Population pharmacokinetics of trabectedin (ET-743) in subjects with cancer

2030

Background: Trabectedin (T) is a DNA minor-groove intercalating agent. The objective of this study is to characterize the population pharmacokinetics of T in cancer subjects. Methods: A total of 603 subjects (945 cycles) receiving intravenous T as monotherapy at doses ranging from 0.024 to 1.8 mg/m2 and given as 1, 3 or 24 hrs infusion every 21 days; 3 hrs infusion on day 1, 8, 15 every 28 days; or 1 hr infusion daily for 5 consecutive days every 21 days were included in the analysis. An open four-compartment pharmacokinetic model with linear elimination, linear and non-linear distribution to the deep and shallow peripheral compartments, respectively, and a catenary compartment off the shallow compartment was developed to best describe a total of 4251 concentrations from 274 subjects (Index Dataset) using NONMEM V. The effect of selected covariates on T pharmacokinetics was investigated. Model was evaluated using goodness of fit plots and relative error measurements for 2362 concentrations from 329 subjects (Test Dataset). Computer simulations were undertaken to evaluate the covariate effects on T pharmacokinetics. Results: Mean (SD) of T terminal half-life was ≈180 (61.4) h. Plasma accumulation was limited when T was given every three weeks. Systemic clearance, 31.5 L/h (CV = 51%), was 19.2% higher in subjects receiving concomitant dexamethasone. Typical values of volume of distribution at steady-state for males and females were 6070 L and 5240 L, respectively. Age, body size variables, AST, ALT, LDH, creatinine clearance, albumin, total protein and presence of liver metastases were not related to T pharmacokinetics. No difference in model parameters was observed for the infusion durations evaluated. T AUC and Cmax were dose proportional for each schedule evaluated and consistent across cancer types. Conclusions: The integration of phase I/II pharmacokinetic data demonstrated T linear elimination, dose-proportionality up to 1800 μg/m2, and time-independent pharmacokinetics. Given the moderate to large interindividual variability in T pharmacokinetics, the clinical relevance of dexamethasone and gender covariates is probably limited since a substantial overlap in simulated concentration-time profiles was observed.

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Comparison of a neural network approach with five traditional methods for predicting creatinine clearance in patients with human immunodeficiency virus infection

STUDY OBJECTIVE

To compare the results of an artificial neural network approach with those of five published creatinine clearance (Cl(cr)) prediction equations and with the measured (true) Cl(cr) in patients infected with the human immunodeficiency virus (HIV).

DESIGN

Six-month prospective study.

SETTINGS

Two university medical centers.

PATIENTS

Sixty-five HIV-infected patients: 18 relatively healthy outpatients and 47 inpatients.

INTERVENTIONS

All subjects had urine collected for 24 hours to determine Cl(cr).

MEASUREMENTS AND MAIN RESULTS

The 16 input variables were age, ideal body weight, actual body weight, body surface area, height, and the following blood chemistries: sodium, potassium, aspartate aminotransferase, alanine aminotransferase, red blood cell count, platelet count, white blood cell count, glucose, serum creatinine, blood urea nitrogen, and albumin. The only output variable was Cl(cr). A training set of 55 subjects was used to develop the relationship between input variables and the output variable. The trained neural network was then used to predict Cl(cr) of a validation set of 10 subjects. Mean differences between predicted Cl(cr) and actual Cl(cr) (bias) were 4.1, 28.7, 29.4, 26.0, 31.8, and 55.8 ml/min/1.73 m2 for the artificial neural network, Cockcroft and Gault, Jelliffe 1, Jelliffe 2, Mawer et al, and Hull et al methods, respectively.

CONCLUSION

The accuracy of predicting Cl(cr) in subjects with HIV infection by the artificial neural network is superior to that of the five equations that are currently used in clinical settings.