The Next Big Thing

10 years ago was the time to invest in AI. Now is the time to invest in gene tech. It will change how we feel and what we touch as much as AI is changing what we know.

Startup waves

From when computers were invented through the 1970s, only large organizations could afford them and only PhDs were allowed to use them.

In the 1980s, things changed. The cost of electronics came down. Computer nerds were freed to create. Things became digital. A new business model appeared called a software company. Software companies created tremendous value. Microsoft and Apple are two, but there were many others that went public or were acquired. They returned a lot of value to their investors. The legendary VC firms are the ones who funded in the computer revolution in the ‘80s.

Computers enabled the development of the internet, which enabled cloud-supported mobile devices, which collected the big data, which enabled AI through the following four decades. However, computer chip technology, internet, mobile, and the foundational developments in AI have matured. Like the US auto industry, the US chip industry has 3 big players (Nvidia, Intel, and Qualcomm). The US AI software industry has 3 big players (Microsoft, Google, and Amazon). There are still many new "AI" startups, but they are addressing ever smaller market niches with less value creation potential than the software startups of past decades.

There is a large opportunity to build companies that apply gene tech and create synthetic biology to gain a market advantage that was previously impossible.

Why now?

Several factors have changed in the world within the past 10 years that will enable the gene tech revolution.

AI programs such as AlphaFold can model the behavior of complex large molecules without lab experiments. In ancient times, biological research could only be performed in vivo. In modern times we learned to do in vitro research. In the future, much biological research will be done in silico.

The engineers of buildings, vehicles, and computer chips model their designs in software before products are built. AI has enabled computer aided design for living organisms.

New Methods

Since 2012, scientists have developed and improved methods for precise editing of DNA using CRISPR-Cas gene editing. Also in the 2010s, scientists improved methods for sensing and imaging DNA using nanoparticles. Next generation sequencing of DNA and RNA has improved in sensitivity and accuracy. COVID-19 caused regulators to allow delivery of drugs (vaccines) encapsulated in lipid nanoparticles for the first time. These are just a few of the new genetic engineering tools that startups are using creatively.

Cost

The cost of sequencing a genome has fallen faster than Moore's law. It is now cheaper than the $666.66 retail price of the first Apple computer. A bio hobbyist can now buy a desktop DNA printer for the price of a high-end office photocopier. The software revolution illustrates that when hobbyists can afford the tools of the trade, it unleashes new industries.

Talent

The New York Times reported in in 2022 that some high schools teach CRISPR gene editing as classroom lab experiments. YouTube abounds with videos on biohacking, teaching the public how to change their own genes. It is estimated that there are now 1 million people in the world with a formal education in genetics. Even still, gene tech startups are clamoring for scientists with an entrepreneurial spirit.

Conclusion

At the beginning of a wave of a new technology, startups are solving big, valuable problems. As an industry matures, startups solve gradually smaller niches in the problem space. Startups solving bigger problems have a better chance of achieving enough value for a good return on investment to investors. The gene tech wave is beginning. Now is the time to invest.

Report abuse