Program Overview

Personalised Medicine (CHLD0092)

Key Information

The Personalised Medicine module is offered by the Faculty of Population Health Sciences, with the UCL GOS Institute of Child Health as the teaching department. This module has a credit value of 15.

Restrictions

There are no restrictions listed for this module.

Alternative Credit Options

There are no alternative credit options available for this module.

Description

Summary

Personalised medicine represents the next generation of healthcare research and delivery, with the potential to fundamentally alter the way healthcare is provided, offering significant benefits to patients. This module aims to equip students with the novel tools necessary to deliver personalised medicine in both the health sector and industry. Students will learn how individual multi-omic profiles (genetic, protein, biochemical, and gut microbiome) guide decisions regarding disease prevention, diagnosis, and treatment.

Aims

This module aims to provide students with an understanding of the basic principles of personalised medicine. It covers the development of new personalised diagnostic tests and the expanding use of biomarkers tailored to the individual, enabling the identification of the molecular cause of disease and supporting the development of novel, more precisely targeted treatments. Specifically, students will learn about the entire process, from using multi-omics technologies for biomarker discovery and patient stratification for clinical trials, to the use of pharmacogenetics for personalised drug use.

Learning Outcomes and Objectives

Through assessments on this module, students will gain experience in transferable skills such as oral presentation, communicating to a lay audience, scientific writing, appraisal, and maintaining scientific dialogue in the context of personalised medicine.

Upon successful completion of the module, students will be able to:

1. Understand ways to measure risk for a range of diseases based on environmental exposures, genetic factors, and interactions between the two.
2. Discover biological markers that signal increased or decreased risk of developing diseases.
3. Utilize multi-omics disease models and biobanks for biomarker discovery.
4. Apply mobile health (medical devices) technologies to correlate activity, physiological measures, and environmental exposures with health outcomes.
5. Recognize the importance of data sharing to improve patients' health.
6. Stratify patients to enable trials of targeted therapies.
7. Understand direct-to-consumer testing.
8. Develop skills in presenting scientific ideas and data to patients and the public.
9. Explore applications of Artificial Intelligence in Personalised Medicine.
10. Learn about innovation and entrepreneurship in Personalised Medicine.

Who is this Module for?

This module is compulsory for the MSc Cell, Gene and Novel Therapies: Personalised Medicine and an optional module for MSc Cell, Gene and Novel Therapies: Cell and Molecular Therapies and MSc Precision Medicine programmes. It is open to all with an interest in personalised medicine and science communication for the public. Note that attendance at discussion groups is mandatory.

Teaching and Learning Method

The module is designed to be highly interactive, with a blend of taught lectures and interactive applied case studies, interactive activities, discussion groups, self-taught sessions, tutorials, and practices (including relevant database searches). It will also utilize virtual reality applications to explore the possibilities of personalised medicine.

Selected Reading List

1. personalised-medicine.pdf
2. Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015 Feb 26;372(9):793-5.
3. Kenny J, Forsythe E, Beales P, Bacchelli C. Toward personalized medicine in Bardet-Biedl syndrome. Per Med. 2017 Sep;14(5):447-456.
4. Doble B, Harris A, Thomas DM, Fox S, Lorgelly P. Multiomics medicine in oncology: assessing effectiveness, cost-effectiveness and future research priorities for the molecularly unique individual. Pharmacogenomics. 2013 Sep;14(12).
5. Tebani A, Afonso C, Marret S, Bekri S. Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations. Int J Mol Sci. 2016 Sep 14;17(9).
6. Chen R, Mias GI, Li-Pook-Than J, Jiang L, Lam HY, Chen R, Miriami E, Karczewski KJ, Hariharan M, Dewey FE, Cheng Y, Clark MJ, Im H, Habegger L, Balasubramanian S, O'Huallachain M, Dudley JT, Hillenmeyer S, Haraksingh R, Sharon D, Euskirchen G, Lacroute P, Bettinger K, Boyle AP, Kasowski M, Grubert F, Seki S, Garcia M, Whirl-Carrillo M, Gallardo M, Blasco MA, Greenberg PL, Snyder P, Klein TE, Altman RB, Butte AJ, Ashley EA, Gerstein M, Nadeau KC, Tang H, Snyder M. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell. 2012 Mar 16;148(6).
7. Aronson SJ, Rehm HL. Building the foundation for genomics in precision medicine. Nature. 2015 Oct 15;526(7573):336-42.
8. Zaman A, Bivona TG. Emerging application of genomics-guided therapeutics in personalized lung cancer treatment. Ann Transl Med. 2018 May;6(9):160.
9. van Vollenhoven RF. Genotypes, phenotypes and treatment with immunomodulators in the rheumatic diseases. J Intern Med. 2018 Jun 16.
10. Hampel H, Vergallo A, Giorgi FS, Kim SH, Depypere H, Graziani M, Saidi A, Nisticò R, Lista S; Alzheimer Precision Medicine Initiative (APMI). Precision medicine and drug development in Alzheimer's disease: The importance of sexual dimorphism and patient stratification. Front Neuroendocrinol. 2018 Jun 12.
11. Tasian SK. Acute myeloid leukemia chimeric antigen receptor T-cell immunotherapy: how far up the road have we traveled? Ther Adv Hematol. 2018 Jun;9(6):135-148.
12. Musunuru K, Sheikh F, Gupta RM, Houser SR, Maher KO, Milan DJ, Terzic A, Wu JC; American Heart Association Council on Functional Genomics and Translational Biology; Council on Cardiovascular Disease in the Young; and Council on Cardiovascular and Stroke Nursing. Induced Pluripotent Stem Cells for Cardiovascular Disease Modeling and Precision Medicine: A Scientific Statement From the American Heart Association. Circ Genom Precis Med. 2018 Jan;11(1).

Module Deliveries for 2026/27 Academic Year

Intended Teaching Term: Terms 1 and 2

• Postgraduate (FHEQ Level 7)

Teaching and Assessment

• Mode of study: In person
• Methods of assessment:
  • 30% Coursework
  • 70% Viva or oral presentation
• Mark scheme: Numeric Marks

Other Information

• Number of students on module in previous year: 28
• Module leader: Dr Wendy Heywood

Last Updated

This module description was last updated on 10th March 2026.