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As it stands now, the twenty-tens will be remembered for the rise of mobile, and the emergence of Artificial Intelligence as a major actor on the technology stage. However, there are two years worth of chapters left to write.
I believe that 2018 will be the year commercialized science arrives in force. In 2010, humanity first birthed using genomic sequencing. Since then, technological forces in this decade have been slowly greasing the wheels of innovation so that science can make its mainstream debut. Now, the stage is set for scientific breakthroughs to reach the market faster, and with more force, than ever before.The Master Tool
In addition to taking center stage as a technology in its own right, AI is playing an important role in science. When AI first earned our attention, many thought of it as its own technology vertical. Venture firms invested in AI. Pundits estimated disruption costs. Companies planned for AI budgets. And while it’s clear that interest and investment in AI is still on the rise (for context, investments into AI technology is expected to grow from $640 million in 2016 to $37 billion by 2025), an important shift is happening. AI is no longer viewed as a siloed technology. Smart VCs no longer invest in generalized AI, but now focus on applied AI for specific solutions. The verticals that AI now permeates are leaving their analog competitors in the dust. Now, the horizontal integration of AI into science platforms is driving breakthroughs and commercialization at unprecedented scale.Drug discovery is a strong case study. What if we could get a drug to market in one year instead of ten? Imagine the effect that would have on big pharma and biotech, a trillion dollar industry, along with the lives of the millions of people they treat, including our loved ones. With AI, we can automate, scale, and innovate the scientific processes that go into drug development, which results in increased speed to breakthrough, and in turn, speed to market. Emerging science companies are already leveraging AI. TwoXAR is leveraging its computational platform to identity promising drug candidates, mitigating some of the risk through preclinical studies. Another, , is able to leverage machine learning for metabolic engineering. Applying computational biology and synthetic chemistry, Arzeda has expanded computational de novo design beyond single enzymes. The application of AI and ML brings us one step closer to applying this process to drug development. AI enables us to reverse-engineer proteins to design drugs and predict side effects, to determine market demand, and anticipate outcomes and treatments — all of which accelerate the time to commercialization by an order of magnitude. The potential is limitless, as these companies, and countless others, leverage AI to underwrite scientific breakthroughs across industries.
Commercialization Platforms & Pipelines
The cost to edit DNA was once hundreds of thousands of dollars. Today, a grad student in a basement with a couple thousand dollars can author a new species. But could she introduce that species to the world? Almost.Companies and researchers are no longer happy with simply making a breakthrough; they also want to get it to market as fast as possible. The new pace of innovation is driving companies to think two steps ahead and design purpose built pipelines to get discoveries into customers’ hands more rapidly. In this new packaging, science-driven platforms are modern-day assembly lines, connecting workflows from lab to lab and rigging them with analytics along the way. It’s customer friendly, and designed to disrupt. Fast. A great example is of this is . NuMat can research, design and develop a new material aimed at solving a specific problem such as storing gases more efficiently. NuMat then follows its production all the way through its customer’s implementation pipeline — a truly end-to-end journey from idea to impact. , a food testing company, is taking next-generation sequencing and commercializing it for the food safety industry. Built on their proprietary platform, they have developed a distribution model in which this kind of testing can be used for multiple use-cases, from GMO testing to authenticity verification. has taken the mammalian olfactory system (the system that makes you taste) and put it on a chip, opening the door for a new scale of testing in fragrance, food, defense, and countless other industries. Another company, is cutting out the process of animal and human testing and replacing it with technology at the chip level. Their “Organs-on-Chips” technology emulates human biology, helping researchers understand how different diseases, medicines, chemicals and foods affect human health. This kind of testing platform is the perfect example of how science has shifted from single use cases to cross industry scale, simply by building a platform structure and an ecosystem around the breakthrough.
Just as AI is powering breakthroughs at scale, the building of these fully integrated commercialization platforms and pipelines will help science transform industries in ways we can’t fathom.
Consumer Focused
Until recently, one could argue that scientific discovery has been locked in the ivory towers of academic research and commercial labs. Tech Transfer programs at universities and incubators have now started to bring breakthroughs to market. However, science is facing an even more radical shift. Catalyzed by AI and powered by commercialization platforms and pipelines, we are now enabling the consumerist movement in science.Examples of consumer-first science are already reaching the market. Driven by the dramatic cost reductions in sequencing, genomics companies have reached the hands of consumers in spades. , , — all of these companies have democratized complex lab testing by driving down user costs, providing a user-friendly interface, and making it directly available to the consumer without seeing your doctor. , too, are on the shelves. For each of these products, not only are the costs accessible to the masses, they are designed to be used at home. These breakthroughs all took this use case into consideration when they were being developed. The food industry is also ripe for disruption based on this new model. Companies like , , and are redefining how we develop foods for consumers, outside of traditional agriculture and processed products. Often categorized as meat replacements, these brands have spent years in research labs understanding the building blocks — down to the molecular level — of our food, and how we can recreate it with FDA approved ingredients that are better for humans and better for the environment. While we have science to thank for these new kinds of foods, each of these companies had to take into consideration the regulatory landscape, consumer demand, and the structure of the food industry in order to have their breakthrough reach the market. The foods you eat tomorrow will be a direct result of consumer first thinking today.
The Resurgence of Science
2018 is here, and with it a new pace of scientific innovation, a new production platform, and a new mentality that puts us, the common consumer, at the center of the design process. While we only have two years left to leave our mark on this decade, that’s more than enough time to roll out the next lifesaving drug, your next ethically developed hamburger, or the next device to understand and track your own biology. This year will be remembered as the resurgence of science and the dawn of a new age of innovation.