This 1 AI stock could revolutionize biotechnology and the pharmaceutical industry

Ginkgo Bioworks (DNA -5.64%) is a biotechnology that runs heavily on artificial intelligence (AI). Between the need to perform basic workflows with high efficiency and the generation of tons of biological and production data that require analysis, Ginkgo will likely find that AI becomes more important to it over time.

This is especially true if it starts selling a key input that other biopharma companies need to use their own AI models. Its impact under these conditions could even be revolutionary for bioscience as a whole. Let’s dive in and appreciate why it’s so uniquely positioned.

Data is fuel for AI

One of Ginkgo’s goals is to become a business capable of ingesting a customer’s requirements for an experiment or workflow, implementing the requirements and running the experiment in the highly automated wet lab, and then delivering the data set back to the customer, cleaned and done. for analysis. The idea is for customers to get the scientific data they need at a lower cost and with far less struggle at the bank than if they were just using their organization’s resources.

Ideally, Ginkgo’s profit margin would come from its ability to generate lots of cheap experimental data, thanks to its investments in adaptive lab automation technology, as well as AI and machine learning (ML) solutions for bioengineering. But the company is not yet profitable.

This business model is nothing new in biopharma; there are many contract research organizations (CROs) and contract development and manufacturing organizations (CDMOs) that handle a wide range of laboratory and biological manufacturing tasks. Like a CDMO, the Ginkgo platform is equipped to take a customer’s biomanufacturing requirements and implement them, delivering the final product (whether it’s a population of bioengineered yeast cells or a vat of a specific protein or biomolecules). Once again, the idea is to offload each customer’s most painful processes and deliver the results they want at a lower cost, with the company profiting from the efficiencies its automation provides.

One thing that’s different about Ginkgo’s approach, and one of the few things that makes it an AI stock rather than just a biotech stock: it wants to be able to extract as much information from experiments or from the production cycles of a customer, so that it has high enough quality. and well-labeled data to help train specialized AI models of customers, assuming they exist.

If this ambition is realized, it will mark a major revolution in biopharma and the biomedical sciences as a whole. And it’s largely a matter of refining the relevant engineering to be more efficient until it becomes profitable. Here’s why.

In the idealized form of the scientific method, researchers try to understand the impact of changing one variable, such as the temperature in a laboratory incubator, on another variable, such as a cell’s rate of production of a particular protein. But when it comes to experiments involving cell biology, no one believes that the variable being investigated is the only factor that changes as a result of the investigator’s actions.

Even something as simple as increasing the heat in the incubator leads to a huge number of subtle changes in cellular activity, almost all of which are invisible to the researcher because it is far too cumbersome to use laboratory techniques to assess those changes at all. date.

At best, the Ginkgo platform could make them all visible and understandable. It could be as trivial as creating another automated workcell module for each of the additional analyses. It could then transmit the comprehensive data set to clients, whose AI models could then be trained to find rich relationships between variables previously thought to be unrelated.

This is the stuff that major breakthroughs are made of.

This revolution is still gathering steam

As amazing as the realization of his data-generating vision of the service might be, for today’s Ginkgo, it could also be a voice.

In Q2, it reported a net loss of more than $217 million, most of which stemmed from its deeply unprofitable operations. It has not proven that it can execute the desired programs for its clients in a way that, on average, creates shareholder value rather than destroys it. Providing very expensive services based on the development of a comprehensive set of experimental data, whether for AI training or any other purpose, will not contribute to the bottom line until biotechnology drastically reduces its operating costs and its efficiency increases substantially.

This makes Ginkgo a risky stock to buy right now.

However, it plans to achieve annual savings of $100 million in 2024 and another $100 million in 2025. Management’s target is to achieve adjusted earnings before interest, taxes, depreciation and amortization (EBITDA) by the end of 2026. In the second quarter, adjusted EBITDA was a loss of $99 million — worse than the same quarter last year, when it had a loss of $80 million. And if Ginkgo is really going to advance a scientific revolution in biopharma, it must continue to drive down costs while continuing to onboard more customers.

Investors should get a better picture of whether Ginkgo’s ambitious plans will come to fruition in the next 12 months. Until then, it’s best to hold off on a purchase.