Patent for Advanced AI Technology to Track and Stop Cancer Cell Growth
A new artificial intelligence tool aims to diagnose specific forms of acute myeloid leukemia — and make treatment suggestions — in record time. Photo by Matthew Modoono/Northeastern University
BioE Assistant Research Professor Kiran Vanaja was awarded a patent for “Multi-dimensional phenotypic space for genotype to phenotype mapping and intelligent design of cancer drug therapies using a deep learning net.”
This article originally appeared on Northeastern Global News. It was published by Noah Lloyd.
How AI could speed treatment for patients with this deadly cancer
Acute myeloid leukemia, or AML, is a rare and aggressive cancer that can affect people of all ages. Kiran Vanaja, an assistant research professor in bioengineering at Northeastern University, says that AML also has a high recurrence rate and no one-size-fits-all treatment option.
Because AML impacts both blood and bone marrow, oncologists need samples of both through blood draws and a bone marrow aspiration to determine the disease’s particular genetic makeup and which treatment might be most appropriate. It can often take a month or more after diagnosis for those with AML to start receiving potentially life-saving treatment. The cancer’s “median age of survival is less than five years after initial diagnosis,” according to Vanaja, so time is of the essence.
Based out of Northeastern’s Roux Institute in Portland, Maine, Vanaja was recently awarded a patent for an artificial intelligence tool that, he hopes, will save time.
The new tool includes a platform that may help oncologists not only diagnose the disease but also map out the many different genetic mutations in a given patient that might have caused their AML. Once the mutations are mapped, the platform also includes a computational model known as a neural network that can both suggest potential drugs for an individual patient and also determine the likelihood of the patient developing resistance to those drugs.
The tool could help cut the preliminary time from diagnosis to treatment from weeks down to a single night, Vanaja says.
The LEGO blocks of life
One of the challenges to understanding what might be happening with AML is understanding what’s happening inside the cancerous cells. And to test their new tool, Vanaja’s team had to go back to the basics of cell biology.
Using conventional strategies — which are still the gold standard, he notes — such as through gene sequencing, RNA sequencing or other techniques, researchers might gain information about what’s inside the cell. But with cancer, Vanaja says, what’s inside the cell doesn’t always align with how the cell acts.
Cells don’t start out as cancer cells, but as basic stem cells that later specialize into different kinds of tissue, whether of the lungs, liver, arteries or something else.
But when a cell becomes cancerous, Vanaja says, it loses that primary specialization, as the team also learned when they treated a bunch of AML cells with FDA-approved therapies.
Many of the cancer cells died off, but after a couple of weeks, Vanaja and his team looked at the surviving cells and observed that they had changed in radical ways. “The cells undergo massive rewiring when subjected to these cancer therapeutics, because they’re literally trying to survive by turning on anything and everything possible.”
Read full story on Northeastern Global News