Computers—once upon a time—took up entire rooms. Many people were needed to run them, and the efficiencies they created were useful only to very large, centralized organizations such as universities, militaries, and governments. Advancements in the technology were slow, as were the productivity increases.
Then the personal computer emerged. Technology improvements accelerated, and so did productivity gains. Apple computers and Windows-based personal computers put incredible computing power into the hands of anyone who had a few thousand dollars to spend. The idea of the Silicon Valley garage startup was reborn as personal computers and peripherals such as desktop printers and scanners enabled new, nimble entrepreneurial businesses.
This early era of democratized computing generated scores of new startups, including such transformative companies as PayPal, eBay, Amazon, and Google—companies that grew to be some of the most successful and influential companies in history; companies that reshaped the way we conduct transactions, purchase goods, and share information; companies that have ultimately reshaped our lives and our world.
Enabling democratized biology
Like technology, biology is full of exciting, transformative ideas—and it’s not too hard to argue that these transformative ideas could be at least as impactful. They could lead to the development of on-demand vaccines; the production of meat from animal cells without the need to raise and slaughter animals; the programming of algae to make bio-based oils for energy or for sustainable, high-performance clothing and gear; and the conversion of emissions or electronic waste into sustainable fuel.
However, biological innovations are much more complicated than working with silicon, requiring more testing and safety precautions. There is a logistical challenge with which biology must contend before it can become a more nimble, high-growth industry.
Biological R&D still relies on infrastructure that is much more like those room-sized computers than the democratized desktop computing that PCs offer. And much more of it happens in large, centralized institutions or within vast, well-funded pharmaceutical companies.
These types of organizations have been able to take advantage of some of the promising turning points that we’ve seen recently in biology—such as the introduction of instruments that dramatically reduce sequencing costs and run times, or of CRISPR-Cas9 tools that greatly simplify gene editing. But like IBM during the rise of personal computing, pharmaceutical companies and other large, entrenched organizations are not necessarily nimble enough to seize on high-risk, high-reward innovations.
Even scientific companies that are more entrepreneurially driven depend on centralized, often mail-order suppliers rather than more flexible suppliers, or even in-house resources, to design and generate new constructs. Relying on centralized service providers can result in significant bottlenecks and impede a startup’s ability to iterate quickly—a key attribute in an innovative, entrepreneurial environment.
Adapting the iterative Design–Build–Test–Learn cycle
Biology’s version of the desktop computing revolution is currently unfolding now that many innovative companies are emerging and introducing cutting-edge tools. Considering the breadth and complexity of biology, we may not be able to look back at any single tool and say that it was the game changer that sparked a wave of innovation. However, each of these tools can vastly improve the ability of entrepreneurial biologists to conduct research and iterate experiments.
What is emerging is a broad suite of tools that will ultimately enable not only the understanding but also the reprogramming of biological systems at the molecular level. Through this transformation, biology is becoming an engineering discipline, one where scientists can achieve innovation through uninterrupted Design–Build–Test–Learn (DBTL) cycles.
Next-generation sequencers have already begun to deliver laboratory-scale performance within benchtop-sized (and priced) instruments. This development has facilitated the ability to read life’s source code quickly and affordably, even at a smaller laboratory or within a clinical setting at the point of care. The next wave of innovation will bring tools that enable the writing or programming of that source code—RNA and DNA—and tools to build or engineer the materials that the source code encodes—synthetic oligonucleotides, genes, and proteins.
For example, Inscripta is developing a platform that could democratize genome-scale editing for individual cells, enabling the editing of hundreds of cells at once, turning genes on and off en masse. Berkeley Lights’ technology can isolate single cells and measure their behavior under different conditions. These technologies make laboratory discovery more programmable, speeding up discovery time immensely and allowing biological entrepreneurs to do more with less space and fewer people.
DNA Script’s SYNTAX™ system brings an even more fundamental biological design function to the bench: DNA synthesis. The SYNTAX printer will enable researchers to synthesize DNA on-demand on a benchtop-sized instrument, allowing them to iterate continuously without lag time.
If you combine these technologies and instruments, it becomes possible for a single laboratory to go through cellular DBTL cycles in a highly controlled environment and in a fully automated manner. Before the introduction of these nascent technologies, one would need an institutional laboratory and teams of scientists to conduct the same level of work. Although you might not be able to synthesize DNA in your garage yet, just a few years will pass before life sciences startups find it practical to program biology using integrated, fully automated life sciences laboratories.
Innovation in programmable biology will truly occur when entrepreneurially oriented academic laboratories and small, nimble companies—or even “garage” scientists—can afford to fail often on the way to breakthrough discoveries. Right now, these companies are weighed down by the need to purchase basic tools from centralized distributors or the need to fill laboratories with expensive equipment and teams of postdoctoral researchers to run experiments. All this added time and expense can prevent a startup with a short runway from taking flight. But biology is being democratized through the introduction of distributed, affordable, and easy-to-use tools. Ultimately, these tools will bring bioengineering to new heights.
Thomas Ybert, PhD, is co-founder and CEO of DNA Script.