AI can halve drug development time. Here are 3 smaller AI biotechs Cathie Wood likes.

The pharmaceutical industry has long used AI to develop drugs. Calculations by analytics firm Norstella in 2024 showed that four out of five companies were using algorithms in at least one drug-development program. AI could potentially shorten early-stage drug testing and development timelines by 30-50% and cut costs by 25-50%, says Boston Consulting Group. That would represent significant savings, considering that bringing a single drug to market takes an average of 10-15 years and costs $1-2 billion.

Recent industry data shows that AI-designed drugs have an 80-90% success rate, twice that of conventionally developed drugs, Harvard-based industry-research site 2 Minute Medicine notes. But there is a catch: that applies only to phase I clinical trials.

The figures are different at the next, intermediate stage: around 40% of candidates succeed in phase II, broadly in line with the rate for conventional molecules. By mid-2026, only eight AI-enabled candidates had completed that stage. They include rentosertib, a treatment for idiopathic pulmonary fibrosis from Hong Kong-based Insilico Medicine, which started the final stage of clinical trials in July. (In our recently launched newsletter on small- and micro-cap stocks, we did a deep dive into Insilico Medicine’s drug development programs and history – subscribe to the English-language newsletter here.)

Another candidate is GB-0895, an antibody from Generate:Biomedicines to treat severe asthma. The FDA allowed it to advance directly from phase I to phase III trials, which got underway in December 2025.

Japan’s Takeda is the only company in the world to have successfully completed every phase of clinical trials for an algorithm-designed drug, according to IntuitionLabs, a consultant. Its candidate, zasocitinib, treats psoriasis. Nimbus Therapeutics developed the drug together with Schrödinger, using computer modeling to select a molecule that blocks TYK2, an enzyme involved in inflammation. Takeda acquired it in 2023 and continued its clinical development. The FDA could approve the drug as early as 2027.

AI-powered drug discovery is attracting a wide range of players, including firms from outside of the industry. Chipmaker Nvidia announced an expansion of its investments in the field in 2023, followed by rival AMD in 2025.

Cathie Wood and her investment outfit, ARK Invest, are considered among the largest and most influential investors in the use of AI in biotech and drug development. Her ARK Genomic Revolution exchange-traded fund has returned 70% year to date. By comparison, the S&P 500, the broad-market benchmark, has gained 13.4% so far in 2026.

Below, Oninvest looks at three smaller AI drug developers that Wood's ETF is invested in.

Nasdaq-listed Recursion, which has a market capitalization of $2.3 billion, uses AI models to develop new drugs, but rather than relying on conventional computer modeling, it extensively automates real-world biological experiments.

Through its proprietary Recursion OS platform, the company runs up to 2 million experiments per week. This has enabled it to amass more than 50 petabytes of data, equivalent to roughly 10 billion songs, which would take approximately 66,600 years to listen to.

Recursion uses this database to identify promising molecules both for its own pipeline and in collaboration with other companies, including pharma giants Roche and Bayer. It also sells scientists access to the data it has accumulated. The company’s work has attracted interest from outside of the pharmaceutical industry, as well. In 2023, Recursion raised $50 million from Nvidia, which said its goal was to accelerate AI-driven drug discovery. Together, they built one of the world’s most powerful supercomputers, powered by Nvidia graphics processors.

The small cap currently has five candidates at various stages of clinical trials: four for cancer and one for familial adenomatous polyposis, an inherited condition in which hundreds of polyps develop in the colon and rectum. Another two candidates have yet to enter human trials.

Recursion currently generates revenue primarily from payments by its corporate partners. In the second quarter, its revenue fell almost 60% year over year to $7.7 million. The net loss narrowed 24% over the same period to $131 million.

Wall Street is broadly cautious on the stock: four analysts rate it a "hold" versus three "buy" calls, according to MarketWatch data. The average target price is $7.22 per share, implying almost 83% upside from the Thursday close.

Setting apart Absci, which has a market capitalization of $1.58 billion, is that it uses neural networks to identify not only compounds that could treat diseases but also their targets – molecules in the body, usually proteins, that the compounds are designed to act on.

Traditionally, scientists first select a target by manually studying scientific literature and databases. They then formulate a hypothesis explaining why that particular target should be attacked to treat the disease. At the next stage, they propose a solution: a new drug. “It sounds simple, but in reality, it is one of the most challenging ventures undertaken by humanity,” Absci writes on its site.

The reason is that there is still no complete understanding of how diseases emerge and develop: much of what is known about molecules in the human body is based on indirect evidence obtained, for example, from tests on animals or individual cells. As a result, most new drugs fail in clinical trials. The extremely low success rate – only around 12% of drugs make it to market – suggests that the wrong target was selected during the target-discovery process, Absci explains.

Absci reverses this process. It first uses AI to study human cells that are fighting a disease and then determines which disease they are fighting. This is how it selects a target. Absci then recreates the antibodies in its laboratory, providing a starting point for drug development. The company used this method to create ABS-201, an antibody for androgenetic alopecia, an inherited condition in which male sex hormones cause hair loss. The candidate is currently in early-stage clinical trials.

The company also intends to test the same antibody in women with endometriosis. Its partner in this is pharma giant Eli Lilly, which has invested $40 million in Absci. However, their agreement does not confer any rights to the ABS-201 program on Eli Lilly.

Absci’s other partners include Merck, Spanish pharmaceutical company Almirall, chipmaker AMD, and the Bill & Melinda Gates Foundation. The latter awarded a grant to a joint project between the biotech and the California Institute of Technology (Caltech) to develop an HIV vaccine.

For the second quarter, the company reported revenue of $300,000, half the year-earlier figure. Meanwhile, the net loss widened 8% to $33.2 million.

Wall Street is broadly upbeat on Absci stock: 10 analysts rate it a "buy" versus a single "hold" recommendation, according to MarketWatch data. The average target price is $14.40 per share, around 60% above the last close.

Schrödinger, which has a market capitalization of $2 billion, differs significantly from Recursion and Absci. It was founded in 1990 and for decades focused exclusively on developing molecular-design software, which it licensed to scientists and pharmaceutical companies.

The software allows them to evaluate molecules virtually before synthesizing and testing them in the laboratory, assess whether they can be made, and identify the most promising compounds, according to a description published by Bayer, which says it has used Schrödinger’s technology for decades. In addition, the software has already helped create two cancer drugs: Agios Pharmaceuticals’ Tibsovo and Idhifa, jointly developed by Agios and Celgene.

Schrödinger first ventured into drug development in 2009, when it cofounded Nimbus Therapeutics with Atlas Ventures. Nimbus uses AI to develop drugs, advances them through the early stages of clinical trials, and then sells them to industry giants. In 2016, for example, its liver-disease drug program was acquired by Gilead Sciences. In 2023, Japan’s Takeda acquired a candidate with potential applications in psoriatic arthritis and systemic lupus erythematosus for $4 billion upfront and up to $2 billion in potential future payments. The drug could become the first AI-created therapy to receive regulatory approval.

Almost a decade later, in 2018, Schrödinger began developing its own drugs. Its current pipeline includes two experimental oncology drugs in early-stage clinical trials. Another five candidates across various therapeutic areas have yet to start human trials. Schrödinger also participates in 19 programs with other pharmaceutical companies and is eligible for royalties on their future sales.

The company's second-quarter revenue rose 7.5% year over year to $58.89 million. Net income came in at almost $6 million versus a net loss of $43.2 million a year earlier, primarily because Eli Lilly’s acquisition of Ajax Therapeutics generated a $45.9 million gain on Schrödinger’s investment in Ajax. The operating loss, meanwhile, was $41.5 million.

Five Wall Street analysts recommend Schrödinger stock at "buy" versus two "hold" ratings. Still, the average target price is $21.43 per share, almost 20% below the last close.

This text is for informational purposes only and does not constitute personalized investment advice.