Molecular Farming | Future of Food | Follow to Explore the SciFi Present of Bioengineering
Can your technology learn fast enough to launch? 🔬🧬🚀 I started my scientific career building incremental improvements to rather well-established theories and technologies. In an incremental environment, technical progress is more or less predictable. Spend more time running experiments and you’ll compound your growing understanding of (and ability to control) the natural world. 🔭 Push far enough out into the frontier of the unknown, however, and these incremental approaches begin to fail. Getting technologies to work out past the border of reliable theory comes down to two factors in my experience: the compactness of your design-build-test loop and your talents as a gambler (more on that in a future post…) This is because, at a fundamental level, the rate of development of any technology is tied directly to how long it takes to “learn a new thing.” ☢️ ☀️ It’s striking to me how few people would have predicted that the future of energy would be driven more by wind and solar than by nuclear power, which was already working at commercial scale more than 50 years ago. This is partly due to the fact that each turn of the DBT loop in nuclear power (designing, building and learning from a new power plant) costs $5-10B over more than a decade (links in comments). The ability to quickly and inexpensively build, test and learn from new wind and solar designs has been fundamental to their massively expanded footprint. 🌲 I think about this all the time as a plant genetic engineer because plants are nothing if not SLOW. Despite the incredible potential plants have as biofactory platforms, building and testing (aka transforming and phenotyping) a new bioengineered design in (even fast-growing, annual) plants takes an entire year - an ENTIRE YEAR to learn if your new combination of alleles, your novel gene or your optimized promoters improved performance over your last design. 👎 This is completely unworkable when you’re operating well beyond the bounds of comfortable theory - or when accelerating down a very short startup runway. 🔄 At this point in my career, I wouldn’t embark on any ambitious, groundbreaking new technology development project without first establishing a clear plan of how to turn an effective design-build-test loop in days or weeks rather than months or years. 📉 This is particularly critical within the environment of a startup - which are all in the process of going out of business every single day until that last day that they finally do close their bank account - or exit. 🛫 Make sure your tech development strategy can learn fast enough to lift you off in time! (and yes, there are some tricks to doing this even in plants… 🌿) #syntheticbiology #future #bioengineering #molecularfarming #startup
Mark Jackson
3w
If you are a start up for sure you need to learn fast or as they say fail fast. If you are lucky enough to have a patient investor with deeper pockets you might get a longer runway 🙏😞If I had a start up I would like to have a balanced portfolio of projects with differing risk versus reward. And proxy test systems (eg protoplasts, transients, in vitro testing) should always be used to identify best bets. Hooray for PMF .. I hope we get some more winners soon.
Molecular Farming | Future of Food | Follow to Explore the SciFi Present of Bioengineering
3whttps://www.inet.ox.ac.uk/publications/no-2021-01-empirically-grounded-technology-forecasts-and-the-energy-transition