How Genetic Testing Company Tempus AI Is Using Data and Artificial Intelligence to Help Personalize Cancer Care

Lefkofsky’s journey into cancer care began with a personal experience. He founded Tempus more than a decade ago after his wife was diagnosed with breast cancer.

“I was just perplexed at how little data was a part of her care,” Lefkofsky recalls. Although she received excellent treatment from her doctors, he was struck by how difficult it was to access information that could help guide important decisions.

That experience inspired a mission: connect genomic sequencing with clinical data so doctors everywhere—not just those at major academic medical centers—could make more informed treatment decisions.

Today, Tempus has become one of the largest providers of cancer sequencing and data-driven decision support in the country.

“When we started 10 years ago, very few patients were sequenced,” Lefkofsky says. “It was way less than 10% of cancer patients.” Today, he estimates that number has increased dramatically as genomic testing has become a more common part of cancer care.

One of Tempus’ primary goals is helping patients gain access to molecular profiling, a type of testing that looks for genetic changes in a tumor. These findings can sometimes identify targeted therapies that may be more effective for a particular patient.

Beyond testing, Tempus also works to accelerate cancer research by sharing de-identified data with healthcare providers, researchers, and pharmaceutical companies working to develop new treatments.

But Lefkofsky believes the next major leap forward may come from artificial intelligence.

“Tempus at its heart is a technology company,” he explains. With more than 500 petabytes of clinical, molecular, and imaging data–a massive trove–the company is using large AI models to uncover patterns that were previously impossible to detect.

According to Lefkofsky, AI is helping move precision medicine beyond simply identifying a cancer mutation. In some cases, these tools may help predict whether a patient is actually likely to respond to a specific treatment.

“We’re able to determine whether or not a patient’s likely to respond to that drug,” he says. “Which helps doctors be way more precise in terms of ensuring that the patient’s on the right path.”

For patients, the promise is straightforward: more personalized treatment decisions, faster access to the most appropriate therapies, and a future where cancer care is increasingly guided by data rather than guesswork.

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