Principal Investigator: Dr Spiros Denaxas
Institution: University College London (UCL)Tags: 58356, disease classification, electronic health records, genomic medicine, Machine Learning, phenotyping, Precision Medicine
Our understanding of human disease and the different factors which influence our health changes all the time through but the manner in which we define diseases is still based on what clinicians can directly observe. As a result, we have a one-size-fits-all medication treatment for many diseases which does not benefit all patients as they might have the same disease but have significant differences in their genetic material which influenced if the treatment will work or how well it will work. The aims of this project is to use analytical approaches in order to identify and describe how the same disease can vary across different patients. To do so, we will use data from many different aspects of human health available in the UK Biobank, from genetic data and blood data to phenotypic data that get collected when we interact with the healthcare system. The result of this study (which will last 36 months) will improve human health and healthcare by enabling clinicians to accurately identify who will benefit from what drug and by providing insights into the creation of better drugs for patients who do not currently benefit from existing treatments.