Skip to Content

Cheap DNA sequencing will drive a revolution in health care

February 23, 2010

The dream of personalized medicine was one of the driving forces behind the 13-year, $3 billion Human Genome Project. Researchers hoped that once the genetic blueprint was revealed, they could create DNA tests to gauge individuals’ risk for conditions like diabetes and cancer, allowing for targeted screening or preëmptive intervention. Genetic information would help doctors select the right drugs to treat disease in a given patient. Such advances would dramatically improve medicine and simultaneously lower costs by eliminating pointless treatments and reducing adverse drug reactions.

Delivering on these promises has been an uphill struggle. Some diseases, like Huntington’s, are caused by mutations in a single gene. But for the most part, when our risk of developing a given condition depends on multiple genes, identifying them is difficult. Even when the genes linked to a condition are identified, using that knowledge to select treatments has proved tough (see “Drowning in Data”). We now have the 1.0 version of personalized medicine, in which relatively simple genetic tests can provide information on whether one patient will benefit from a certain cancer drug or how big a dose of blood thinner another should receive. But there are signs that personalized medicine will soon get more sophisticated. Ever cheaper genetic sequencing means that researchers are getting more and more genomic information, from which they can tease out subtle genetic variations that explain why two otherwise similar people can have very different medical destinies. Within the next few years, it will become cheaper to have your genome sequenced than to get an MRI (see “A Moore’s Law for Genetics”). Figuring out how to use that information to improve your medical care is personalized medicine’s next great challenge.

Keep Reading

Most Popular

This new data poisoning tool lets artists fight back against generative AI

The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. 

The Biggest Questions: What is death?

New neuroscience is challenging our understanding of the dying process—bringing opportunities for the living.

Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist

An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.

How to fix the internet

If we want online discourse to improve, we need to move beyond the big platforms.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.