| Title: | Harnessing associations of genetic and phenotypic traits for drug target validation, Ref: 12113. |
| Lead Institution: | University College London |
| Principal investigator: | Dr Amand Schmidt |
Application 12113
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About
We aim to identify and select drug targets for common human diseases and create repurposing hypotheses for existing medications, using associations of genetic and phenotypic traits as natural randomised control trials (RCTs) Bringing a new drug to market is protracted, expensive, and uncertain. Failure at the late, clinical stages of drug development has become a surprisingly common, productivity-limiting hurdle in drug development, regardless of the therapeutic area (2-4). Genetic studies are an alternative source of randomised human evidence, and can be deployed to inform drug development ahead of critical decision points in the drug development pathway, for example to help distinguish on- versus off-target (adverse) effects of a first in class compound (7), to repurpose drugs licensed in one condition for another (10), or to aid drug developers' decision to move a compound forward (1). Using the genetic variant as a randomized variable (i.e., a Mendelian randomization study) we will explore the association between genes and a cardiovascular endpoints (e.g., stroke) and genes and biomarkers (e.g., LDL-cholesterol). Given that genes are allocated at random at conception, these gene, phenotype/biomarker associations are unaffected by confounding or reverse causation and represent the true causal effect of intervening on a gene. Depending on the gene, this information can be used to repurpose existing drugs or better inform drug developers which gene to develop de novo compounds for. The full UK Biobank cohort will be included to maximise statistical power for genetic analyses2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 8863 | Prioritising genetic findings for drug target identification and validation | Nikita Hukerikar (+4) | 2024 | Atherosclerosis |
| 10423 | Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics | María Gordillo-Marañón (+20) | 2021 | Nature Communications |
Enabling scientific discoveries that improve human health