Sorafenib is metabolized by cytochrome P450 (CYP) 3A4 and UDP-glucuronosyltransferase (UGT) 1A9. It was reported that the genetic polymorphisms of UGT1A9 influence on the PK of sorafenib [1]. A population pharmacokinetic (PPK) analysis of sorafenib in 111 patients with solid tumor from five phase I and II clinical trials demonstrated that baseline bodyweight was a statically significant covariate for distribution volume, accumulating for 4 % of interindividual variability. In other PPK analyses, no clinically important PK covariates were identified in evaluating the possible effects of genetic polymorphisms of CYP3A4/5 and UGT 1A9 [2].

Early clinical trials showed that higher C _trough in sorafenib-treated patients were moderately predictive of prolonged progression-free survival (PFS). A weak relationship between C _trough and skin toxicity, as well as hand-foot skin reactions and hypertension, was also observed [3]. In a preliminary study in 58 patients with advanced or metastatic solid tumors treated with sorafenib, increased cumulated sorafenib exposure (AUC_cum) between day 0 and day 30 was independently associated with any grade ≥3 toxicity (P = 0.037). Additionally, the threshold AUC_cum value of 3161 mg·h/L was associated with the highest risk to develop any grade ≥3 toxicity (P = 0.018) [1].

Body size affects volume of distribution but not clearance for sunitinib in patients with RCC [4]. CYP3A4 metabolizes sunitinib to its active N-desethyl metabolites, SU12662, and subsequently into SU14335 and other inactive metabolites. Sunitinib is a substrate of the efflux transporters ATP-binding cassette transporter P-glycoprotein and the breast cancer-resistant protein encoded by the ABCB1 and ABCG2 genes, respectively. Genetic polymorphism of ABCG2 was identified as a significant covariate for the prediction of oral clearance (CL/F) of sunitinib by PPK analysis [5].

In a PK and PD meta-analysis, tentative relationships were identified between the following:

The frequency of the ABCG2 421 AA genotype, which developed severe toxicities due to high exposure of sunitinib and SU12662 [5], is higher in Asian populations (Japanese, 7 % [7]; Korean, 8 % [8]; and Chinese, 12 % [9]) than in non-Asian populations (Caucasian, 1.7 % and African, 0.2 % [9]). Thus, this racial difference in the frequency of the ABCG2 421 AA genotype could explain the higher frequency of grade 3 and 4 sunitinib-related toxicities in Asians [10, 11] than in non-Asians [12].

Axitinib is metabolized primarily by CYP 3A4/5 and to a lesser extent (<10 % each) by CYP1A2, CYP2C19, and UGT1A1. Axitinib is also a substrate for the drug transporters P-glycoprotein and OATP1B1 encoded by the ABCB1 and SLCO1B1 genes, respectively. Meta-analysis was performed using AUC_0-∞ data measured in 315 healthy subjects from 11 clinical pharmacology trials to examine potential influences of genetic polymorphisms in drug-metabolizing enzymes or transporters on axitinib pharmacokinetics. The results demonstrated no statistically significant associations between the specific genetic polymorphisms analyzed and axitinib plasma exposures and that none of them contributed >5 % to the overall pharmacokinetic variability of axitinib [13]. The lack of the pharmacogenetic effect of CYP2C19 and UGT1A1 on axitinib pharmacokinetic variability was also supported by the PPK analysis of axitinib in 337 healthy subjects from 10 phase I studies [14].

In a PPK analysis of 383 healthy volunteers, 181 patients with mRCC and 26 patients with other solid tumors in 17 trials, the median(range) for AUC at the end of 4 weeks (AUC _ss ) was 375 ng·h/mL (32.8–1728). The relationship between axitinib plasma exposure and the probability of response (i.e., 1.5-fold increase in the probability of achieving a partial response for every 100 ng·h/mL increase in AUC _ss ) in 168 metastatic RCC patients was demonstrated (P < 0.0001). Patients were stratified by having an AUC _ss greater or equal to axitinib total daily therapeutic exposure of 300 ng·h/mL (high AUC _ss ) or <300 ng·h/mL (low AUC _ss ). Median PFS in the high-AUC _ss group was significantly longer than median PFS in the low-AUC _ss group (13.8 months vs. 7.4 months, respectively; hazard ratio [HR] 0.558; P = 0.003). Similarly median OS of 37.4 months in the high-AUC _ss group was considerably longer than the 15.8 months in the low-AUC_ss group (HR 0.489; P < 0.001) shown in Table 16.2. These results indicated significant associations between AUC _ss and clinical responses for axitinib. When used as a continuous variable, the result was more significant than using a cut-off value of 300 ng·h/mL. For PFS and OS, the HR was 0.871 (P = 0.001) and 0.810 (P < 0.001) for every 100 ng·h/mL increase in AUC _ss , respectively (Table 16.2). In toxicity, a weak correlation between exposure and dBP (r ² value<0.10) was shown [15].