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Approved Research

Complementing human data centric approaches to discover novel therapies and biomarkers at Novo Nordisk

Principal Investigator: Dr Dmitry Shungin
Approved Research ID: 86252
Approval date: September 14th 2022

Lay summary

Despite tremendous advances in contemporary biomedical research, the success rates of drug discovery from initial idea to approved medicines remain low resulting in substantial financial burden on healthcare systems around the globe. Large-scale population-level datasets with genetic and other omics data layers such as UK Biobank are one of the key resources of real-world human evidence that could improve and accelerate the process of new drug discovery. Such collections of data open new opportunities both to personalize medicines by finding sub-populations of individuals with favourable treatment response; as well as to efficiently estimate drug efficacy and safety at early stages of drug development process. A rich panorama of phenotypes available in UK Biobank, such as imaging, can further strengthen attempts to search for new therapies when combined with omics data.

Thus, the aim of this proposal is to utilize multiple layers of data from UK Biobank to potentiate and complement novel target and biomarker discovery efforts in Novo Nordisk with focus on multiple therapeutic areas, including but not limited to obesity, diabetes, cardiovascular, kidney and liver diseases.

To achieve that aim we will utilize all available UK Biobank data to identify new and re-purpose existing targets and biomarkers within Novo Nordisk disease portfolio. Using state of the art statistical and bioinformatic methods we will connect and cross-reference individual genetic profiles, clinical markers, metabolomics and proteomics readouts, imaging data, as well as other available data points to obtain the most extensive evidence linking particular drug targets with relevant diseases at multiple levels of biological comprehension. This systematic approach will allow for faster drug development cycles, as well as will streamline spending of resources by prioritizing therapies that have the highest potential to help people suffering from key chronic conditions.

Using plethora of UK Biobank data, we will also strive to identify sub-groups of individuals with differences in disease features or treatment responses which will help us to personalize therapies for people who benefit the most and guide our clinical trials to be more personalized, with less risk to patients and faster trial completion as a result.

Thus, evidence from UK Biobank combined with other resources in Novo Nordisk will galvanize development of novel prevention strategies and innovative therapies that will improve and prolong lives of patients burdened with chronic conditions around the globe. This proposal therefore fits well with the UK Biobank's purpose of improving the prevention and treatment of illness.