MSc Model-based Drug Development - Pharmacokinetic and Pharmacodynamic Modelling
Year of entry: 2025
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Course unit details:
Data Analysis in Pharmacokinetics and Pharmacodynamics
Unit code | PHAR69923 |
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Credit rating | 30 |
Unit level | FHEQ level 7 – master's degree or fourth year of an integrated master's degree |
Teaching period(s) | Semester 2 |
Available as a free choice unit? | No |
Overview
Data analysis in PKPD studies is a specialised area of modelling that combines mathematical and statistical knowledge in data fitting with the sound knowledge of the human body as a system to enable choosing more mechanistic models. The analysis can describe the observed data but also it can be used for the purpose of prediction.
The mathematical background provided in this module relates to linear and non-linear fitting, optimisation procedures that are applied to objective function(s). Statistical input relates to finding inferences, covariates, application of non-linear mixed effect modelling.
This Unit also provides information on available tools for data analysis and their applications. Many commonly used platforms for data analysis (such as Phoenix, Monolix, nlmixr and NONMEM) are part of the module. Students analyse data with different packages to grasp the advantages and disadvantages of these packages.
Teaching and learning methods
The total teaching and assessment methods would be based on 10 notional learning hours per credit (i.e. a total of 300 learning hours teaching and assessment for this 30-credit unit).
Knowledge and understanding
- Distinguish the capability of different tools to perform certain type of data analysis.
Intellectual skills
- Make informed choices on using various models to be used to fit data obtained from studies involving Enzyme Kinetics, Pharmacokinetics and Pharmacodynamics.
- Report essential part of the results from data analysis.
Transferable skills and personal qualities
- Critically assess published reports in the field of Pharmacometrics for consistency in use of methods and other assumptions.
Assessment methods
Assessment Methods | Weighting (%) |
Written exam | 40% |
Written coursework 1 | 30% |
Written coursework 2 | 30% |
Study hours
Scheduled activity hours | |
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Assessment written exam | 2 |
Lectures | 30 |
Practical classes & workshops | 20 |
Seminars | 12 |
Tutorials | 10 |
Placement hours | |
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Placement | 48 |
Independent study hours | |
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Independent study | 178 |
Teaching staff
Staff member | Role |
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Kayode Ogungbenro | Unit coordinator |