Drug Development Statistics and Data Management

*Please note that applicants to this short course should go via King's Apply (click red 'Apply' button on the right of this page) and select the following programme*:

Pharmaceutical Medicine Non-Award (Part-time)

Module Code 7MMM0004

This module aims to provide a broad understanding of statistics as they apply to medicines development, including those used in clinical trials, to enable a power calculation to be done, to organise clinical trial data and to analyse and report the data. In addition, methods used in drug safety studies including epidemiological approaches and meta-analysis will be taught.

The module will consist of classroom teaching with a large element of practical experience designing studies and evaluating, analysing and presenting data.

The first aim is to provide a broad understanding of statistical concepts as they apply to the development of medicines, including those used in clinical trials. Key skills will also be taught, for example, to enable a power calculation to be done, to organise clinical trial data and to analyse and report the data. The module consists of classroom teaching supplemented by many workshops in which clinical studies are designed, evaluated and analysed. Students get also involved in making oral scientific presentations to their peers, and drafting documents in the format required for submission to a scientific journal.

The second aim of this module is to provide students with a more detailed understanding of different study designs, including non-experimental as well as adaptive and Bayesian designs.

On completion of the section on statistics, students will be able to:

• Use statistical techniques to produce a robust design for a clinical trial, including decisions on type 1 and type 2 errors and running a power calculation.
• Decide whether to use a superiority, non-inferiority or equivalence approach when designing a protocol.
• Understand the pros and cons of various study designs.
• Use techniques to avoid bias.
• Review a data set and participate in the designing of an analysis plan.
• Decide whether to use intention to treat or per protocol approach as the primary analysis.
• Identify appropriate analysis techniques depending on the outcome and context.
• Decide whether to use parametric or non-parametric tests for a particular data set.
• Use epidemiological data to evaluate a drug safety problem.
• Critically comment on a meta-analysis plan.

Minimum entry requirements are either a medical degree (such as an MBBS) or a 2:1 first degree in pharmacy, pharmacology, biology, biochemistry, chemistry or related subject.

Suitable for individuals seeking an intensive course in drug development statistics and data management e.g. pharmaceutical industry physicians, medical affairs and regulatory affairs personnel.