In the evolving landscape of technological innovation, few names resonate as strongly as that of Cathie Wood, the founder and CEO of ARK Investment Management. Affectionately called the "female Warren Buffett," Cathie Wood has been a fervent supporter of revolutionary technologies that promise to reshape industries. Recently, she has turned her keen focus towards a burgeoning frontier: the intersection of artificial intelligence (AI) and healthcare, which she asserts is the most undervalued application of AI.

This ambition was further outlined in a recent report by Wood's ARK research team, an exhaustive 148-page document titled "Big Ideas 2025." The report meticulously dissects five transformative technological platforms: AI, robotics, energy storage, public blockchain, and multi-omics sequencing, emphasizing how their complex intertwining could catalyze exponential growth across various sectors and initiate a seismic shift in the global economy.

Among the pivotal themes discussed within the report is multi-omics sequencing, which represents a cutting-edge approach in genomics and molecular biology. The researchers highlighted a promising trend — the potential of AI-driven autonomous laboratory systems to drastically slash the costs associated with drug development. With an avalanche of multi-omics data, these systems could redefine an industry that has long struggled with efficiency and returns on investment.

Under the auspices of AI technologies, multi-omics holds the promise of enhancing our understanding by generating vast datasets, conducting tests, making inferences, and guiding development efficiently. This approach could resolve issues related to small patient populations and refine the process of patient and disease identification, consequently shortening the time required to bring a drug to market from 13 years down to 8 years while reducing total costs by a staggering fourfold.

ARK's projections are striking; they anticipate that by 2030, the performance of multi-omics will improve by an order of magnitude. This improvement encompasses several areas:

  • AI is expected to accelerate the commercialization speed of drug development by 1.6 times, lower costs by four times, and amplify return rates by five times.
  • In molecular diagnostics, the productivity for cancer screening could skyrocket by a factor of 20, while the cancer monitoring market could expand tenfold.
  • In terms of multi-omics tools, the cost of reading biological information, such as DNA, may drop by 100 times, and writing costs could be reduced by 1000 times.
  • Moreover, the efficacy of therapeutic drugs could outstrip standard care treatments by 20 times and outperform the best precision medications by 2.4 times.

To contextualize these numbers, consider the role of AI models such as AlphaFold, which have achieved groundbreaking advances in protein structure prediction, operating with a remarkable 508-fold efficiency compared to traditional methodologies. The latest iteration, AlphaFold3, is capable of predicting over a billion structures, including complex multimeric assemblies, protein-ligand complexes, and interactions between proteins and nucleic acids.

Furthermore, in the domain of cancer diagnosis and monitoring, technologies that detect minimal residual disease can identify cancer recurrence an impressive 20 months earlier than conventional imaging methods. The ARK report posits that MRD detection will soon become a standard part of care for every cancer patient, potentially generating vast amounts of data within the next five years, which would dwarf even the largest genomics projects to date, such as the UK Biobank, by a staggering 700 times.

The potential for multi-cancer screening is another noteworthy area of growth, leveraging liquid biopsy technology that allows for the simultaneous screening of various cancers with just one blood draw. This advance could double the potential market size in the United States, bringing it to a soaring $240 billion. Equally impressive is the expectation that screening costs could fall by five times, thereby quadrupling the number of lives saved.

In the realm of drug development, automation driven by AI is set to transform traditional processes. ARK's analysis suggests that the time to market for new drugs could be shortened by as much as 40%, reducing total costs from $2.4 billion to just $600 million.

Moreover, AI-powered drug development could extend patent protection periods, dramatically enhancing the economic benefits associated with drugs:

  • The current AI methodologies may shave off 2 to 3 years from development timelines, increasing a drug's intellectual property value by 30% to 50%.
  • Emerging AI design techniques could potentially cut development times by 4 to 5 years, elevating the value of intellectual property by 70% to 80%.

Over a 30-year span, AI-designed drugs could generate cumulative cash flows reaching $4 billion — representing more than four times the returns of traditional drug models. Curative drugs, in particular, are projected to deliver 20 times the value of typical medications and 2.4 times the value of chronic prescription drugs that merely manage conditions.

When assessing the financial outcomes of AI-accelerated curative drugs, it’s anticipated that during initial human trials, their worth could exceed $2 billion — a substantive return, given that conventional assets typically just cover clinical phase one costs.

ARK asserts that the integration of AI in drug development and the pursuit of disease cures could fundamentally overturn trends of diminishing returns that have plagued the pharmaceutical and biotechnology sectors for decades. Companies that prioritize AI technologies focusing on curative drug development could see returns on investment ranging from 30% to 47%, significantly outpacing the industry’s mean performance.

Nevertheless, Wood warns of potential disparities emerging within the industry. Traditional pharmaceutical companies that resist adapting to this technological shift may find themselves at a competitive disadvantage. Many existing development efforts could transform into sunk costs as nimble AI-centric platforms swiftly roll out curative medications, thereby eradicating certain diseases altogether.

In a recent interview with CNBC, Cathie Wood reiterated her belief that the most unnoticed investment opportunity within the current AI frenzy is indeed healthcare. She stated, "There are 37 trillion cells in our bodies, all of which will be sequenced to search for treatments. I believe healthcare is the most undervalued application of AI. The healthcare industry currently holds a staggering amount of storage, and data is indeed the key." Wood’s flagship fund, the ARK Innovation ETF, invests in a variety of healthcare stocks, including Recursion, Crispr Therapeutics, Tempus AI, Twist Bioscience, and Beam Therapeutics. She pointed out how Recursion has leveraged AI to amplify the number of hypotheses generated by their researchers tenfold.

While Wood believes that healthcare will provide some of the most profound AI applications over the long term, she also notes that automated ride-hailing services may emerge as the largest AI application in the next five to ten years. Thus, as we stand on the brink of what could be a transformative era in healthcare facilitated by AI, the implications for investment, innovation, and societal health could be significant.