On average, it takes about eight years from the time a potential cancer drug enters clinical trials until it’s approved, according to the American Cancer Society.
But not every drug that’s approved works with every cancer patient. Often doctors must try different therapies on the patient until one is deemed effective.
Saving that time spent on trial and error is the focus of South Carolina startup KIYATEC.
During his Ph.D. research, Matthew Gevaert ran experiments to try to evaluate cells reactions. He had issues with the data coming from 2D cell cultures — cells that are flat on the bottom of a petri dish and “not very accurate to the human body.”
That’s when he learned about 3D cells, and the importance of working with cells that mirror those in the body. He started creating more accurate models of cells to get better data.
“You can produce data that’s orders of magnitude more valuable, and frankly people aren’t doing it like they should,” Gevaert tells Hypepotamus. “There’s a tremendous opportunity to be on the front edge of bringing that kind of data into the world.”
Gevaert initially founded KIYATEC to commercialize the ex vivo 3D cell culture technology he developed. He started testing the market and, to his surprise, companies said they wanted the data versus the cell culture itself.
In 2011, the startup found its focus after an invitation to move into a cancer institute in South Carolina. Their location helped narrow down their value proposition to using the tech to analyze tumors and predict a patient’s response to cancer therapies.
“When the doctor is making a decision on which drug to give a cancer patient, they’re using the best information they have, but none of it is derived from the actual interaction of the drug and the patient’s live cells,” says Gevaert.
Their initial clinical study, 3D-PREDICT, uses live cancer cells that are removed during a biopsy or surgery. The cells are grown in the lab so researchers can assess how they will respond to the treatment before starting it on the patient.
This way, doctors can try different therapies, established or experimental, to see which one is most effective at killing the diseased cells. This saves valuable time and can prevent the patient from getting sicker from an ineffective drug.
“It translates into a solution that uniformly doctors are excited about and want. It makes for a good business when you’ve got a great unmet need, a big market. The opportunity to do a lot of good as well is a big motivating factor,” says Gevaert.
KIYATEC’s current priority is ovarian cancer and glioblastomas.
Their competitors, says Gevaert, operate on a tools model where they sell equipment to scientists to do the experiments and create the data.
KIYATEC, on the other hand, produces the data in-house in their lab in Greenville, South Carolina. They can test between eight to 12 drugs depending on the panel.
Their predictive modeling is now being used in clinical trials at leading hospitals around the country.
KIYATEC’s revenue today comes from a mix of contracts with pharma/biotech companies and the National Cancer Institute, and also through government grants.
“We have three business verticals: one is clinical testing for drugs that are safe and approved. One is clinical trials to make [drugs] more efficient and successful, and then the last one is pre-clinical testing, before it’s been used on a human,” Gevaert says.
KIYATEC closed a $3 million Series B round last month, led by VentureSouth with participation from LabCorp, one of the largest clinical laboratory networks in the world. The funds are going toward the startup’s current clinical study to continue validating its technology and predictions.
“LabCorp is the kind of company that we’re really excited to have on board as an investor,” Gevaert says.