Integrating genomic and electronic health data for drug-discovery

Lead Research Organisation: University College London
Department Name: Institute of Health Informatics


Drug discovery process faces major challenges that threat their sustainability, and this has wider implications to society in general. A major problem is that standard pre-clinical models for drug-target selection and validation had a poor predictive capacity to corrective identify valid drug-targets. An alternative way to improve the process of drug-target selection and validation is to use large-scale human genomics in conjunction with other omics (e.g. proteomics, radiomics) and electronic health record (EHR). A systematic, scalable and computational robust integration of genetic, other-omics and EHR data poses multiple methodological challenges:
1. The use of complex, longitudinal data from multiple sources to stratify patients by their disease trajectories or response to treatment, in order to use these strata to determine more precisely the phenotypic consequences of genetic variation and hence suggest drug targets that enable precision medicine, or more generally, the definition of phenotypes relevant to drug discovery e.g. focused on disease progression rather than occurrence.
2. The integration of EHR data with 'omics data (expression, protein etc) to understand the causal pathway from genetic variant to disease endpoint This project aims to contribute to the development and application of novel analytics that capitalise on the integration of Big Data in the form of national electronic health record, genomics and other omics (including imaging) to improve the selection and validation of drug-targets.
In this project, I will develop methods to solve these and related questions. This project will help improve the drug target identification and lead compound discovery process.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R512400/1 01/10/2017 31/03/2022
1947579 Studentship EP/R512400/1 02/10/2017 30/12/2021 Kamran Khan