To reach full potential Synthetic biology needs a truly scalable design platforms

From eetimes, the last keynote speech at the Design Automation Conference (DAC) lived up to its billing of “design without borders.” A tribute to the late A. Richard Newton, it focused on the application of manufacturing and design approaches developed for microelectronics to the emerging field of synthetic biology.

Some months before Newton’s death, Rabaey noted, Newton gave a talk in which he declared that the “future is bio design automation (BDA).

[Applying Electronic Design Automation principles to >Synthetic biology]Rabaey quoted a definition of synthetic biology: “The creation of novel biological functions and tools by modifying or integrating well-characterized biological components into higher-order systems using mathematical modeling to direct the construction towards a desired end product.” This, Rabaey said, sounds like “custom design.

What’s needed to make synthetic biology successful, Rabaey said, are the same three elements that made microelectronics successful. These are a scalable, reliable manufacturing process; a scalable design methodology; and a clear understanding of a computational model. “This is not biology, this is not physics, this is hard core engineering,” Rabaey said.

In electronics, photolithography provides a scalable, reliable manufacturing process for designs involving millions of elements. Biology has a long ways to go. What’s needed, Rabaey said, is a way to generate thousands of genes reliably in a very short time period with very few errors. The difference between what’s available and what’s needed is about a trillion to one.

In electronics, there’s a design methodology that involves clear abstractions, standardized interfaces, a constrained design space, and availability of intellectual property (IP). The same requirements exist in biology, Rabaey said; designers need to build models, compress them for analysis, and synthesize into “substrates” such as e.coli bacteria. “The synergy with EDA is huge,” he said.

Computational models allow designers to describe what’s possible and interpret the capabilities of the system that’s being engineered. While synthetic biology can use advanced modeling and model reduction techniques, “the lack of clear computational models worries me,” Rabaey said.

Just as techniques borrowed from microelectronics can be applied to biology, the reverse is also true, Rabaey said. He showed an example of a “biological oscillator” in which a gene generates a protein that is used to switch the oscillator on and off. It uses e.coli bacteria as a substrate. Hooked up to a scope, it shows a typical oscillation pattern, although the period is in the hundreds of minutes.

But there are more practical ways in which approaches borrowed from the biological world can help overcome the challenges of Moore’s Law, Rabaey said. For instance, consider the problem of timing synchronization — and crickets.

Today, he noted, IC designers use a crystal to distribute a clock signal to all the flip-flops on a die. It’s expensive and difficult to implement. What if designers could instead employ a variety of cheap oscillating elements? Nature does that with the sound the crickets make, Rabaey said, resulting in “distributed synchronization using only local communications without precision timing elements.”

Rabaey said that experimental work has shown the same principle can be applied to chip design using simple analog and digital components with minimal power consumption, and it’s been shown to work