One of the ideas I champion is that DNA is a programming language for living things. By stringing DNA bases together in different ways, one gets different organisms. With one sequence, a bacterium is the result. With another, a butterfly. The same can be said about any subcomponent of life, all the way down to individual proteins.
As we get better at “printing” DNA with automated synthesizers, it gets easier to make DNA-based programs, from simple scripts (instructing a bacterium to make a new protein or compound) to whole new operating systems (genomes). And it‘s just gotten easier, faster and cheaper — a biological version of Moore‘s Law. With DNA synthesis, metabolism can be shaped by anyone who can master various DNA design tools. It‘s the start of a whole new era in biology: digital biology.
I started focusing on DNA synthesis about ten years ago. At the time, I worked for a large biopharmaceutical company. As with any language, mastering DNA means one must learn to read, comprehend, and write. We had a fantastic bioinformatics team. We bought a subscription to Celera, the company Craig Venter created to sequence the human genome. With reading and comprehension well taken care of, it made sense to start thinking about how to write DNA code better.
Celera was possible because people had spent decades improving DNA sequencing technology. Still, the state of the art of DNA synthesis was poor, with low throughput and high cost (on the order of $10 per base pair). Making even a small protein (roughly 1000 bases) was expensive, and only justifiable for things like small, high-value proteins such as a growth hormone. But I believed that as synthesis costs fell over time, less lucrative applications or experimental designs that had a higher probability of failure would fall within reach. Moreover, the work would become increasingly computer-based, rather than being done in the laboratory. Genetic engineering would come to resemble software engineering, except the programming would be biochemical.
In 2003, I took a year off to digest past experiences and to consider where life science may be going in the near future. In the meantime, digital biology got a name: synthetic biology. A small group at MIT was leading the way with DNA modules they called BioBricks that could be snapped together like Lego blocks and then easily reconfigured. The next year, they developed a student training program with BioBricks and challenged student teams to be creative in designing and making applications. Almost overnight, the genetic engineering capability once available only to the experienced and well-financed became available to relative novices for a fraction of the price.
Around this time, I found myself thinking a lot about open source versus proprietary software. The success of open source software, like Linux and Apache server, had demonstrated that community-based development could rival the work done in dedicated companies. Was open source biology possible? I believed strongly that synthetic biology, done openly, could eventually compete with the for-profit biotechnology industry. I could see a day where almost anyone with a laptop could start to create software for cells. What would people make? The projects developed by students with BioBricks suggested a broad range, from fun (bacteria programmed to smell like bananas or wintergreen) to commercially useful (next generation biofuels like butanol).
We get better at "printing" DNA has gotten easier, faster and cheaper – a biological version of Moore’s Law.
By 2005, several synthetic biology companies had appeared. They‘d attracted large investments from top-tier venture groups. The field was hot. I began to think seriously about creating a Linux-style company to make drugs. How would the company be financed? How would people work together? What would they make?
Eventually, I came to believe that drug development needed a complete reboot. In the wake of the Human Genome Project and increasing lab automation, life science data was exploding. Genomics had spawned proteomics and metabolomics, and even more “omics” were appearing on the horizon. Research was growing exponentially, but development,was still stuck on a linear path from discovery to the clinic that could take a decade and a billion dollars or more. The gulf between biological R&D, always wide compared to more traditional fields of engineering, was growing even wider.
I threw away the old model for making drugs and started from scratch. Synthetic biology allowed almost anything biological — from a single protein to an entire organism — to be developed using a tool that was costing less each day. The cost of DNA-based diagnostic tests were falling quickly, too. So what was keeping the cost of making drugs so high? I identified three factors. One was overhead: the physical infrastructure of labs and staff. The second was the cost of manufacturing: facilities to make large quantities of a new drug were often custom-designed and could cost hundreds of millions of dollars. The third was the cost of clinical trials, necessary to prove to regulators that a drug was effective and safe.
Then it hit me. What if, using synthetic biology, we made drugs for just one person at a time? Fully individualized (n=1) medicines? Done open source and virtually, the overheads would be very low. Large manufacturing plants wouldn‘t be necessary. Best of all, the cost and complexity of clinical trials would be reduced, potentially saving years of time and massive amounts of money. Suddenly, the idea of open source drug development didn‘t seem farfetched.
Cancer was the perfect target to test this idea. Because cancer results from the corruption of a person‘s DNA, and no two people have the same DNA, each cancer is unique. A customized drug would be the ideal drug, but wasn‘t economically viable — at least until synthetic biology. I needed a therapeutic agent that was flexible and could be programmed. That‘s when I learned about oncolytic viruses — benign viruses that can infect cancer cells and kill them without affecting normal, healthy cells.
In September 2007, I gave a short talk at Aubrey De Grey‘s SENS conference in Cambridge outlining my intention to found an open source biotech company that would make customized therapies for breast cancer. The response to the presentation was predictable: many had concerns whether regulators would allow such a drug to be used in a human trial. I had no idea, but I knew the only way to truly find out would be to try. It took almost two years of discussion and feeling my way around, but this company now exists. It‘s called the Pink Army Cooperative.
The technology behind Pink Army is off-the-shelf computing and synthetic biology. What makes Pink Army unique is the way the technology is assembled and its cooperative business structure. The company sketches out a path to drug development — a process where each of the major steps has Moore‘s law dynamics. With experience, the performance should increase while the price falls. Meanwhile, the cooperative architecture puts it in a class of its own compared to other drug companies.
Cooperatives are community-owned and operated enterprises that exist to serve their memberships. They are corporations that operate as non-profits and can have broad membership, because people don‘t need to be qualified investors to get a share. They can raise substantial sums by attracting a large membership — an army — something that is fairly easy to do these days because of social networking sites like Facebook. Members of the cooperative are united by their common interest, in Pink Army‘s case, better, faster, and less expensive treatments for breast cancer.
Breast cancer is the first target, but ultimately the cooperative‘s goal is to open a path from diagnostics to the clinic for individualized medicines — to make effective cancer treatments as fast as diagnostic data can be translated into designs, manufactured, tested in the lab, and approved for use on a single person. Using open source synthetic biology, each of these steps can be automated, and each should get cheaper over time. If it works, drug development could become a real technology.
Pink Army, then, is the first DIY drug company. It‘s a container that allows people interested in tackling cancer to connect and focus their passion, skills, and other resources. It takes cancer — a field that has mushroomed to become a vastly complex global R&D enterprise — and reduces it to an easy-to-understand, manageable task: finding better ways to analyze and treat just one person; ways that can connect experts and resources no matter where they are in the world, ways that are safe, and ways that can scale and become more affordable as they do.
My role in the company is to share stories and make connections, something that, as a generalist, I absolutely love to do. More people are connecting every day, and the company intelligence is growing. For Pink Army to work, it needs to resonate with many people, for many different reasons. It must somehow convey the message that although cancers can arise in countless ways, the goal for treatment is almost always the same: selectively shut down or kill the broken cells.
Why am I passionate about DIYbio and open biology? Mostly it‘s because I think that collectively we can do better than we have. The transistor and the structure of DNA were discovered within six years of each other. Recombinant DNA technology and the microcomputer both appeared in the early 1970‘s. Both became big industries, but with very different dynamics. Computers are ubiquitous, while biotechnologies remain a mystery to most people, with few applications that demonstrate the utility and potential of the field to make the world a better place.
The biotech industry has struggled economically and is reaching a point where even the largest companies are resorting to merger and consolidation for growth. It‘s clear that something needs to change. Open biology is that change. I believe that open biology will continue to make bioengineering more accessible. It will produce new products that people want, can afford, and trust, at a much faster pace. A more open foundation for drug development could lay a strong foundation for a thriving bioeconomy that could one day be larger than the computing industry. After all, life is the most valuable commodity of all.
Andrew Hessel champions open source synthetic biology, enabling researchers and entrepreneurs to better address major challenges, including renewable energy, environmental remediation, and curing human disease.
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