Bioethics Blogs

Precision Medicine: Using Genomic Data to Predict Drug Side Effects and Benefits

People with type 2 diabetes are at increased risk for heart attacks, stroke, and other forms of cardiovascular disease, and at an earlier age than other people. Several years ago, the Food and Drug Administration (FDA) recommended that drug developers take special care to show that potential drugs to treat diabetes don’t adversely affect the cardiovascular system [1]. The challenge in implementing that laudable exhortation is that a drug’s long-term health risks may not become clear until thousands or even tens of thousands of people have received it over the course of many years, sometimes even decades.

Now, a large international study, partly funded by NIH, offers some good news: proof-of-principle that “Big Data” tools can help to identify a drug’s potential side effects much earlier in the drug development process [2]. The study, which analyzed vast troves of genomic and clinical data collected over many years from more than 50,000 people with and without diabetes, indicates that anti-diabetes therapies that lower glucose by targeting the product of a specific gene, called GLP1R, are unlikely to boost the risk of cardiovascular disease. In fact, the evidence suggests that such drugs might even offer some protection against heart disease.

Genetic approaches have increasingly been used to identify potentially promising new drug targets. In the study reported in Science Translational Medicine, researchers led by Robert Scott and Nick Wareham from the University of Cambridge, England, and Dawn Waterworth from GlaxoSmithKline, King of Prussia, PA, also wanted to explore whether genomic data could yield important clues about the potential side effects of drugs targeting particular genes.

The views, opinions and positions expressed by these authors and blogs are theirs and do not necessarily represent that of the Bioethics Research Library and Kennedy Institute of Ethics or Georgetown University.