PM1PCOL3-Mathematics & Statistics for Pharmacology

Module Provider: Pharmacy
Number of credits: 20 [10 ECTS credits]
Level:4
Terms in which taught: Autumn / Spring / Summer module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites: PM1PCOL1 Principles of Drug Action and PM1PCOL2 Key Skills for Pharmacology
Modules excluded:
Current from: 2020/1

Module Convenor: Dr Marcus Tindall

Email: m.tindall@reading.ac.uk

Type of module:

Summary module description:

This module will provide you with an introduction to basic mathematical and statistical concepts relevant to pharmacology. The module is designed to ensure you have the required quantitative skills for application in your first year pharmacological modules as well as providing you with relevant foundation material for the second year Mathematical Modelling for Pharmacology Module. The module will provide you with an overview of functions, basic algebra, differentiation, integration, ordinary differential equations, matrices and vectors, exploratory data analysis, statistical inference, basic experimental design and an introduction to medical statistics used in clinical trials.

Aims:

To provide students with the necessary skills for undertaking basic quantitative analysis in pharmacology. It also includes an introduction to a mathematical/statistical computing package.

Assessable learning outcomes:

Students will learn a range of fundamental mathematical and statistical techniques including:Ìý

• How to plot functions relevant to pharmacological students,Ìý


• The role of the calculus in informing pharmacological studies,Ìý


• How to manipulate matrices and vectors and undertake simple operations relevant to data analysis, how to explore estimate and test pharmacological data recognising the statistical concepts of preci sion and statistical significance.

Additional outcomes:

Working in small groups during workshops and engaging in 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


• Develop effective communication within a team and communicate findings to a wider audience.

Outline content:

• Motivation for the use of mathematics & statistics in drug discovery and development.


• Functions and basic algebra for pharmacological applications (Algebra, polynomials in x, roots of quadratic equations, factorising, plotting graphs of y=f(x), logs and the exponential function, trigonometric functions, solving simultaneous equations).Ìý


• Differentiation as a prelude to learning about differential equations (Differentiation of polynomials, e xponential and log functions, product rule, chain rule).


• Integration as the anti-derivative and a sum (Integration of polynomials, simple functions, exponential, integration by substitution).Ìý


• Ordinary differential equations for formulating mathematical models (Formulating and solving linear first order equations).


• Matrices & vectors (Matrix operations; determinants, inverse).Ìý


• Probability and Statistics for understand ing data: use of probability distributions, exploratory data analysis including graphical displays of data.


• Concept of sampling distributions.


• Estimation and confidence intervals for means and proportions.


• Hypothesis testing of continuous and categorical dataÌý


• Basic experimental design (Completely Randomised Designs and Randomised Block Designs).Ìý


• Introduction to medical statistics focussing on Clinical Tri als

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.Ìý

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 reinfor ce fundamental concepts of mathematics and statistics which underpin therapeutic and pharmaceutical areas.

Contact hours:

Ìý	Autumn	Spring	Summer
Lectures	10	13
Tutorials	7	4
Practicals classes and workshops	3	5
Guided independent study:	Ìý	Ìý	Ìý
Ìý Ìý Wider reading (independent)	15	15
Ìý Ìý Advance preparation for classes	20	18
Ìý Ìý Revision and preparation	20	20	8
Ìý Ìý Essay preparation	11	11
Ìý Ìý Reflection	10	10
Ìý	Ìý	Ìý	Ìý
Total hours by term	96	96	8
Ìý	Ìý	Ìý	Ìý
Total hours for module	200

Summative Assessment Methods:

Method	Percentage
Written exam	70
Set exercise	30

Summative assessment- Examinations:

There will be a three-hour final examination.

Summative assessment- Coursework and in-class tests:

Assessed coursework.

Formative assessment methods:

Formative assessment and associated feedback form a large proportion of the module, with students being provided with workshops, tutorials and online assessments to prepare for the final examination. Formative assessment is provided through compulsory small group tutorials and workshops, instructor-, self-, and peer-led assessment and feedback.

Penalties for late submission:

The Module Convenor 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[1] (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.

The University policy statement on penalties for late submission can be found at:
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:

Students must obtain an overall module mark of 40% and obtain at least 40% in the final examination.

Reassessment arrangements:

Reassessment is by examination in August and will be by written examination. Students are normally permitted one further attempt at any failed assessments. Failed coursework may be reassessed by an alternative piece of work, before or during the August examination period. Students who fail written examinations at their second attempt are not permitted a further attempt and are required to leave the University.

Additional Costs (specified where applicable):

Cost	Amount
Required textbooks	A wide variety of textbooks is available from the University library.Ìý Students are not expected to purchase additional texts for this module
Specialist equipment or materials	Ìý
Specialist clothing, footwear or headgear	Ìý
Printing and binding	There may be some printing costs linked to coursework – final submission will be electronic
Computers and devices with a particular specification	Ìý
Travel, accommodation and subsistence	Ìý

Last updated: 12 June 2020