determine if the same mutations would be selected and to assess how these mutations contribute to multiple-regression models of tipranavir-related phenotype and of virologic response. A tipranavir mutation score was developed from these analyses, which consisted of a unique string of 16 protease positions and 21 mutations (10V, 13V, 20M/R/V, 33F, 35G, 36I, 43T, 46L, 47V, 54A/M/V, 58E, 69K, 74P, 82L/T, 83D, and 84V). HIV-1 isolates displaying an increasing number of these tipranavir resistance-associated mutations had a reduced phenotypic susceptibility and virologic response to tipranavir. Regression models for predicting virologic response in phase III trials revealed that each point in the tipranavir score was associated with a 0.16-log 10 copies/ml-lower virologic response to tipranavir at week 24 of treatment. A lower number of points in the tipranavir score and a greater number of active drugs in the background regimen were predictive of virologic success. These analyses demonstrate that the tipranavir mutation score is a potentially valuable tool for predicting the virologic response to tipranavir in protease inhibitor-experienced patients.