Remote Control Biology
I’m approached on a weekly basis by PhDs looking to leave academia and enter industry. The first question I ask them is “How much time do you have left before graduating?” What I’m really asking is “How much time do you have left to network the hell out of industry?” There’s a lot of downtime in science, and that downtime is invaluable if your mind is made up that professorship is not for you. Growing bacterial clones? Inoculate the liquid media, place flask in a shaker at 37 degrees, and wait 3–6 hours. Trying to get an understanding of gene expression? Add DNA to master mix, distribute at infinitesimally low volumes in 384-well plates, place in PCR machine, input settings and wait 2–3 hours. Want to visualize protein expression? Grow cells (at least 1 day), fix cells to dish (hours), add antibody to cells and wait overnight. Running gels, growing bacteria, transfecting cells, enzymatic reactions, sequencing, PCR, breeding mice, sectioning, staining and imaging tissue it all takes time. And there’s a lot of waiting. Now for the PhDs that aren’t long for academia, that time can be spent researching their next career move. But there’s another movement that is specifically looking at that downtime, and further to the entire process of biological experimentation and thinking that science research can get a whole lot more efficient — at Lux we call them the biological hackers.
Rinse, repeat, rinse, repeat, rinse, repeat. Science for the most part is repetitive, filled with protocols and standards. Sure, just like cooking where there are some magicians in the kitchen that move beyond the recipes for the masses, there too are the Nobels, the Laskers and the Breakthroughs that creatively and innovatively look at things different, establishing new protocols, procedures and setting new standards. But once established, these once-innovative methods are now within the grasp of researchers globally. And if you do something over and over again it becomes second nature. There were experiments in the lab that I had performed so many times that I could have done them blindfolded. Pipetting, mixing, shaking, inoculating, growing, warming, cutting, measuring, picking, freezing. It’s repetitive. But is it productive? Is it better for mindshare to be spent elsewhere in designing complex experiments, collaborating globally, updating our theses, and trying new things?
Enter the robots
Science has traditionally been the world of ‘do-it-yourself’. Big pharma introduced the research world to outsourcing through contract research organizations (CROs), stretching pre-clinical to clinical experiments. However, CROs are still a labor-intensive manual service. Whereas the industrial revolution brought machines to the likes of mass manufacturing, the CROs still brought people rather than machines. A new wave of innovators are infusing this service world with smart machines. Transcriptic, Synthego and Emerald Cloud Lab all offer services whereby robots are running the experiments. The idea is to take the repetitive and mundane out of the lab and have a machine do it. It’s automating science. In a business sense, they’re trimming the industry’s fat and eating away at CRO margins. In a scientific sense, they are offering repeatable science. Machines don’t get tired, human arms do. And machines can repeat processes to such a high degree of precision that they can reduce the discrepancies and disparities between labs and across time. Combine this with a world where the researcher’s own lab is becoming more intelligent. The internet-of-things is knocking on the lab door. Machines are becoming cheaper, smarter and more mobile. Liquid handling robots, like BioBots and Modular Science, once hundreds of thousands or dollars, can now be bought for the price of a consumer 3D printer. Companies like Zymergen and Gingko Bioworks are taking advantage of this, increasing scale of operations and drastically improving time taken to achieve never-before-seen yields. 3D printers, led by the maker movement, are entering the biology realm and printing tissue structures equivalent to the human body and in forms never seen nor contemplated before. New tools have such speed, efficiency and sensitivity that creating a defined, characterized single cell atlas of every cell in the human body is being contemplated. With technology so refined and so pioneering, you have to sit up and ask “What is actually possible in the next 10 years?!?”
Science and its instruments is getting so precise, so sensitive, so high throughput, and so massive (in terms of data generation) that in reality only machines and robots are capable carrying out (both physically and analytically) the almost infinite permutations and possible combinations. BUT scientists aren’t being replaced. They’re the ones being armed with new equipment and tools — and at a scale never before seen. Researchers will continue to be the conductors, but in the near future their orchestra will be an armada of highly intelligent, precise and connected robotic instruments performing harmoniously in tune — efficiently and in real time. Scientists should be like kids in a candy story with what is on the horizon.
A Virtual Scientific World
Picture a world where Scientist A in America, B in Europe and C in Asia all communicate and collaborate on Research Gate. Research goals are set and experiments designed using electronic lab books like Benchling. Science Exchange is then queried for service providers to perform those experiments. Sequencing and DNA writing is outsourced to core facilities at academia or industry — it’s becoming a commodity service/product, price and time are the only things that matter. Data is stored in the cloud with AWS or Google. Bioinformatics are completed by DNANexus or Google themselves. For repetitive, standard protocols like PCR, clone picking and high-throughput candidate screening, companies like Emerald Cloud Lab and Transcriptic can be utilized. Log in online and order your experiment. The same is true of preclinical animal work. Order your mouse model and send your top drug candidates to Mousera. Researchers can design, run, and analyze experiments and their high volumes of quality data. The platform improves the speed and reproducibility of preclinical research so that it is more predictive of human performance. Simultaneously run experiments on organ-on-a-chip technologies, miniature models of organs mimicking human drug interactions for early insights into drug-host-physiology. Tissue processing can be directly sent to 3Scan. Control the robotic pathology microscope using your iPhone to tailor the work to your needs.
During the entire process, use Authorea to start populating figures and tabulating data to produce a publication ready scientific paper that can immediately be submitted to an online peer reviewed journal. What’s cool is that the underlying data are all there. The figures are live. Independent scientists can look at the generated datasets and delineate their own conclusions. Big Pharma or biotech read the paper and are interested in the molecule and they have the capital to license and develop further, but they need to find the right patients. Facebook, Twitter and Google Ads are used for patient recruitment. Capella Biosciences or Atomwise are employed to ingest clinical, lab, and genomic data to filter down to the right patients. But those patients are spread across the country so virtual trial sites are established with the entire clinical trial being carried out in the comfort of the patients on home.
Now, yes, this is not a completely closed loop today. There are clearly some gaps. But there’s also a framework whereby the majority of scientific research and drug development can be carried out almost entirely virtually. Researchers are used to doing 90% of wet lab work and outsourcing 10%. Technology and innovation is flipping it. And our bet at Lux is that those “gaps” in this process are going to get smaller and smaller as the biological hackers continue to innovate. What may sound even more provocative is that we’re not even convinced that Scientists A, B or C need to have PhDs or scientific degrees. In that sense, we enter a world of citizen and crowd-performed science. That can be incredibly powerful (and potentially dangerous) where a large multiple of today’s existing number of researchers have an entire army of connected life science robots at their disposal to carry out experiments. Almost endless possibilities and suddenly precision medicine are within reach.
(Disclaimer: Lux Capital is an equity investor in Mousera, 3Scan and Capella Biosciences).
