Sci-Fi to Reality- The World of Deep-Science Tech

“The people who are crazy enough to think they can change the world, are the ones who do!” — Rob Siltanen

Over the 4.6-billion-year history of the earth, it has undergone many changes. While much of the early changes can be attributed to natural evolution, the last 300 odd years have seen changes like no other — driven by industrialization.

Beginning with the first industrial revolution in the 18th century, humans have set out to push their limits through innovation. From the discovery of the steam engine to the shift towards oil & gas for mass production to the post-war revolution in information communications technologies, humankind has indeed come a long way. While the effects of human evolution on the planet have been debatable, there is no doubt that humans have used their ingenuity to mold the planet.

In the 21st century, we are experiencing what we now call the fourth industrial revolution. This wave is being driven by deep-science technology.

What is Deep-Science Tech?

When Peter Parker got bit by a genetically modified spider and attained superpowers, a scientist somewhere in a small rustic lab must have burst out laughing. First, because of the way that DNA recombinant technology is interpreted and second because they wouldn’t have imagined that it could be used to save the world. Fast forward to 2022 and spiderman isn’t special anymore. Gene recombination is a familiar face. It’s applied across the healthcare value chain in areas including diagnostics, relation identification and treatment itself. This is merely a sample from the sea of deep-science technologies surfacing upon years of scientific and engineering breakthrough research.

Deep-science technologies such as genomics, biotechnology, advanced materials, and AI are disrupting life as we know it. These technologies are completely transforming legacy systems. In fact, Deep-science tech innovators are working on solutions to some of the world’s most pressing problems.

Deep-science tech companies are true mavericks. They work at the intersection of science and technology to create innovative products. They use intellectual property to leapfrog their incumbents thereby unleashing potential for exponential growth. This sets them apart from those working merely on incremental value adds. Deep-science tech companies permeate across sectors from healthcare to manufacturing to telecoms. For example, some are developing synthetic biology and gene editing technologies for advanced seed varieties, diagnostic tests for life threatening diseases and alternative food products. Others are using advanced materials to develop batteries, photovoltaic films and biodegradable plastics. Keeping up with the tradition, the deep-science tech wave has been driven by startups, while large corporates are still playing the waiting game. While large pharmaceutical industries are still focusing on traditional methods of drug production, startups in the biotech space are utilizing advanced technologies such as synthetic biology and AI to significantly shorten the drug development timelines and find solutions for long standing problems.

In general, deep-science tech companies rely on a three-prong approach for success:

Problem orientation deals with identifying the problems and the opportunities to solve them. Currently, more than 97% of deep-science tech ventures are targeting at least one of the UN’s Sustainable Development Goals. In the next stage, they use a combination of approaches in science, engineering and design to conceptualize a novel technological solution. The design-build-test-learn cycle (DBTL) involves cycling through product development and the commercialization process alongside intellectual property protection.

Investment Trends in Deep-Science Technology

Considering that deep-science tech can require long drawn-out years of research, it needs investment and support at various stages of development. Analysis from Dr. Arnaud de la Tour and Massimo Portincaso at Hello Tomorrow in collaboration with Boston Consulting Group (BCG) shows that global capital flow into deep-science tech has grown more than 4 times from 2015 to 2020 to reach over $60 billion. In 2020, more than 60% of the investments were focused on synthetic biology and AI, which have had a major impact on the advanced diagnostics and therapeutics industry as well as alternative meat markets. Unsurprisingly, over three quarters of global capital flow has been concentrated in the US. While deep-science tech investments in Europe and the Asia Pacific are on the rise, they still represent a small portion of the pie.

India is a relatively nascent player in the global deep-science tech landscape, but investments are on the rise — up more than 200% since 2017. Over 80% of these investments went into companies at seed stage with products under development. Much of it is concentrated in the fields of artificial intelligence, machine learning and biotechnology. As these technology-first companies grow, they will impact multiple sectors.

Approaches for Deep-Science Technology Investing

Investing in Deep-science tech poses significantly more risk compared to general technology. These risks entail higher chances of product failure, longer commercialization timelines, and larger early-stage cheque sizes, among others. In order to mitigate risks, investors should note the following for their playbooks:

  1. Technical due diligence is the key: The moat in Deep-science technology investing lies in the technology being developed. A deep dive into the technology is essential to understand the value of what is being created while also assessing common parameters for an investment. Early-stage investors need to understand the technology risk by bridging information asymmetry.
  2. Longer pre-revenue phase demands stringent milestones: Unlike general software technologies, early-stage investments into Deep-science tech come with risks associated with high R&D cost, high barriers to entry, longer timelines for market entry, and fewer successes to benchmark. Identifying key milestones to achieve commercialization is critical for managing progress to go from product to market traction. These involve IP protection, product diversification, regulatory hurdle clearance and partnerships — all of which move Deep-science tech companies towards higher Technology Readiness Levels (TRLs).
  3. Deep-science tech requires an ecosystem: Deep-science tech companies go through different phases from Technology Readiness Levels (TRL) 1- 9. Grant giving entities typically support the R&D sandbox phase as private funds cannot take such premature risks. BIRAC, DBT and several other agencies actively support Deep-science tech ventures in India. Post the early development phase, an ecosystem is needed to facilitate partnerships with corporates, technical advisors and marketing affiliates to get through commercialization. Since technology is typically the moat, intellectual property protection is an important anchor while approaching ecosystem players.

“While all this may sound daunting, we need to keep in mind that investors in Deep-science tech aren’t playing for small multiples. If a technology matures and disrupts the market, we are talking way beyond unicorns.”- Dr. Ritu Verma, Ankur Capital

The Future of Deep-Science Technology

If the history of industrial revolutions is anything to go by, deep-science technologies are expected to completely transform the world in the coming years. As the world pushes to achieve the UN’s Sustainable Development Goals for 2030 within the remaining years, disruptive technologies will claim the forefront of solutions. While many of these technologies are under development, the companies leading them are undervalued. There is an overlooked upside potential. This presents an untapped niche market opportunity for VCs and other private investors in a dynamic market like India. There are several deep-science tech startups being incubated in universities and research facilities across the country. They are being supported by an ecosystem of grants, incentive programs and technical assistance while building a minimum viable product. With effective risk mitigation strategies in place, private investors can help and benefit from getting these technologies to the market.



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