You might be one of the millions of people who have taken a cheek swab, mailed it in to a company, and excitedly waited for a summary of the clues your DNA provided about your ancestral background. The popularity of these services doesn’t seem to be slowing, and they are now expanding into assessments of health risk. However, some people might be disappointed by the relatively small number of diseases they can get this information about.
The good news is that AI applications to genetics are making major strides in unlocking the link between genetics and a whole host of health conditions by leveraging large datasets and impressive computing power.
It’s been nearly 15 years since the Human Genome Project led to a complete mapping of the human blueprint, raising the possibility of precision medicine at the level of the gene. After all these years, however, we still know very little about how genes interact with the environment to shape health risks.
Shedding Light on Individual Health Risks
One way AI is helping to close this gap in understanding is providing insights into the impact of DNA on basic molecular biology. For example, Deep Genomics is developing the capability to interpret DNA by creating a system that predicts the molecular effects of genetic variation. Their database is able to explain how hundreds of millions of genetic variations can have an impact at the cell level, with the hope that this knowledge can then be applied to understanding a wide range of diseases.
Consumer genetics companies such as 23andMe and Rthm represent a few of the first movers in this domain. They have developed consumerized genetic diagnostic tools to help individuals understand their genetic makeup. With Rthm, users are able to go one step further and leverage the insights produced from their genetic test to implement changes to their everyday routine through a mobile application, all in real time.
Understanding health risks is one important use of our knowledge about genes, but an even more exciting application is the possibility of medicine personalized to our particular genetic makeup. AI is currently being used to figure out which cancer treatments are more or less likely to work for people with different genes. By performing genetic tests on the cancer cells and on normal cells, doctors may be able to customize treatment to each patient’s needs, increasing effectiveness and reducing negative side effects.
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