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The DNA of A Science Startup: Betting on the Right Horse

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The DNA of A Science Startup: Betting on the Right Horse

There is no doubt we are living through atypical times. A confluence of factors have introduced, in an unprecedented way, the one thing that businesses and investors abhor: uncertainty. Now more than ever, the investor community needs to evaluate, which startups and newly launched businesses are likely to weather the storm, particularly businesses commercializing a science-based idea.

We’ve identified three kinds of science-based startups that are likely to weather the storm, and three that may succumb, beginning with three that will succeed:

1. Startups that add value (beware of “complete reinvention”): Many startups, given their energy and momentum, may seek to “completely reinvent” the ecosystem. These startups underestimate the inertia of not only consumers but also established players, supply chains and practices within the industry. One good example is the diagnostics sector; a startup that aims to improve efficiency for large players (E.g. such as Quest Diagnostics) by offering, say, a new kit that greatly reduces testing expenses, is more likely to thrive, even if it does not have unicorn potential. Conversely, a startup that offers new technology that will require a large player to completely replace or revamp an existing pipeline will not be easily adopted.

2. Startups in evergreen sectors within biotech/pharma: Science-based startups are almost immediately equated with biotech. This is understandable, as the biotech sector attracts the most attention and most capital. While all of medicine is always up for improvement, within biotech/pharma, certain disease areas such as Oncology and Neurobiology remain evergreen. This is not to say that a strategy similar to Gilead’s in developing some antivirals (best-in-class) will not succeed, it is just that such strategies need to be executed very carefully. In contrast, the drastic unmet need in some sectors means a less than perfect drug stands a good chance of gaining market share. In fact, over the next 10-15 years, Neurobiology appears poised to experience leaps similar to Oncology when biologics took the stage by storm. As the population ages, neurodegenerative diseases are likely to increase, creating potential for a large market. The same demographic trend also hints at one as yet untapped area, that of aging biology. Although there are big players, for instance, Calico, the path forward remains unclear given the complicated science.

3.  Startups that address fundamental needs: Startups that address fundamental needs and deficiencies in any sector are most likely to survive and thrive. This is not by any means a new thought or message, but one that needs to be highlighted and should remain a guiding principle. While they may not be apparent, deficiencies exist in all sectors, be they automation, manufacturing, or even something as distinct as textiles and apparel. One straightforward example here is biotech/pharma: economic downturn or not, new medicines are always needed. Another example is food-tech, nobody is going to stop eating; in fact, disruption of supply chains is expected to create new opportunities. It is not surprising that a number of startups are developing plant-based substitutes for animal products, and demand for these is expected to remain strong. From a high-level perspective, startups emerging from materials science, nanotechnology, and of course computer science, especially AI, are particularly attractive, as they appear poised to provide solutions to long-standing environmental problems. On the other hand, areas such as biofuels, which attracted considerable attention a decade ago, no longer appear viable given the shift toward electric and hybrid vehicles.

Conversely, there are three types of ventures that may not weather the storm:

1. Startups that pivot without having a core strategy: A pivot by itself is not bad, and many businesses do indeed change directions to take advantage of an opportunity or rebuild their revenue streams. But there is an important distinction: businesses that lack a core strategy will rarely survive even with a pivot, especially in a fickle investment environment. Many companies and even well-funded startups may venture into new areas such as infectious diseases, but this does not change their original business model. A COVID-specific solution will melt away the minute a good drug/vaccine is announced. The diagnostics sector here provides good case studies. A newly developed scientific method or protocol may be able to detect the SARS-Cov2 virus within minutes or seconds, which is a great achievement, but will this solution supplant existing medical pipelines and setups? If a startup’s pivot is purely opportunistic, rather than being part of a larger strategy, it may indicate inability to survive over the long term.

2. Startups that address trends: This overlaps with the previous point, but it is important in its own right. Ideas are dime-a-dozen, and many startups are born during times of distress and social upheaval when deficiencies in our societies and industry come to fore. It is important to distinguish if the startup is addressing a need-of-the-hour or a trend that has the potential to stick.  With regard to science-based startups, there is less of a trend following, although it is quite common for startups to mushroom every time new technology is developed. One example of this is AI, which represents a trend that is cyclically in vogue. Established computer scientists can attest to multiple periods when AI was supposed to solve all of the world’s problems, only for scientists and entrepreneurs to realize that the real world was too complex and you could never really leave decision making to machines for many crucial tasks.

3. Startups that fall prey to shifting regulation and circumstance. This is unfortunately beyond a startup team’s control, but investors should be careful when funding startups in such sectors. Two interesting examples here are businesses that provided services to the oil and natural gas industry, and the development of biotechs around CRISPR-Cas9 genome editing technology. In case of oil, it would have been very difficult to predict that petrochemicals and related sectors would plunge overnight, wiping billions of dollars’ worth of value from some of the biggest companies in the world. A strange confluence of geopolitical contests, coupled with uncertainty due to a pandemic and shifting consumer habits, probably a once-in-a-lifetime event, may spell doom for many players. Any startups connected to this sector may likely suffer significantly in the coming months, and their long-term survival is uncertain. In the case of CRISPR, the potential for rogue actors to misuse the technology means that many governments in the world will proceed extremely cautiously, and indeed, initial miss-steps may lead to stringent regulation. While there is plenty of potential, CRISPR-based startups should be evaluated carefully.

This brings us to the big question: where are the real returns? Can we break out of COVID play? Real returns are where startups and ideas address fundamental questions and needs that are apparent but overlooked. Overall, even though investor interest these turbulent times still appears to be strong, with many new startups being funded, the next few quarters will be the ones to watch, as the downturn reduces both investor appetite and revenue. Investors must continue to be discerning with their dollars, especially when it comes to science-based startups.

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Dr. Shailesh Date is the founder and CEO of LRC Systems, which uniquely combines advances in natural and quantitative sciences with cutting-edge technology to help solve fundamental health, economic and social problems for public and private organizations. LRC serves as an ideas hub for high-level transdisciplinary research that is bigger, faster and more impactful, to propel innovations that can change the world.  Dr. Date obtained his Ph.D. in Molecular Biology (computational focus) and completed his postdoctoral research at the University of Pennsylvania’s School of Medicine, focusing on apicomplexan parasites, including Plasmodium falciparum, the causal agent of malaria. His current research covers topics in both public health and complexity science). He also serves as Associate Adjunct Professor in the Dept. of Epidemiology & Biostatistics at UCSF and Adjunct Professor of Biology at SF State.