MSc Model-based Drug Development - Pharmacokinetic and Pharmacodynamic Modelling
Year of entry: 2025
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Course unit details:
Biostatistics
Unit code | PHAR69931 |
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Credit rating | 15 |
Unit level | FHEQ level 7 – master's degree or fourth year of an integrated master's degree |
Teaching period(s) | Semester 1 |
Available as a free choice unit? | No |
Overview
This unit is designed to give the student an understanding of fundamental statistical concepts that are routinely used in designing clinical trials or interpreting trial results.
Emphasis is given to the use of simple hands-on exercises to build confidence in the application of concepts and in the practical use of software for statistical problem solving.
This unit is a prerequisite for the subsequent unit (PHAR69923) on advanced approaches to data analysis, including mixed effects models and population pharmacokinetics.
Theoretical knowledge will be disseminated first by lecture, but the unit will emphasise the application of theory by solving problems in workshops and coursework assignments. Some of the assignments will be computer based, to ensure students are comfortable with basic software for data analysis and presentation before encountering more specialised software in subsequent units.
Students will complete exercises using Microsoft Excel and will also be introduced to more specialised software such as R.
Aims
The unit aims to:
- introduce statistical concepts applied in the design of clinical trials and interpretation of clinical results in drug development
- provide practice in applying statistical methods to typical clinical trial data.
Syllabus
Basic statistical concepts and definitions:
- types of data
- probability concepts
- estimation
- confidence intervals
- hypothesis testing/ significance testing.
Trial design:
- choice of variables
- control groups
- randomisation
- blinding
- sample size and power.
Statistical analysis methods:
- types of variables
- time to event data.
Statistical analysis issues.
The statistical analysis plan (SAP) in clinical research.
Teaching and learning methods
- Lectures.
- Workshops, entailing guided sequences of analyses with interactive discussion with tutor.
- Directed reading.
- Formative-assessed calculation-based coursework (pass/fail).
- Summative-assessed calculation-based coursework.
Knowledge and understanding
Students should be able to:
- define and apply the statistical terms relevant to clinical trial data collection and interpretation
- explain the crucial roles biostatistics in guiding the design and conduct of clinical trials.
Intellectual skills
Students should be able to:
- apply basic biostatistical concepts and interpret statistical information arising from clinical trials
- perform power calculations and apply them in the design of a clinical trial
- understand the statistical terms presented in clinical trial documents.
Practical skills
Students should be able to:
- use computer software such as Excel or R to perform basic computational tasks including file input/output, calculations, and production of effective graphs.
Transferable skills and personal qualities
- Independent learning.
- Mastering new software.
Assessment methods
Assessment | Length | Feedback | Weighting |
---|---|---|---|
Formative assessments x 4 | 8 hours | Model answer presented in tutorial | N/A (just need to submit) |
Biostatistics problems x 3 coursework | 20 hours | Online feedback within standard time | 100% |
Recommended reading
- ICH E9 Statistical Principles for clinical trials. ICH E9 Statistical Principles for clinical trials.
- Senn S. Statistical Issues in Drug Development. John Wiley & Sons. Chichester. 1997.
- Armitage P, Berry, G, Mathews JNS. Statistical Methods in Medical Research. Blackwell Publishing, Oxford. 2002.
- BMJ statistics notes. (Altman et al.).
Study hours
Scheduled activity hours | |
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Lectures | 10 |
Seminars | 20 |
Tutorials | 4 |
Independent study hours | |
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Independent study | 116 |
Teaching staff
Staff member | Role |
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Leon Aarons | Unit coordinator |