A computational framework designed to personalize cancer treatment by matching individual tumors with drugs or drug combinations that are most likely to destroy them has been created by an international team including researchers at the Columbia University Irving Medical Center (CUIMC).
This proof-of-concept platform analyzed samples to first identify a new class of drug-targets that seldom are mutated in cancer patients, and then predict the drugs that can reverse their cancers.
The algorithm accurately predicted that the same drug would be effective in nearly half the patients.
"Using novel systems-biology methodologies, which combine the use of supercomputers with large-scale pharmacological assays, we can computationally predict and prioritize drugs and drug combinations that will most effectively kill cancer cells," says CUIMC's Andrea Califano.
From Columbia Systems Biology
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