As we've all been told, artificial intelligence (AI) is going to disrupt everything in healthcare, from scheduling a doctor's appointment to developing new medicines. But there's a lot more to AI than large language models (LLMs) like ChatGPT.
In fact, there's a good chance that AI's impact on biotech will go far beyond what consumer-facing AI applications might imply. Investors will accrue many of the benefits. Here's my predictions for how this trend will play out, and why it's bullish.
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These companies are already implementing AI services for biotech
Biotech businesses face a number of challenges.
The first is the need to perform years of research and development (R&D) work in the lab and in the clinic before they have hope of generating revenue from sales of a medicine or new technology. That process takes a lot of money, and success with a given project is much less likely than failure.
What's more, as a program advances through the pipeline, from discovery to preclinical trials, then to clinical trials and beyond, the associated expenses just get larger and larger. It's cheap enough to run a prototyping experiment in the laboratory to preliminarily prove a concept. And, in the big scheme of things, preclinical testing in animal models isn't that expensive. However, as soon as a company starts to perform large late-stage clinical trials with real people, the total costs quickly balloon into the tens of millions of dollars and often beyond.
Another big issue is that for pre-revenue biotechs, there's a finite amount of cash in the bank. So there's a strong incentive to only advance programs that are judged to be the most likely to succeed at each step of the development process, as failure means expending resources that can't be easily recovered. Similarly, when it comes to manufacturing doses of a medicine for the purposes of clinical-stage testing, the incentive is to make every dollar count at first and focus on scaling up the output capacity only later on, once the project is more proven.
AI will help biotechs handle these challenges by reducing the cost of both R&D and manufacturing. In turn, that will enable them to advance more programs with the same amount of money. More shots on the goal means scoring more frequently. And that will drive higher returns for biotech stocks as a category.
But investors shouldn't assume that companies are going to develop their own AI-based solutions to the industry's long-standing obstacles. Instead, they probably will outsource key aspects of their R&D and manufacturing processes to platform biotechs that aim to heavily integrate AI, like Recursion Pharmaceuticals (NASDAQ: RXRX) and Ginkgo Bioworks (NYSE: DNA).
For instance, part of Recursion's business model is to use AI to help biotechs develop and vet leads for developing new therapies.
That implies that eventually it could be possible for a business's discovery-stage expenses to be lower. More importantly, Recursion claims that its data-intensive approach to lead generation results in fewer late-stage failures, thereby saving capital. If that turns out to be true, and if other platform companies follow suit in offering a similar proposition to customers, there will also be fewer instances of biotech stocks cratering after whiffing their clinical trial goals.
Ginkgo's value proposition points to a parallel trend in manufacturing.
It claims that its customers can save cash by paying to have the company do much of the bioengineering work required to implement biomanufacturing processes. Some of those bioengineering tasks may eventually be offloaded to AI. It also runs the manufacturing protocol with its highly automated work cells, passing the final product off to the customer, who avoids the need to invest in expensive equipment of their own. Plus, customers can potentially save on labor costs too.
But that's not all. Other companies are aiming to bring AI to the conception, operation, and analysis of clinical trials. Automating aspects like regulatory compliance and patient recruitment could go a long way toward driving down costs.
So with the benefits of AI potentially slashing expenses while reducing the chance of problems practically across the board in biotech, a lot of big and common pain points will be mitigated. And that's bullish for the entire industry.
Don't believe everything you read
As delightful as the efficiency improvements posited by AI companies are likely to be, it's important for investors to exercise critical thinking when considering the probable affects.
Biotechs will still be constrained by their access to capital. Clinical trials will still be expensive and fail to meet their endpoints on a regular basis. Large-scale manufacturing will still be a significant cost driver for many players. And, in case it wasn't obvious, many biotech stocks will still go down when problems arise.
Furthermore, recognize that Recursion Pharmaceuticals and Ginkgo Bioworks may not be able to deliver the actual economic benefits of AI that they are claiming today.
Nonetheless, as AI's implementation in biopharma becomes consistently more sophisticated in the coming years, it could be transformative if it can decrease expenses enough to make the average biotech's cash stretch a bit more than it does today. In the long run, AI might even help biotech stocks to become less risky, which is a perfectly good reason to be optimistic about the industry's prospects right now.
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Alex Carchidi has no position in any of the stocks mentioned. The Motley Fool has no position in any of the stocks mentioned. The Motley Fool has a disclosure policy.
