PM2MMM: Mathematical Modelling for Pharmacology

Module code: PM2MMM

Module provider: Pharmacy; School of Chemistry, Food and Pharmacy

Credits: 20

Level: Level 2 (Intermediate)

When you'll be taught: Semester 2

Module convenor: Professor Marcus Tindall, email: m.tindall@reading.ac.uk

Pre-requisite module(s): This module is only available to students on the Associated Pharmacy programme. (Open)

Co-requisite module(s): IN THE SAME YEAR AS TAKING THIS MODULE YOU MUST TAKE PM2MDT AND TAKE PM2DDD (Compulsory)

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: Yes

Last updated: 19 September 2024

Overview

Module aims and purpose

This module will provide students with an understanding of the modelling process using mathematical and statistical approaches. They will learn how to interrogate data using statistical approaches and what inferences can be drawn from it, and formulate, solve and investigate biological and pharmacological systems using mechanistic modelling approaches.

This module aims to provide students with a fundamental understanding of the role of statistical and mathematical modelling in pharmacology.

Module learning outcomes

By the end of the module, it is expected that students will be able to:

1. Build statistical models to understand trends and relationships in pharmacological data and formulate, solve and analyse mechanistic mathematical models of pharmacological systems
2. Demonstrate the core steps of the modelling process and how modelling can be used to determine the importance of relationships between different aspects of the problem being considered
3. Understand how data can be used to inform mechanistic models, test hypotheses and inform future directions for experimental work
4. 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
5. Improve self-directed learning

Module content

• Introduction to the statistical/mathematical modelling process. 
• Reaction equations and receptor-compound binding in a pharmacological context. 
• Whole body pharmacokinetic pharmacodynamic (PKPD) compartmental modelling. 
• Numerical methods and Matlab 
• Sensitivity analysis. 
• Data and 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.

Structure

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 and computer practical sessions. 

Supplementary information and a reading list will be provided by the lecturers. 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 reinforce fundamental concepts of pharmacology and modelling that underpin therapeutic and pharmaceutical areas.

Study hours

At least 55 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• 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 three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

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.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

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.

Reassessment

Additional costs