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Drug Manufacturing Has One Huge Flaw. This Synthetic Biology Startup Just Raised $200 Million To Fix It.

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In the shadow of Boston’s infamous Fenway Park stadium the room is lit up by a huge, fluorescent, dynamically morphing orb.

It’s a video of a cell, nature’s infinite nanofactory, churning through many millions of molecules every second.

On the screen in front of me, reminiscent of the base-loop of a Red Sox home run, I’m watching a biological circuit reformatted through software. The basic building blocks of life laid out, stepwise, able to predict the performance of cellular components as if modeling those of a rocketship.

“Every cell is capable of computing. Perceiving environmental signals, information processing, turning genes on and off,says my host Alec Nielsen, CEO and co-founder of Asimov, a company building the tools to design living systems.

“The ability to engineer this gift of evolution is, in my view, going to be the most meaningful and impactful technology that humans have ever developed.”

It’s a vision shared by investors and over 25 customers including top-ten pharmaceutical and biotechnology companies, which is why Asimov has this week attracted new funding worth $200million to scale its therapeutic discovery toolkit.

Financing includes a $175M Series B led by the Canada Pension Plan Investment Board (CPP Investments), with participation from Fidelity Investments, KDT, Casdin Capital, Pillar, and Andreessen Horowitz (a16z).

The drug discovery bottleneck

Asimov is a spin-out of Chris Voigt’s lab at MIT, co-founded by Nielsen along with Voigt, Raja Srinivas, and Doug Densmore of Boston University.

“I really like the whole school of thought,” says Nielsen on what inspired him to join the Voigt lab as a PhD student. “How do we get away from brute force trial and error and make the field more of an engineering discipline?”

It’s an important philosophy to bring cell-derived therapeutic discovery up to speed.

Nielsen cites Scott Gottlieb, former commissioner of the US Food and Drug Administration. He said that "for normal drugs 80% of the complexity is in the clinical testing. With cell and gene therapy, it’s inverted: 80% of the complexity is the manufacturing."

The manufacturing process is a huge bottleneck, particularly when using mammalian cells. Even after a lengthy discovery process has revealed a new therapy, it’s tough to produce antibodies or RNA in sufficient quantities and purities.

“Therapeutics that used to be the stuff of science fiction are now reaching patients,”

says Nielsen. “But the technology to design and manufacture these medicines hasn’t kept up. The trial and error approach does not scale.”

Better design tools for biology

Nielsen draws an eloquent analogy between genetic engineering now versus computer science in the 1970s. Then, an image of Intel engineers carving out a stencil for a semiconductor circuit by hand. Now you can hold a supercomputer packed with 10 million transistors.

That’s where Asimov aims to take biology by applying the principles of engineering, and a neat toolkit that combines gene edited mammalian cell lines with a computer-aided design platform they call Kernel.

It’s a clever name, rooted in biological origins through maize, but also the term for a layer between the hardware and the operating system of a computer.

Kernel starts with a database of known biological parts. Elements of DNA code. You can then combine those parts into circuits, much like you might for an electronic circuit, and the software will predict how they work together to produce the proteins that will go on to become therapeutics such as antibodies.

“This is, in some ways, the holy grail of computational synthetic biology,” says Nielsen. “To be able to predict a genetic system on a computer.”

Improving drug development now

Asimov provides customers with specialized cell lines that can be customized with these biological parts, as well as access to the software and instructions on how to use it.

Say you’re looking to improve the production of an antibody. Maybe make more of it, or get rid of impurities. You can use Kernel to tweak your genetic circuits, then test the best combinations experimentally.

Asimov is currently focused on two major commercial applications. One uses CRISPR-engineered Chinese hamster cells and accompanying genetic templates to improve the production of proteins such as antibodies. The other is nucleic acid therapies, including messenger RNA, famously pioneered in response to the COVID pandemic.

“In the future we expect to expand into other domains,” says Nielsen. “But right now, we want to execute and be the best in mammalian synthetic biology for therapeutics. It’s the testbed, the beachhead market for this kind of computer-aided synthetic biology approach that we're developing here.”

It’s an exciting prospect. And as the toolkit grows, so do the possibilities.

“Our database currently numbers in the thousands of genetic parts,” says Nielsen. “But one day, we'll number in the billions. We want it to be a truly comprehensive repository of any genetic function you can ever want for any biotech application.”

Thank you to Peter Bickerton for additional research and reporting on this article. I’m the founder of SynBioBeta and an operating partner at DCVC that has invested in Asimov, and some of the companies that I write about are sponsors of the SynBioBeta conference and weekly digest.

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