Applied Biomedical Science

• Case Studies in Drug Discovery and Development (15 credits)
• Genomic Technologies in Clinical Diagnostics (15 credits)
• Research Methods and Management (15 credits)
• Clinical Trials (15 credits)

• Big Data in Biomedicine (30 credits)
• Personalised Medicine (15 credits)
• Population Health Research (15 credits)

• Research Project (60 credits)

Understanding of large biomedical datasets and data analysis skills are now required at all stages of the translational research continuum; training in this area is thus greatly desired by potential employers.

Since the human genome was first sequenced in 2003, the biomedical sciences have experienced an explosion of DNA sequence data, functional genomics collections and epidemiological information. The exponential progress in this area was made possible by the emergence of novel technologies used to sequence DNA, investigate gene function and to store and analyse large amounts of data. New technologies, comprehensive datasets and advances in data storage have ushered in the field of ‘systems biology’, a catchphrase used in reference to growing efforts of using holistic approaches to study complex problems in biology and medicine. Availability of properly trained scientists who can analyse these data is now becoming the limiting factor in industry and academia.

The first part of this module focuses on malaria, a disease of global importance. Sessions go through a series of case studies that explore very comprehensively the pathophysiology of malaria, plus preclinical and clinical studies that led to the development of antimalarials. The second half consists of presentations and workshops by translational scientists at St George’s talking about their own research.

This module will introduce students to fundamental principles and concepts of clinical trials. Particular attention will be given to randomised controlled trials (RCTs), which are considered to be the most robust approach to testing new treatments. Students will learn how to appraise the validity and reliability of trial results and how trials are managed and conducted in real-world settings. Students will also gain an appreciation of the ethical and regulatory requirements surrounding RCTs.

Students will complete practical sessions each week based on the topic of the preceding lecture. Work from the practical sessions will be documented in a practical session notebook, which will count towards the ICA helping to consolidate learning and knowledge. The final sessions of the module will draw together the key themes explored with a presentation on landmark trials from experts in the field.

Importantly, a one-day face-to-face good clinical practice (GCP) course will form part of the module with a certificate awarded on successful completion. This GCP certificate is a key requirement for those working on clinical trials in any sector. The module thus provides knowledge, skills and a qualification immediately relevant for potential employment in the area of clinical trials management.

Powerful new technologies are transforming healthcare. Over the last decade technologies have emerged that allow scientists to interrogate the genome at the chromosome or single nucleotide level in just a few days, resulting in greater availability of genomic data, which is increasingly being used to determine health management. Genomics have become pivotal in various areas of current translational medicine such as diagnostics, pharmacogenetics / precision medicine, and population genetics.

This online module focuses upon these fundamental genomic technologies. Students will familiarise themselves with the molecular and cytogenetic techniques currently employed in the diagnostic laboratories and, using their knowledge, develop testing stratagems for particular clinical condition(s). Students will also gain an in-depth understanding of genetic technologies currently undertaken in the research setting, and the challenges involved in the implementation of novel technologies in the diagnostic setting.

The ultimate goal of personalised, or precision, medicine is to create healthcare strategies that are tailored to each individual patient. This will be achieved by integrating molecular information with traditional clinical and pathological signs of disease. Advances in genomic technologies have provided new perspectives across medicine, particularly in screening, diagnosis, disease classification and treatment. This module explores how this research is being translated intoclinical practice to make personalised medicine a reality.

Personalised medicine is not limited to pharmacogenetics (which examines the effect of genetic variation on drug targets, metabolism, efficacy and toxicity) but looks more broadly at how molecular profiling can influence health outcomes. Examples include molecular therapies used in oncology, advances in pre-natal screening and management of infection. We also consider issues surrounding personalised medicine, including patient responses to genetic testing, the challenge of translating research results into clinical practice, genetic discrimination, and regulation.

Examples are drawn from cancer, infection and a range of clinical specialties.

Population-based policies and changes in clinical practice rely on data analyses of all forms: descriptive and inferential. The latter refers to studies aiming at producing reproducible results or estimates which can be generalised to large populations. Understanding patterns in population health related to disease demographics, lifestyle, socioeconomic features, environmental exposures, and interventions are quintessential in designing evidenced-based public health policies.

This module will equip students with a body of knowledge on epidemiology of public health, study designs, measures of associations between diseases and potential risk factors and associated statistical methods which quantify their magnitude and statistical significance.

This module will walk the students through all phases of research development lifecycle: from initial stage of research question and the importance of pilot and feasibility studies to main complex observational epidemiological settings such as cross-sectional, cohort, case control and longitudinal studies. The associated statistical concepts and techniques will include not only simple hypotheses testing but also basic elements of statistical modelling addressing bias and confounding in observational studies and methods to minimise them.

The Research Methods and Management module tightly integrates with the research project by introducing students to the conceptual, technical, regulatory and ethical aspects of conducting research. The module also covers a number of transferable skills related to self-directed learning, literature analysis, communication, and time management. Teaching strategies will include a “flipped classroom” approach involving self-directed learning followed by class presentations, discussions and tutorials. The principal assessment is a research proposal on the subject of students’ laboratory project.

The supervised research project constitutes a central learning activity by providing immersive, work-based training in translational science. A research project involves choosing a subject, formulating a specific research question or aim, devising a research strategy to address this question, performing the research and analysing the resulting data. Project background, experimental procedures, results and discussion are written up as a 15,000 to 25,000-word dissertation and presented orally to an audience with the aid of a poster.

At the beginning of the course students will be presented with a list of available research projects, and they are asked to explore possible subjects in meetings with potential supervisors. Students choose a project by the end of the first month. The course has been designed such that the research project interdigitates, wherever possible, with the taught modules. The 'Case Studies in Drug Development' and 'Big Data in Biomedicine' modules will include assignments requiring reading and presenting scientific literature, and students will have opportunities to choose material with relevance to their project.

Following the first term, students will prepare a research proposal on the subject of their research project.