Interpretation and Clinical Application of Genomic Data

Overview

The Interpretation and Clinical Application of Genomic Data programme from St George's, University of London consists of four modules which are firmly embedded in the Clinical Genetics training pathway; utilising but restructuring training, so that it runs in parallel with full time clinical duties and embeds academic teaching with clinical application. 

The course will enable you to feel proficient in the interpretation of genomic data, and confident in making clinical management decisions on the basis of your interpretation. It will also provide you with the knowledge, skills and attitudes to disseminate your expert knowledge through the wider medical workforce.

• Bespoke training for clinical geneticists

• Teaching runs in parallel with full time clinical duties and embeds academic teaching with clinical application

• Course is part of package of genomic educational initiatives run through the University

• St George’s clinical research ranked 4th for impact

Career

The aim of the PGCert ICAG is to develop you into a self-reliant and autonomous learner, capable of independent and novel thinking and having developed the skills to enable you to apply your learning to clinical practice.

The learning objectives will be achieved through a teaching scheme delivered through three key domains: knowledge, skills and attitudes. 

The acquisition of knowledge will be achieved through a blended learning approach of face-to-face/online teaching sessions and workshops and self-directed learning through online and library resources. A secure knowledge base will then provide a platform to develop the skills of data interpretation in the context of clinical phenotyping. 

This will primarily be achieved through engagement at workshop sessions, assignments and portfolio development. The third domain, attitude, emphasises the need for the clinician to develop the skills to effectively communicate complex genomic data and discuss ethical considerations such as the identification of incidental findings.