Biology Will Be the Next Great Computing Platform

Biology Will Be the Next Great Computing Platform

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Edward Carvalho-Monaghan

In some ways, Synthego looks like any other Silicon Valley startup. Inside its beige business park facilities, a five-minute drive from Facebook HQ, rows of nondescript black server racks whir and blink and vent. But inside the metal shelving, the company isn’t pushing around ones and zeros to keep the internet running. It’s making molecules to rewrite the code of life.

Crispr, the powerful gene-editing tool, is revolutionizing the speed and scope with which scientists can modify the DNA of organisms, including human cells. So many people want to use it—from academic researchers to agtech companies to biopharma firms—that new companies are popping up to staunch the demand. Companies like Synthego, which is using a combination of software engineering and hardware automation to become the Amazon of genome engineering. And Inscripta, which wants to be the Apple. And Twist Biosciences, which could be the Intel.

All these analogies to the computing industry are more than just wordplay. Crispr is making biology more programmable than ever before. And the biotech execs staking their claims in Crispr’s backend systems have read their Silicon Valley history. They’re betting biology will be the next great computing platform, DNA will be the code that runs it, and Crispr will be the programming language.

Synthego was founded by a pair of fraternal software engineers fresh off a tour working for Elon Musk’s SpaceX. Brothers Paul and Michael Dabrowski aren’t biologists. But in Crispr they saw a unique opportunity to take the principles of agile design they learned building rockets and apply it to making gene editing tools. Their first order of business was using miniaturization and automation to drastically speed up research and product development. They started by packing an airplane hangar’s worth of intelligent instrumentation into machines stacked in those server racks. Each one orchestrates a biochemical ballet, transforming a string of in silico instructions into the company’s first product: a custom Crispr kit.

To order a kit, scientists log on to Synthego’s design portal and pick out one of the roughly 5,000 organisms they might want to edit from Synthego’s genome library—everything from E. coli to Homo sapiens—and the gene they want to knock out. The company’s predictive software then kicks out a couple optimized options for synthetic guide RNAs—the genetic guides that get Crispr’s DNA-cutting proteins where they need to go. After the order is completed, software directs compressors and pumps to push chemical reagents into the rows of instruments, mixing the fluids and catalyzing the 100,000 reactions needed to create a single batch of kits. Within a week, a delivery shows up at the lab’s doorstep: everything a lab tech needs to begin manipulating the genome of a lab rat or zebrafish or dish of HeLa cells. They simply add their Crispr protein and start injecting.

“Being able to do that in a parallel way is the novel part,” says Paul Dabrowski, who estimates that Synthego cuts down the time it takes for a scientists to perform gene edits from several months to just one. Those services are in high demand. While coy about exact numbers, Dabrowski said Synthego is putting out hundreds to thousands of kits a day. But they’ll soon be more, and Synthego is ramping up accordingly. They doubled their space last year and this year they’re doubling it again.

But they’re not just adding more rows of server rack-mounted machines. They’re also adding services. Starting later this month scientists will be able to order custom-Crispr’d human cell lines, an important tool for people making potentially life-saving medicines. “We’ve got hundreds of thousands of brilliant PhDs and bench researchers who have to spend up to 50 percent of their time just taking care of these cells,” says Dabrowski. Instead, he wants them to be able to go from designing an experiment to doing it in just a few clicks.

This is all well and good for academic researchers using Crispr for basic science. But for companies that want to use Synthego’s tools to speed up product development, they still have to pay steep licensing fees to the Crispr companies who own the foundational Crispr/Cas9 IP—the patents of which remain in legal limbo. According to Inscripta CEO Kevin Ness, that technology bottleneck is creating financial barriers to innovation. Which is why his company’s first move was to release a different gene-editing enzyme called MAD7—you can think of it like a Crispr/Cas9 knockoff, but legal—free for R&D uses. Inscripta will charge a single-digit royalty, far below market standards, to use MAD7 in manufacturing products or therapeutics.

Right now it’s the company’s only revenue stream—well, let’s call it a trickle. But Ness has his reasons. “It’s not a trick or a ploy. We’re trying to get more people into the game now, by democratizing access to this family of enzymes,” he says. It’s a page from the Steve Jobs playbook; get them hooked on the MADzyme platform, down the line sell them personal hardware. Inscripta is working on a benchtop instrument where you design your gene editor and it kicks out your constructs on the spot. “We’re trying to build the tools to standardize the process of reading, writing, and testing genomes in living cells so that you don’t have to be a wizard to get it to work,” says Ness. “Everybody can push a button.”

If Inscripta is working on a biological equivalent of the personal computer, Twist Biosciences is working a level down, where the processors are. The San Francisco-based startup manufactures custom strands of synthetic DNA on semiconductor chips, to crank out the As, Ts, Cs, and Gs that are the building blocks of biology. From the Crispr guides Twist produces on a single chip, researchers can make up to a million edits. Just as the exponential miniaturization of silicon wafers propelled the computing industry forward, so too will the massive parallelization of gene editing push the boundaries of biology into the future.

A shorter version of this article appears in the May issue. Subscribe now.


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