Skip to Content

Editor’s letter: The precision medicine issue

Precision medicine has led to incredibly effective treatments for cancer and inherited disease. But not everyone gets treated.

October 23, 2018

It’s been nearly two decades since the first human genome was sequenced. That achievement opened up the promise of drugs and treatments perfectly tailored to each person’s DNA. But personalized or “precision” medicine has always felt a bit like flying cars, sexbots, or lab-grown meat—one of those things we’re perpetually being promised but never quite getting. This issue of MIT Technology Review makes the case that, in fact, the age of precision medicine has been slowly dawning on us all this time—and we’re unprepared.

What’s changing fastest now is the sheer volume of medical data available, and the tools for analyzing it. As Antonio Regalado points out in his opening essay, the number of people getting their DNA tested is now in the tens of millions and doubling each year.

By pairing DNA data with people’s medical records, algorithms can predict your risk of certain common diseases and suggest drugs and diets to ward them off, as Ali Torkamani and Erik Topol explain. Cancer drugs are now being customized to individual patients, as Adam Piore reports. Epigenetic data can forecast how long you’ll live, writes Karen Weintraub, and new “senolytic” drugs might keep age-related ailments at bay for more of that time, reports Stephen S. Hall.

Photo of Editor in chief Gideon Lichfield
NEPHI NIVEN

Not just DNA sequences but data of all kinds is being scooped up and crunched in vastly greater quantities than before. As Rachel Metz explains, it’s becoming possible to track mental illness just by monitoring how you tap, type, and swipe on your phone.

Better treatments and healthier living aren’t the only benefits. Doctors like Rahul Parikh hope to be able to spend more time getting to know their patients as algorithms take on the more routine tasks. In a UK trial, AI systems are already replacing physicians for simple consultations, as Douglas Heaven reports. That could help meet the ballooning health-care needs of an aging population.

The problem? As medicine gets more personalized, it risks getting more unequal. Our cover story is Regalado’s gripping and troubling account of the parents who raise millions of dollars to finance gene-therapy cures for their children’s ultra-rare diseases. Are they trailblazers for a technology that will one day provide cheap, customized care to everyone, or harbingers of a future in which only the super-wealthy and crowdfunding whizzes are saved? IVF combined with genetic screening can weed fatal diseases out of a family for good, but, Laura Hercher argues, it could also lead to two genetically distinct human castes—one rich and disease-free, the other poor and disease-ridden. The rich and well educated won’t only be better able to afford boutique treatments; they’ll be more likely to have the technology, and hence the data, that helps them avoid falling ill in the first place.

All this has more than merely medical consequences. Nathaniel Comfort warns that our growing ability to find genetic correlations with things like intelligence is threatening to revive the ugly dogma of eugenics. And what, asks Mary Madden, can any of us do to keep tabs on how the oceans of data about us are being used, or misused?

We’ll face this question even in death. As Courtney Humphries reports, people now in their 30s will have generated enough data by the time they die to power quite convincing digital avatars of themselves. So who will own you when you’re gone? At least Simson Garfinkel has some advice on how to prepare.

This issue of the magazine, therefore, spans the entire arc of human existence, from before you’re born until after you die. Through it all runs a simple question. We know that in health care, human beings are unequal. But just how unequal are we willing to be?

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

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.