Program Overview

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The course is designed as a Masters programme but it is credit-bearing and flexible, so you may also exit with a PgCert or PgDip at key points. Interested students are also welcome to undertake some of the individual modules as short courses.

Students will study the following modules;

Introduction to Personalised Medicine & Pharmacogenomics

This module seeks to develop students' knowledge of important and emerging areas within personalised medicine. It explores the role of pharmacogenetics developing an understanding of the molecular aspects of stratified medicine and creates a foundation for future learning in modules to follow. The module reviews the methods of biomarker discovery and translation and considers the issues surrounding personalised medicine research and its application into society.

Mathematical and Computational Methods

This module describes the mathematical frameworks required to analyse data and some of the statistical methods need to evaluate hypotheses supported by data. It also introduces students to frameworks and concepts required by scientific computing and develops their programming skills such that they implement analyses of data.

Clinical governance, regulatory processes and ethics

This module is designed to provide an understanding of the importance of clinical and research ethics and governance. The module covers the regulatory processes involved in seeking research governance approval and provides students with an opportunity to complete an ethical review and to prepare a research ethics and governance application.

Biomedical Informatics

This module develops essential skills, knowledge and understanding of biomedical informatics in relation to basic and applied research and practice. Providing an overview of biomedical informatics and its application.

In Silico Genomic Proteomic & Metabolomic Analyses Methods

This module provides an overview of in silico methods, theories and applications to study genes, proteins or metabolites. It will also provide students with an understanding of python.

Clinical Trials Design and Patient Recruitment

This module is designed to provide students with the ability to critically evaluate clinical trial design, and in depth understanding of patient recruitment and the regulatory and ethical processes involved. The module will also provide students with the ability to critically appraise clinical trial analysis, reporting and quality assurance.

Clinical Decision Making and Diagnostic Theory

This module details the regulatory and clinical guidance which is required to ensure the use of tests are evidence-based. Prognostic and clinical decision making theory are explored in consideration of current and future clinical applications for stratified medicine.

Healthcare Economics and Innovation in Personalised Medicine

This module will provide an overview of the vital importance of economics in healthcare provision, before considering the potential large scale economic benefits promised by personalised approaches to treatment. The effect that the emergence of personalised medicine is having on the economic and business models of big pharma, as well as regulatory agencies will also be addressed, as well the importance of entrepreneurship and small medium enterprises in driving forward healthcare innovation, especially within the personalised medicine space.

Research Project

This module will allow student to undertake an in-depth project in a topic related to Personalised Medicine.

Attendance

Fully Online.

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Start dates

October 2023

January 2024

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Teaching, Learning and Assessment

Teaching and Learning

All course content will be delivered online, the course will be taught using a combination of lectures, tutorials and independent reading. Problem areas identified by students will be further explained during tutorials and lecture material will be supplemented with possible sources of reading material to encourage independent learning.

Assessment

Assessment will be by 100% coursework.

The pass mark for the module and individual pieces of coursework is 50%. Coursework will consist of online tests, discussions and assignments.

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Academic profile

The University employs over 1,000 suitably qualified and experienced academic staff - 59% have PhDs in their subject field and many have professional body recognition.

Courses are taught by staff who are Professors (25%), Readers, Senior Lecturers (20%) or Lecturers (55%).

We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic staff (81%) are accredited fellows of the Higher Education Academy (HEA) by Advanced HE - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.

The profiles of many academic staff can be found on the University’s departmental websites and give a detailed insight into the range of staffing and expertise.  The precise staffing for a course will depend on the department(s) involved and the availability and management of staff.  This is subject to change annually and is confirmed in the timetable issued at the start of the course.

Occasionally, teaching may be supplemented by suitably qualified part-time staff (usually qualified researchers) and specialist guest lecturers. In these cases, all staff are inducted, mostly through our staff development programme ‘First Steps to Teaching’. In some cases, usually for provision in one of our out-centres, Recognised University Teachers are involved, supported by the University in suitable professional development for teaching.

Figures correct for academic year 2021-2022.