Artificial intelligence (AI) has given a fillip to cost-cutting efforts in a wide range of industries, including health care, an area in which rising patient costs remains a hot-button issue. For investors, opportunities could come from companies that can capitalize on AI as a way to cut costs via improved workflow and more efficient administrative tools. In addition, AI may lead to attractive growth in companies that can use it to accelerate R&D and/or be more productive in diagnosing patients. In our view, the health care space is ripe for disruption, especially in the biopharma segment, which is highly profitable but extremely inefficient. In this piece, we detail some of the most important AI trends for investors to watch in health care.
Rising health care costs are a challenge being faced by every country, but it’s a particularly acute issue in the United States (Figure 1). US health expenditures represented 18% of GDP in 2021, the highest among wealthy developed nations, and is growing at a 5% compound annual growth rate (CAGR).1 This is unsustainable.
On a per capita basis, the US spent nearly twice as much on health care as comparable countries ($12,197 vs $6,345),1 but we’re not getting much bang for the buck. Americans have a lower life expectancy and the gap has actually widened as our spend has increased (Figure 2).
Exscientia is an example of an AI-first biotechnology company. By using successive AI-driven design cycles, company scientists were able to identify an AI-designed kidney cancer drug by testing 80% fewer compounds (160 instead of 2,500), taking 90% less time (9 months instead of 54) than the traditional approach. This is the company’s third AI-designed drug in clinical trials. Exscientia thinks AI can reduce drug discovery time by 70%, decrease the number of compounds synthesized by a factor of 10, and lower the capital required to go from finding a biological target through completing preclinical toxicology studies by 80%.4
While AI is likely to significantly impact the way we receive care, it’s not a silver bullet and its impact will be gradual. There are several headwinds to the industry’s adoption of AI.
First, the human connection remains vital in many facets of health care. You build up a level of trust and comfort with your doctor. Health care is still very personal. According to a Pew Research Center survey, the majority of Americans (60%) are uncomfortable with health providers relying on AI to make clinical decisions. Women, in particular, expressed discomfort (66%).
That said, the level of patient comfort does vary based on what AI is being used for: There was widespread support for skin cancer screening (65%). Conversely, people were very opposed to mental health chatbots (79%) or using AI to prescribe pain medication (67%).
Additionally, in the Pew study, Americans were evenly split on whether AI would make the quality of health care better or worse. They did believe it would result in fewer mistakes and less racial bias. However, there were data security concerns and a belief relationships with providers would deteriorate.
Second, certain parts of health care require physical interaction. An in-person check-up is still more effective in certain instances. And AI can’t draw blood or perform a biopsy.
Third, the health care industry tends to be very conservative and is slow to embrace change. Health care practitioners have been conditioned to base decisions on evidence that usually comes from multi-year clinical trials. They need to see the data before they’re willing to support new approaches.
Finally, whether they want to admit it or not, health providers are financially motivated. You can have a great product that’s FDA approved, but if providers aren’t getting paid to use it, they won’t. Reimbursement is the single largest hurdle to AI adoption. According to a Boston Consulting Group/UCLA Biobank survey, 72% of respondents cited reimbursement as the barrier preventing patients from accessing novel medical devices in the US. Only 16% cited FDA regulation.
Health care costs are an increasing global burden. AI can help bend the cost curve, but it’s not a panacea and will take time. Even so, for most large health care companies, rather than being a differentiator, it will be table stakes. There are some small AI-first biotechs or biosimulation software providers, but large cap companies will be increasingly inclined to adopt AI in one form or another to keep up with industry innovation. A company’s adoption may simply be on the cost/administrative side, or it can be more transformational, such as new work in drug discovery and development. Still, importantly, the large health care stalwarts will not be the only adopters of AI, with peers left behind; in our view, all health care companies will be leveraging AI.
For the Life Science Tools industry, AI may represent a longer-term risk given the potential wealth transfer from instruments and consumables to semiconductors and super computers. On the flipside, the consumer should be the ultimate winner. AI promises more life-saving drugs and devices that come to market sooner and are offered at lower cost. AI also could spawn improved practitioner productivity, which will broaden access to health care, and a healthier population, which should drive economic growth.