Vanderbilt Team Develops New Drug Synergy Algorithm for Melanoma & Lung Cancer

lung cancer

Heidi Hall writing for Vanderbilt reports that a cross-disciplinary team has developed a compelling new algorithm to predict drug interactions for cancer patients. Presently drug combinations for treatment of non-small-cell lung cancer (NSCLC) and melanoma are not optimal.  Moreover the only effective way oncologists can determine optimal combinations is via costly clinical trials.

That may change.  Thanks to the new Vanderbilt developed drug synergy algorithm, oncologists may be able to distinguish drug interactions leading to more efficient and effective ways of killing tumors from interactions that also may include fewer side effects. Ms. Hall reports that the team utilized the algorithm in 500,000 individual drug combination tests applied to live cancer cells.

The new algorithm, called MuSYC (Mult-dimensional Synergy of Combinations), can distinguish between potency and efficacy.  The work appeared recently in the Journal of Cell Systems. The team conducted 500,000 measurements of 12,000 drug combination conditions. An objective was to calculate the synergistic profile of 64 anti-cancer drugs in combination with standard of care osimertinib in NSCLC, which targets mutant EGFR.  Follow the link to learn more about the researchers grouping methodologies.

Lead Research/Investigator

Vito Quaranta