Biology as the next hardware

Ive spent the last couple of years arguing that the barriers between software and the physical world are falling. The barriers between software and the living world are next.

At our Solid Conference last May, Carl Bass, Autodesks CEO, described the coming of generativedesign. Massive computing power, along with frictionless translation between digital and physical through devices like 3D scanners and CNC machines, will radically change the way we design the world around us. Instead of prototyping five versions of a chair through trial and error, you can use a computer to prototype and test a billion versions in a few hours, then fabricate it immediately. That scenario isnt far off, Bass suggested, and it arises from a fluid relationship between real and virtual.

Biology is headed down the same path: with tools on both the input and output sides getting easier to use, materials getting easier to make, and plenty of computation in the middle, itll become the next way to translate between physical and digital. (Excitement has built to the degree that Solid co-chair Joi Ito suggested we change the name of our conference to Solid and Squishy.)

I spoke with Andrew Hessel, a distinguished research scientistin Autodesks Bio/Nano/Programmable Matter Group, about the promise of synthetic biology (and why Autodesk is interested in it). Hessel says the next generation of synthetic biology will be brought about by a blend of physical and virtual systems that make experimental iteration faster and processes more reliable.

On the input and output sides of experimentation the physical portions hardware is rapidly evolving. DNA sequencers have brought the cost of reading DNA into software down by more than three orders of magnitude since 2007 (vastly outpacing even Gordon Moores curve for computing power). The cost of writing DNA has also fallen dramatically, from about $4 per base pair in 2004 to between 5 and 10 cents per base pair today, says Hessel. Robotic laboratory systems from start-ups like Transcriptic and Emerald Cloud Lab make repetition and exploration easy, inexpensive, and reproducible.

In the middle, between DNA read-in and DNA read-out, is a computing layer thats seen enormous growth in the availability of useful data. Databases like KEGG, for metabolic pathways, and Genbank, for genetic sequences, codify biological processes in machine terms. Software can instantaneously run through millions of permutations before suggesting a physical experiment. Thats the biological counterpart to Carl Basss algorithmic chair.

What were seeing is the birth of a new programming industry.

For decades, one of the exciting frontiers of biology has been the possibility of running experiments in silico as opposed to in vitro simulating complex reactions and pathways with software and avoiding the expense and time needed to actually carry them out in a wet lab. Hessel says that movement is circling back toward physical implementation again: In synthetic biology, its not just in silico anymore; you can print DNA so easily, put it into a living cell or cell system, run those experiments, and do living biology, too, alongside the computation, he says. That sounds familiar to me from the new hardware movement, where electronics like the Arduino and Raspberry Pi have convinced a generation of programmers that they dont need to stay locked behind their screens.

Its easy to compare things to software, and the effect of doing so is always dramatic. Software is, after all, a pure, formal expression of human logic, and it has changed nearly everything in the modern world. Im naturally a little skeptical of comparisons, then, but Hessels is very compelling:

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Biology as the next hardware