AstraZeneca has put hundreds of millions of dollars into AI deals, with an eye toward not just accelerating the development of drugs that treat cancer after it appears but also in creating diagnostics that can catch cancer earlier than current methods allow.
AstraZeneca has put more than $1 billion in biobucks into a series of artificial intelligence partnerships over the past few years. In the basement of Chicago’s McCormick Place, in the spooky, cubicle-like temporary meeting rooms that ASCO 2025 sets up for meetings, I asked the company’s head of U.S. oncology for lung cancer Arun Krishna what exactly that money was paying for. He leaned back in his squishy office chair before answering.
“AI is such a huge topic,” he said. “Let me break it down into a life cycle.”
According to Krishna, there are three stages of AI drug development. The buzziest one, where companies like Insilico and Generate:Biomedicines have staked their claims, is in discovery. That’s where predictive AI can, hopefully, identify potentially useful molecules much faster than the months or years the process would take in wet labs. “Now it can be 30 days or less,” Krishna said.
The second stage is in clinical trials.
“Can we use predictive AI that we have to flag patients who might be eligible?” Krishna asked. According to Krishna, this is not just a matter of analyzing existing patient data and selecting people who might be eligible, something a human can do just fine, but a matter of predicting who might benefit the most from a new drug candidate. A patient, for example, might not have developed symptoms or biomarkers that directly qualify them for a clinical trial, but they could develop those down the line, and AI might be well suited to make that determination based on other clues in their profile. It may also be able to identify patients who are already eligible but just haven’t gotten the proper tests.
“Even if we don’t know a biomarker,” Krishna said, “if [a patient] fits a profile, you should test for that inclusive biomarker. AI fills in the gap for you.”
This is still an active area of discussion for regulators, clinical trial organizers and academic centers. But Krishna forecasts that AI-based clinical trial patient enrollment could be an active part of the drug testing landscape “within 1-2 years.”
The third stage is the most unusual: population screening. According to Krishna, the next step for AstraZeneca is not just in treating cancer but in getting involved at the diagnostic level.
Krishna gave an example: people often develop incidental pulmonary nodules (IPNs). Most of the time they are benign and lead to nothing, but in 5–6% of patients they become cancerous. They can also be missed by radiologists reading a CT scan. Krishna said that AstraZeneca has done side-by-side comparisons of its predictive AI algorithm versus a human radiologist. The AI can spy a cancerous nodule where a radiologist would say there is nothing.
To be clear, there’s been a rise over the last few decades in the detection of IPNs, mostly driven by increased numbers of scans being ordered, and the vast majority are benign, but as Krishna put it, the company wants to be involved in the entire arc of a patient’s illness.
“It is unusual,” Krishna said. “We primarily want to treat via our drugs. It’s important but not sufficient. Our goal is to look at the entirety of the patient pathway. AI is a critical component of that. That’s population-based screening.”
Partnering For Success
To take advantage of AI’s capabilities across all board, AstraZeneca has been scooping up collaborators. “We know that we’re not an AI company but that we have to partner,” Krishna said.
In April, AstraZeneca entered into a three-way partnership with Tempus AI and Pathos , with $200 million in data licensing, to build a multimodal AI oncology model. “This is about building those data foundations,” Krishna said.
That followed several other AI-based deals made by AstraZeneca. In December 2023, the pharma committed up to $247 million to AI development company Absci with the goal of finding new targets in unspecified areas of oncology. Also in late 2023, AstraZeneca gave Verge Genomics $42 million up front, with $840 million in milestone payments on the line, to use the biotech’s AI platform to find new targets in neurodegenerative and neuromuscular diseases. AstraZeneca has also struck multiple collaborations with BenevolentAI and AI immuno-oncology firm Immunai.
When it comes to population screening, the pharma is working with Greenbaum Cancer Center at the University of Maryland Cancer Hospitals. “We’re looking to roll this out at scale. We’re looking to get up to 50,000 CT scans within 18 months,” Krishna said.
It’s not difficult to understand the potential role AstraZeneca sees AI playing in drug development. The company has put more than $1 billion down on it, eagerly sent Krishna to talk with me about it. And when Krishna speaks, it erases all doubt:
“We believe that AI is the future. It will really enable every aspect of that patient journey and ultimately serve our purpose of eliminating cancer. We want to play an integral role in that.”
