Spring 2026,
Uppsala, 100%, On-campus, English
For exchange students
- Location
- Uppsala
- Pace of study
- 100%
- Teaching form
- On-campus
- Instructional time
- Daytime
- Study period
- 20 February 2026–24 March 2026
- Language of instruction
- English
- Entry requirements
-
150 credits in biomedicine, pharmaceutical science, drug development, natural science and/or technology. Previous studies must contain 5 credits of statistics or probability theory. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Admitted or on the waiting list?
About the course
The course deals with computer models for biological systems that are important in a drug development context. Specifically, the focus is on models for clinical pharmacokinetic and pharmacodynamic data. The course will also include models of systems that are of importance for preclinical research in the pharmaceutical field. Evaluation of modelling results is an important part of the course.
The course will also illustrate the use of models for addressing scientific issues and aspects of study design. Technical, mathematical and statistical aspects of model fitting and non-linear regression form an integral part of the course.
Reading list
No reading list found.