This model predicted myelosuppression after administration of one of several different chemotherapeutic drugs. In addition, with fixed system-related parameters to proposed values, and only drug-related parameters estimated, myelosuppression can be predicted. We propose that this model can be a useful tool in the development of anticancer drugs and therapies.

Purpose: To retrospectively evaluate the effects of six known allelic variants in the CYP2C8, CYP3A4, CYP3A5, and ABCB1 genes on the pharmacokinetics of the anticancer agent paclitaxel (Taxol). Experimental Design: A cohort of 97 Caucasian patients with cancer (median age, 57 years) received paclitaxel as an i.v. infusion (dose range, 80-225 mg/m 2 ). Genomic DNA was analyzed using PCR RFLP or using Pyrosequencing. Pharmacokinetic variables for unbound paclitaxel were estimated using nonlinear mixed effect modeling. The effects of genotypes on typical value of clearance were evaluated with the likelihood ratio test within NONMEM. In addition, relations between genotype and individual pharmacokinetic variable estimates were evaluated with oneway ANOVA. Results: The allele frequencies for the CYP2C8*2, CYP2C8*3, CYP2C8*4, CYP3A4*3, CYP3A5*3C, and ABCB1 3435C>T variants were 0.7%, 9.2%, 2.1%, 0.5%, 93.2%, and 47.1%, respectively, and all were in Hardy-Weinberg equilibrium.The population typical value of clearance of unbound paclitaxel was 301L/h (individual clearance range, 83.7-1055 L/h). The CYP2C8 or CYP3A4/5 genotypes were not statistically significantly associated with unbound clearance of paclitaxel. Likewise, no statistically significant association was observed between the ABCB1 3435C>T variant and any of the studied pharmacokinetic variables. Conclusions: This study indicates that the presently evaluated variant alleles in the CYP2C8, CYP3A4, CYP3A5, and ABCB1 genes do not explain the substantial interindividual variability in paclitaxel pharmacokinetics.

Earlier PK models for paclitaxel have been empirical. This study shows that a mechanistic model can be used to describe the nonlinear PK of paclitaxel. There is an indication that the PK/PD relationship is not the same for unbound and total plasma concentrations.

Purpose: Cancer chemotherapy, although based on body surface area, often causes unpredictable myelosuppression, especially severe neutropenia. The aim of this study was to evaluate qualitatively and quantitatively the influence of patient-specific characteristics on the neutrophil concentration-time course, to identify patient subgroups, and to compare covariates on systemrelated pharmacodynamic variable between drugs. Experimental Design: Drug and neutrophil concentration, demographic, and clinical chemistry data of several trials with docetaxel (637 patients), paclitaxel (45 patients), etoposide (71 patients), or topotecan (191 patients) were included in the covariate analysis of a physiologybased pharmacokinetic-pharmacodynamic neutropenia model. Comparisons of covariate relations across drugs were made.Results: A population model incorporating four to five relevant patient factors for each drug to explain variability in the degree and duration of neutropenia has been developed. Sex, previous anticancer therapy, performance status, height, binding partners, or liver enzymes influenced system-related variables and a 1 -acid glycoprotein, albumin, bilirubin, concomitant cytotoxic agents, or administration route changed drug-specific variables. Overall, female and pretreated patients had a lower baseline neutrophil concentration. Across-drug comparison revealed that several covariates (e.g., age) had minor (clinically irrelevant) influences but consistently shifted the pharmacodynamic variable in the same direction. Conclusions: These mechanistic models, including patient characteristics that influence drugspecific parameters, form the rationale basis for more tailored dosing of individual patients or subgroups to minimize the risk of infection and thus might contribute to a more successful therapy. In addition, nonsignificant or clinically irrelevant relations on system-related parameters suggest that these covariates could be negligible in clinical trails and daily use.In cancer chemotherapy, despite dose adaptation to body surface area, the degree of interpatient variability in effects is large (1, 2). Some patients fail to respond, whereas others experience unacceptable toxicity (3). Myelosuppression is the most common, often dose-limiting toxicity. Neutropenia makes patients highly susceptible to pathogens resulting in lifethreatening infections or even death.Empirical pharmacodynamic models accounting for the entire concentration-time profile of neutrophils have been developed (4,5). Recently, also (semi-)mechanistic models (6, 7) and a physiology-based pharmacokinetic-pharmacodynamic model describing neutropenia for several drugs (8) have been introduced. Mechanistic models have the great advantage that estimated variables may be attributed and compared with physiologic values.The contribution of pharmacokinetic or pharmacodynamic variability to the variable clinical outcome has clearly been shown (9, 10). A more rational approach for optimal dosing is based on elucidating the sources of variabil...

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