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This paper provides a fresh method, called Q-Rank, to predict the susceptibility of mobile lines to anti-cancer drugs. Q-Rank integrates different prediction formulas and identifies an appropriate algorithm for a given application. Q-Rank is based on reinforcement mastering solutions to position prediction formulas on such basis as relevant functions (e.g., omics characterization). The best-ranked algorithm is advised and used to anticipate