Immunomics Stocks: 3 Ways to Play This Massive AI-Biotech Megatrend

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Biotech has long seemed to move slower than its fellow tech fields due to the complexity of biological systems and the difficulty of drug regulations. However, that precedent is set to change thanks to the growing implementation of artificial intelligence (AI), upending the field and bringing big changes to the industry. As a result, the AI-biotech trend will likely determine the winners and losers of the next few decades.

Biotechnology is especially amenable to AI because it involves complex systems and a lot of data. Big data is one of the foundations of good AI. The companies best-positioned to make the most of this trend are those that can now harness that data to make future discoveries easier.

For example, over 80% of drugs never make it through clinical trials, but AI can predict which ones will and won’t. That means that if companies can focus on the winners and ignore the guaranteed losers, they could vastly decrease their costs of bringing drugs to market. Similarly, synthetic biology companies usually make and test hundreds of failed proteins for each successful one they can use. But AI can be used to cull back these numbers before the making and testing phase. If a synthetic biology company now only needs to make and test tens of proteins to get a successful one, costs go down substantially.

The AI revolution is still in its infancy, so now is the best time to invest in the AI-biotech trend of the future. With that in mind, here are three companies an AI-Biotech investor should look out for.

Ginkgo Bioworks (DNA)

Source: T. Schneider /

Ginkgo Bioworks (NYSE:DNA) is harnessing the power of AI to optimize enzyme development, with enormous implications for many industries. Key to their future is the recently announced collaboration with Alphabet (NASDAQ:GOOG; NASDAQ:GOOGL) to use Google cloud and AI infrastructure. Not only that, Google will provide funding to support Ginkgo in creating and fine-tuning AI models for biological applications. Together, this partnership hopes to catapult Ginkgo to the next level.

The key to Ginkgo’s AI dreams is big data. As I mentioned, good AI needs an exceptional amount of data to train on, and Gingko thinks they can provide it. Ginkgo already produces huge amounts of data through high-throughput engineering and testing. When tasked with building or improving enzymes for customers, they create numerous enzyme strains, each with subtle variations. By testing and analyzing each strain, Ginkgo not only identifies the best enzyme for the customer, but they also build a database of how every variation affects the enzyme. That data can be pulled together to build an AI model which streamlines the process significantly. That allows Ginkgo to focus on making and testing winners and avoiding guaranteed losers.

The beauty of this approach is its iterative nature. With every project, Ginkgo builds their database and fuels their AI models. This accumulated knowledge lets the AI continuously improve which in turn improves their core business allowing them to take on more and more projects. Every Gingko project is then laying the foundation for even more and better projects down the road. And this powerful focus on the AI-biotech trend makes Gingko a strong stock for the future.

Recursion Pharmaceutical (RXRX)

Source: Piotr Swat /

Recursion Pharmaceuticals (NASDAQ:RXRX) is investing big in the AI-biotech trend. They recently partnered with NVIDIA (NASDAQ:NVDA) and will receive $50 million dollars with their access to NVIDIA’s advanced AI tools. They are also acquiring Cyclica and Valence Labs, two AI-driven drug discovery companies. Taken together, Recursion is building a strong AI-driven platform to revolutionize the drug industry.

What makes Recursion special is that instead of focusing solely on specific diseases, they aim to make an AI-powered map of all human biology. With such a map, Recursion is betting on a process to create any drug to fill any niche, rather than betting on individual drugs.

The fact is, drug testing is fraught with peril. Drugs may be discovered that have a positive impact on one part of the body. But in testing, they have negative impacts on another part, leading to failure in clinical trials. Recursion’s AI-driven map seeks to predict these off-target effects in advance, which lets them eliminate “failure” drugs at an early stage. It also lets them predict the behavior of structurally or chemically similar drugs. Maybe a drug works well except for a certain subset of patients due to a rare reaction. Recursion can then search for a highly similar drug which won’t have this reaction, and use that.

Clinical trials are costly, lengthy, and have a terrible success rate, Recursion’s mission is to change all that. By leveraging the tools provided by the new AI-biotech trend, they can make themselves big players in the trillion-dollar drug industry.

Eli Lilly (LLY)

Source: Vi

Eli Lilly (NYSE:LLY) has long been investing in the AI-biotech trend. They recently announced a $250 million investment in XtalPi, an AI-powered drug discovery company. This collaboration will use AI to develop drugs for an as-yet-unnamed target. And at the regulatory level, Eli Lilly has partnered with Yseop, a natural language processing company. Yseop will help Eli Lilly turn scientific data into a compelling narrative to give to regulators. It may sound unscientific, but facts alone don’t always win over regulators. By ensuring that their facts are presented as persuasively as possible, Eli Lilly is setting itself up for much smoother regulatory approvals down the line.

Eli Lilly’s biggest advantage in AI is their extensive history in drug discovery and commercialization. Together, these provide a treasure trove of data that’s invaluable for AI model development. Taken together with their deep financial resources, Eli Lilly is one of the best positioned companies to take advantage of the AI-biotech trend.

Because Eli Lilly’s future is built off a very strong present. Their most recent earnings report shows revenue growing from $6.5 to $8.3 billion year on year. And net income grew from $952 million to $1,763 million over the same interval. Eli Lilly can afford the data, cloud storage, and computing power needed for good AI in spades, more than almost any other biotech company on the market. So for investors seeking a strong financial base along with a great opportunity to take advantage of AI, Eli Lilly is one of the best stocks you’ll find.

On the date of publication, John Blankenhorn held long positions in GOOGL and NVDA. The opinions expressed in this article are those of the writer, subject to the Publishing Guidelines.

John Blankenhorn is a neuroscientist at Emory University. He has significant experience in biochemistry, biotechnology and pharmaceutical research.

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