The struggle of Deep Science Startups.

[After years of sharing my poems and experiences in spirituality on this blog, I am now bringing all my other writings here so as to consolidate them all in one place.]

The MIT Technology Review carries a typical story about how innovators in deep science are finding it difficult to translate their R&D into viable businesses due to the lack of understanding, patience, and support from the wider finance ecosystem. Written by Illan Gur, Founding Director of Cyclotron Road, a VC firm that invests in hard science, this short article captures the core of the issue in Deep Science Investments.

Illan writes:

An innovator I know—let’s call him Tom—had trained for a decade at some of the world’s top research institutions to become an expert in materials science and engineering. He’d developed a new manufacturing technique for semiconductors with the potential to enable next-generation power conversion devices for lighting, EVs, renewable power, and defense applications. After demonstrating promising results and gathering enthusiastic feedback from industry experts, he was ready to take his technology to market. But how?

….Today’s research ecosystem isn’t built to support innovators like Tom. Their projects are too applied for academic labs, which focus narrowly on new scientific discoveries. Meanwhile, private industry can’t justify investment in expensive research that doesn’t yet have clear commercial potential. Faced with this chasm, even the best innovators struggle. Many are bound to say “why bother?” Can we blame them?

So how do we keep the Toms of this world in the game? For starters, we need to do a better job catalyzing the creation of science-based startups and supporting cutting-edge research within them. Free from the institutional pressures of academic publication or corporate quarterly earnings, startups can serve as powerful vehicles to bring hard technologies to market. Such firms often spend years performing research to develop a first product. Yet despite driving some of the biggest technology disruptions in recent history, small businesses receive only a small percentage of all government research funding.

These aren’t just anecdotal stories. Closer home too, we do see – innovators, researchers, engineers and scientists in area’s other than software – struggling to make viable business from their research. As Illan writes, had they been software engineers, it would be a different story altogether:

If Tom were a software innovator, he could build a prototype and validate his product in months with little more than a laptop. But to innovate in semiconductor technology, he would need the tools of cutting-edge research—fume hoods, spectrometers, electron microscopes. He would also need time. Turning a semiconductor breakthrough into a market-ready product can take years.

We all know the amount of money that has been pushed by Angel Investors, VC’s and Fund’s into the startup ecosystem in India – most, if not all, going towards software startups, making it hard for those who are trying to build businesses in Deep Science. BTW, the GoI has several ongoing schemes trying to help startups across industries and technology area. Here is a quick list of 50+ such schemes.

Columbia Business  Press recently published a book titled “Venture Investing in Science” by Douglas Jamison and Stephen Waite. Douglas is the CEO of 180degreecapital, which invests and builds transformative companies from disruptive sciences with a focus on what they call Biology+. With over decades of experience in venture investing in deep science companies in the US, Douglas had, had a front side view of the issues related to the deep science investments and he brings that out in a very vivid manner – the book starts off with a historical context related to advancements in deep science and technological changes and their profound impact on economic development as well as the Evolution of Venture Capital in the US. The authors brilliantly trace the beginning of deep science from the publication of Newton’s scientific treatise in 1687 titled Principea and trace all the advancements in sciences and link them to the corresponding shifts in economic models and the consequent increase in living standards in the Country. The first three chapters are a brilliant read for those who are interested in getting a refresher in sciences as well as those wishing to understand the emergence of the VC market in the US.

The key theme of the book is the diversity breakdown in Venture Capital and how the shifts in US Capital Markets have worked to impede VC investments in deep science that have had a consequent dampening on the American economic system that is essential to foster higher living standard over time. The author’s build a strong case by telling the story of Digital Equipment Corporation (DEC) – a company built on deep science innovation and how the VC investment returned a massive 500 times return to the investors.

DEC was founded in 1957 was born from funding  provided by Dept of Defense to the Lincoln Labaratory at the MIT. The lab was established to build new computer technology for the cold war. DEC blossomed ‘cause of the adoption of another great deep science advance in the 1950’ – the transistor – developed by three engineers at Bell Labs. The first American VC firm ARD invested $70,000 into DEC and took control of a 70% stake in the company. In 1996, DEC went public raising $8 million, making ARD’s investment 500 times more valuable at IPO price. Deep Science was translated into technology, into innovation and into great wealth.

The heart of the book is about “diversity breakdown in venture investing”. A Diversity breakdown when it happens ultimately leads to the collapse of systems (eg., The DotCom bubble of 2000 and the stock market crash). The premise being with more venture capital being diverted to software investments, there is relatively less money flowing towards investing in deep science companies, specifically deep science companies outside of biotech/health devices, this could ultimately result in a collapse of VC system. In addition, the authors make a brilliant point: While Govt continues to spend on Deep Science R&D, the research and inventions will be wasted if there isn’t any innovation capital left to take these research to commercialization. This, in turn, will have a cascading effect where the payoff from R&D and research will be less, consequently impacting govt funding to R&D as well. Brilliantly detailing the changing landscape in investments and why investors prefer investing in software rather than deep sciences; how the shifts in the US capital markets have contributed towards impeding venture investments in deep science, the authors back their claim by extensive economic data points, with the key underlying message being that “Software is eating the world”. The authors go on to make a case for emerging deep science venture opportunities in areas such as Quantum Computers, Hydrogen Fuel Cells, Nanomaterial enabled water filtration and desalination; Nano-enabled therapeutics, Precision health etc. that could provide growth and prosperity if we find a way back to bring diversity back to venture capital investing.

The authors conclude with a rational optimism and hope that there will be a change in this trend and that investments will come back to deep science ventures in the future. They point out that while most Silicon Valley VC’s continue to shun deep science ventures in favor of software investments, established companies like Google, FB etc have stepped up investing in Deep Science as well as some newer funds have started raising money for early stage investing in deep science companies. In addition, they believe that the success of Elon Musk’ venture may also result in the beginning of a new trend that may lure VC’s back to deep science investments.

If you are an investor or an entrepreneur or even someone who is remotely interested in current scientific and economic trends, this book is a brilliant read. I only wish I had a hard copy rather than the ebook on Kindle to read. Some of the economic charts are practically unreadable on the ebook.

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