Personalised or precision medicine aims to tailor medical decisions, practices or interventions to an individual, with the aim of improving health outcomes. As with all scientific endeavours these decisions need to be evidence-based. The data used must be of high quality but can come from a variety of sources. In this module we will consider what is meant by precision/personalised medicine and how this can be achieved using the different sources of patient data that we have, the potential future sources of data, alongside the data complexity, reliability and analysis.

We will explore interventions such as clinical genomics and clinical and health bioinformatics and will consider the impacts that these are having on the diagnostic landscape and beyond. We will consider both current and potential impacts of how the data we have now may be used in the future with the aim of improving personalised/precision medicine and outcomes for the patient. We will look to the future, and the digitising of pathology service, the use of AI, and the potential for both positive and negative outcomes.

Viva Voce (15 minutes) LOs 1,2
A structured oral assessment.

Scientific Article (1500 words) LOs 3,4
A formal scientific article applying the key skills and techniques developed within this module.

This module is delivered as a blend of asynchronous online learning sessions, on campus study days and work-based study. Within each learning unit you will be given a range of learning outcomes and directed through a variety of learning material (for example recorded lectures, online exercises or collaborative activities) to work though asynchronously together with an opportunity to check and develop your learning (for example through online quizzes, challenge questions or discussion fora). You are encouraged to reflect upon the academic content of the module and consider how this is applicable within your workplace.

Your learning is supported by a group discussion board and weekly online sessions where you can discuss your learning with the academic teaching team.

1. Explain the principles and core concepts of clinical genetics, genomics and personalised/precision medicine and discuss these in the context of patients referred to healthcare science services. Knowledge and Understanding

2. Explain the principles of clinical bioinformatics and health informatics and discuss their impact on health care, health and healthcare science services. Application

3. Develop knowledge and understanding of the key technologies used for the acquisition and analysis of clinical data. Knowledge and Understanding, Learning

4. Critically analyse information and data in order to illustrate the relationship between disease, environment and health. Analysis

You will require access to a computer with internet access.
Access to specialist facilities on campus.

The IBMS Fundamentals series will be used throughout to support discussions.
https://global.oup.com/academic/content/series/f/fundamentals-of-biomedical-science-ibms/?cc=gb&lang=en&

Reference to primary literature will be strongly encouraged.

Personalised or precision medicine aims to tailor medical decisions, practices or interventions to an individual, with the aim of improving health outcomes. As with all scientific endeavours these decisions need to be evidence-based. The data used must be of high quality but can come from a variety of sources. In this module we will consider what is meant by precision/personalised medicine and how this can be achieved using the different sources of patient data that we have, the potential future sources of data, alongside the data complexity, reliability and analysis.