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PM2PCOL3-Mathematical Modelling for Pharmacology
Module Provider: Pharmacy
Number of credits: 20 [10 ECTS credits]
Level:5
Terms in which taught: Autumn / Spring / Summer module
Pre-requisites: PM1PCOL1 Principles of Drug Action and PM1PCOL2 Key Skills for Pharmacology and PM1PCOL3 Mathematics & Statistics for Pharmacology
Non-modular pre-requisites:
Co-requisites: PM2PCOL1 Molecular Drug Targets PM2PCOL2 Drug Design and Delivery
Modules excluded:
Current from: 2023/4
Module Convenor: Prof Marcus Tindall
Email: m.tindall@reading.ac.uk
Type of module:
Summary module description:
This module will provide studies with an understanding of the modelling process using mathematical and statistical approaches. They will learn how to interrogate data using statistical approaches, what inferences can be drawn from the data, formulate, solve and investigate biological and pharmacological systems using mechanistic modelling approaches.
Aims:
To provide students with a fundamental understanding of the role of statistical and mathematical modelling in pharmacology.
Assessable learning outcomes:
Students will learn to build statistical models to understand trends and relationships in pharmacological data and formulate, solve and analyse mechanistic mathematical models of pharmacological systems. In doing so they will learn:
- the core steps of the modelling process,
- how modelling can be used to determine the importance of relationships between different aspects of the problem being considered,
- where data can be used to inform mechanistic models
- how data can be used to inform understanding about a system, test hypotheses and inform future directions for experimental work
Additional outcomes:
Working in small groups during laboratory practical classes and workshops and engaging in a multidisciplinary team-based working will:
- Improve team-working skills, such as leadership, motivating and working with others, and contribute to identifying the learning and development needs of team members through coaching and feedback
- Communicate effectively within a team and communicate findings to a wider audience.
- Improve self-directed learning.
Outline content:
- Introduction to the statistical/mathematical modelling process.
- Pharmacokinetic/Pharmacodynamic compartmental modelling.
- Michaelis-Menten Reaction.
- Numerical methods.
- Sensitivity analysis.
- Model parameterisation.
- Using models to inform experimental design.
- Regression analysis including parameter interpretation, testing of parameters and model checking.
- Analysis of variance.
- Modelling with categorical explanatory variables (simplest experimental design)
- Analysis of covariance.
- Incorporating blocks into a design (from how to randomise using techniques such as stratification and minimisation, to how to analyse such designs such as RBD).
- Use of statistical software to fit models and produce associated output.
Brief description of teaching and learning methods:
The course content will be provided through a mixture of formal lectures, interactive workshops using appropriate case studies, supported by tutorial sessions.
- Supplementary information and reading list will be provided by the lecturers and the available facilities for computer-aided literature searching for related material will enable students to improve independent-learning skills.
- Workshops and exercises associated with the module will rein force fundamental concepts of pharmacology that underpin therapeutics and pharmaceutics areas.
Ìý | Autumn | Spring | Summer |
Lectures | 19 | 4 | |
Tutorials | 8 | 12 | 4 |
Practicals classes and workshops | 2 | 6 | |
Guided independent study: | Ìý | Ìý | Ìý |
Ìý Ìý Wider reading (independent) | 15 | 15 | |
Ìý Ìý Advance preparation for classes | 20 | 20 | |
Ìý Ìý Revision and preparation | 20 | 20 | 10 |
Ìý Ìý Reflection | 10 | 10 | 5 |
Ìý | Ìý | Ìý | Ìý |
Total hours by term | 94 | 87 | 19 |
Ìý | Ìý | Ìý | Ìý |
Total hours for module | 200 |
Method | Percentage |
Written exam | 70 |
Set exercise | 30 |
Summative assessment- Examinations:
A 3-hour end of module written examination.
The examination for this module will require a narrowly defined time window and is likely to be held in a dedicated exam venue.
Summative assessment- Coursework and in-class tests:
Set exercise.
Formative assessment methods:
Formative assessment is provided through small group tutorials and workshops, instructor-, self-, and peer-led assessment and feedback. Worked examples and case studies encountered in tutorials will provide the opportunity for formative feedback from staff and peers as well as self-reflection.
Penalties for late submission:
The Support Centres will apply the following penalties for work submitted late:
- where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
- where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Assessment requirements for a pass:
An overall module mark of 40% will be required.
Reassessment arrangements:
Reassessment is by examination in August and will be by written examination.Ìý
Additional Costs (specified where applicable):
Cost | Amount |
| A wide variety of text books is available from the University library.Ìý Students are not expected to purchase additional texts for this module |
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| Ìý |
| There may be some printing costs linked to coursework – final submission will be electronic |
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Last updated: 17 July 2023
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.