New Metric May Better Assess Drug Potency, Efficacy

In vitro cell proliferation assays are used in pharmacology, molecular biology, and cancer drug development. Vanderbilt University researchers have discovered that this method used to test compounds for anticancer activity in cells may be flawed. The findings call into question specific methods that research scientists use to discover efficacy of new cancer therapies. This was first published May 2, 2016, in Nature Methods.

Because of the discovery that the methods may be flawed, Vito Quaranta, MD, director of the Quantitative Systems Biology Center at Vanderbilt and his team began looking for another method. Together, they have developed a new metric to evaluate a compound’s effect on cell proliferation - called the DIP (drug-induced proliferation) rate - that they believe overcomes the flawed bias in the traditional method.

“More than 90% of candidate cancer drugs fail in late-stage clinical trials, costing hundreds of millions of dollars,” said Quaranta. “The flawed in vitro drug discovery metric may not be the only responsible factor, but it may be worth pursuing an estimate of its impact.”

Using theoretical modeling and experimentation, the researchers demonstrated how current metrics of antiproliferative small molecule effect experience time-dependent bias, which can lead to inaccurate assessments of parameters such as drug potency and efficacy. The Vanderbilt team recommends using the drug-induced proliferation (DIP) rate, the slope of the line on a plot of cell population doublings versus time, as an alternative, time-independent metric.

Computational biologist Carlos Lopez, PhD, assistant professor of Cancer Biology and Dr. Quaranta’s team used a combination of experimentation and mathematical modeling to determine the time-dependent bias in static proliferation assays and to develop the time-independent DIP rate metric.

Darren Tyson, PhD, co-author of the Nature Methods article and research assistant professor of Cancer Biology, identified the problem of time with the way proliferation assays are currently being used and how they work. Proliferation assays measure cell number at a single time point, but don’t take into account the bias introduced by exponential cell proliferation, even in the presence of the drug, according to Dr. Tyson. He deduced this fact and created a new method along with Leonard Harris, PhD, a systems biology postdoctoral fellow and co-first author Peter Frick, PhD, a recent Vanderbilt graduate.

The findings are important in light of recent international efforts to generate data sets that include the responses of “thousands of cell lines to hundreds of compounds,” Dr. Quaranta said in a news release. The Cancer Cell Line Encyclopedia (CCLE) and Genomics of Drug Sensitivity in Cancer (GDSC) databases include drug response data along with genomic and proteomic data that detail each cell line’s molecular makeup. In effect, one cell line may react to a drug therapy in a different way than another cell line.

Getting down to the molecular level may improve cancer care down the road, and additional testing on this method will reveal more.