big data

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Mooning cancer

Buzzing aroundBuzzing around Tranquility Base.

We can only applaud a big push to add resources for attacking cancer, but it’s a mistake to call this newly announced federal initiative a moonshot. We won’t land on the cancer cure moon in a decade.

Never mind what it says about our society that our only common metaphor for a large successful national effort is more than a half-century old. The metaphor doesn’t work here.

The actual moon shot built on existing engineering. And the National Aeronautics and Space Administration created its infrastructure from scratch. That’s not possible in our health system, and its irrationalities are increasingly slowing down the grand march toward more personalized medicine.

If the space program had been run like our current health system, computers at Mission Control in Houston and the launch site at Cape Canaveral would not have talked to each other.

Promising efforts like the American Society of Clinical Oncology’s CancerLinQ program are threatened by our inability and unwillingness to share clinical data. As Otis Brawley, chief medical and scientific officer for the American Cancer Society, wrote this week in STAT, “real or perceived privacy issues, along with difficulties connecting disparate electronic health records, may scuttle it.”

As cancer research rockets ahead in the lab, clinical studies may lag years or decades behind. We can take steps to speed them up, but there’s no quick fix.

If NASA had worked like our medical system, the rocket engine makers would have charged whatever they liked. Contrast that with the famous quote from astronaut John Glenn about how he felt before liftoff: “you were sitting on top of two million parts — all built by the lowest bidder on a government contract.”

And if we had run space like medicine, all engineering decisions would have been second-guessed by non-engineers.

The world’s largest cancer center, MD Anderson in Houston, launched its own Moon Shots cancer program three years ago. The initiative helped MDA raise about $300 million, sharpen its priorities and add a few important efforts. And it seems to have achieved progress in a few fairly narrow treatment areas. That’s good news and about what we should expect so far.

There’s nothing theoretical to me about the suffering that cancer inflicts on human lives. I’m happy to see our vice president bringing in the best and brightest to plan an initiative, and especially to figure how to connect the data silos.

But we need another metaphor to help us conceptualize the effort. (And no, not the War on Cancer.) Maybe we can try a title based more closely on another major healthcare initiative (Obamacan? Bidencare?). Grand national projects can live or die by their metaphors.

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Man petabytes dog

husky

One of the earliest stories I wrote about genomics past the gee-whiz aspects of the Human Genome Project covered the first whole-genome sequencing of a dog. Kerstin Lindblad-Toh of the Broad Institute patiently explained the project to me, and scientists who used dog models to study inherited blindness told me why they were more than excited about the prospects.

More than a decade later as I’m putting together a special report on big data for Nature, the genomic revolution has marched ahead, well, much as predicted.

The cost of genomic sequencing has dropped arguably faster than any other technology in human history. Research initiatives that most of us haven’t heard about are gathering genomic data on hundreds of thousands of people. This flood of data is multiplied with data from proteomics and other omics now scaling up to the genomic scale. We talk casually about petabytes (millions of gigabytes). Data scientists, many of them coming in from fields outside biology, are integrating these data and making some astonishingly good predictions about what drugs might work for a given condition, without needing any new wet-lab work. We’ve seen wonderful progress in stem cells and cellular models and genetic engineering tools. And this revolution is on television, also websites, social media and an entirely sufficient plenitude of TED talks.

Not so much in the clinic, though.

Of course omic research on many diseases is starting to pay off for actual patients—for example, The Cancer Genome Atlas has spun off clues for real advances in many cancers—and its grand march points straight ahead through enormous but movable objects.

But clinical steps are slow. Part of the reason is the sheer complexity of disease, for instance the ways cancers duck and weave to dodge treatments. And, of course, clinical trials can’t be rushed.

Last week I asked one neuroscientist why we still lack drugs that treat the causes of neurodegenerative diseases, as opposed to their symptoms. She responded, reasonably enough, that it takes years to build better lab models of the disease and push findings from those models into the long tunnel of pre-clinical work toward trials. She expected that some of the compounds coming from her work will help. She didn’t predict home runs.

But we haven’t lost the gee-whiz discoveries and our faith that they’ll end up in the clinic in our lifetimes. My favorite: Scientists can take a human skin cell, bombard it with select small molecules until it morphs into a reasonable facsimile of an insulin–producing cell (a notoriously fickle beast) and produce such cells in the millions. Maybe those cells will arrive in the next decade, bringing actual cures. And although I don’t follow discoveries in dog proteomics, I see that University of California/Berkeley researchers have restored vision to blind dogs via genetic therapy. Progress, yes. Dogged research!