Limited sampling models for doxorubicin pharmacokinetics

Although doxorubicin is one of the most commonly used antineoplastics, no studies to date have clearly related the area under the concentration-time curve (AUC) to toxicity or response. The limited sampling model has recently been shown to be a feasible method for estimating the AUC to facilitate pharmacodynamic studies. Data from two previous studies of doxorubicin pharmacokinetics were used, including 26 patients with sarcoma and five patients with breast cancer or unknown primary. The former were divided into a training data set of 15 patients and a test datum set of 11 patients, and the latter patients formed a second test data set. The model was developed by stepwise multiple regression on the training data set: AUC (nanogram hour per milliliter) = 17.39 C2 + 163 C48-111.0 [dose/(50 mg/m2)], where C2 and C48 are the concentrations at 2 and 48 hours after bolus dose. The model was subsequently validated on both test data sets: first test data set--mean predictive error (MPE), 4.7%; root mean square error (RMSE), 12.4%; second test data set--MPE, 4.5%, RMSE, 9.2%. An additional model was also generated using a simulated time point to estimate the total AUC for a daily x 3-day schedule: AUC (nanogram hour per milliliter) = 44.79 C2 + 175.65 C48 + 47.25 [dose/(25 mg/m2/d)], where the C48 is obtained just prior to the third dose. We conclude that the AUC of doxorubicin after bolus administration can be adequately estimated from two timed plasma concentrations.