Moving towards dose individualization of tyrosine kinase inhibitors

Molecular targeted therapies with tyrosine kinase inhibitors (TKIs) have been a recent breakthrough in cancer treatment. These small molecules are mainly used at a fixed dose ignoring the possible need for dose individualization. Fixed dosing may indeed result in suboptimal treatment or excessive toxicity considering the high inter-individual variability in the pharmacokinetics (PK) of these therapies. The PK, toxicity and efficacy of ten commonly used molecular targeted anti-cancer therapies were reviewed in order to optimize their prescription. A wide interpatient variability in the pharmacokinetics of these small molecules is demonstrated. Moreover associations between certain toxicities and the treatment efficacy have also been demonstrated for some agents, such as erlotinib and skin rash, that may be used as a surrogate marker. Other biomarkers intended to substitute for a clinical endpoint have been described for some TKIs and may be useful for dose individualization. Promising alternatives to fixed dosing were explored such as therapeutic drug monitoring, genotype and phenotype adjusted dosing, and toxicity-adjusted dosing. Prospective studies are needed to validate these methods so that dosing algorithms may be developed in the near future in order to personalize therapeutics to the individual needs of each cancer patient. (C) 2010 Elsevier Ltd. All rights reserved

The impact of combining Selective Internal Radiation Therapy (SIRT) with sorafenib on overall survival in patients with advanced hepatocellular carcinoma: The SORAMIC trial palliative cohort

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Predictive Value of CYP3A and ABCB1 Phenotyping Probes for the Pharmacokinetics of Sunitinib: the ClearSun Study

The wide inter-patient variability in drug exposure partly explains the toxicity and efficacy profile of sunitinib treatment. In this prospective study cytochrome P450 (CYP) 3A and adenosine triphosphate binding cassette (ABC) B1 phenotypes were correlated to the pharmacokinetics of sunitinib and its active metabolite N-desethylsunitinib. A correlation analysis was performed between sunitinib pharmacokinetics and 1'OH-midazolam/midazolam ratio and parameters derived from technetium-99m-2-methoxy isobutyl isonitrile (Tc-99m-MIBI) scans, respectively. A population pharmacokinetic model using non-linear mixed-effects modeling software NONMEM was built, which included the phenotype tests as covariate. In 52 patients, the mean trough concentration of sunitinib plus metabolite increased from 21.4 ng/mL at day 1 of a cycle to 88.1 ng/mL in the fourth week of treatment. A trend for a correlation was observed between Tc-99m-MIBI elimination constant and trough concentrations of N-desethylsunitinib; however, this was not significant. Correlations were found between 1'OH-midazolam/midazolam ratio and sunitinib clearance (P = 0.008) and day 1 N-desethylsunitinib trough concentrations (P = 0.005), respectively. Moreover, patients suffering from grade 3 toxicities had significant lower clearance of sunitinib than patients without grade 3 toxicities (34.4 vs. 41.4 L/h; P = 0.025). Phenotype tests for ABCB1 and CYP3A4 did not explain inter-individual variability of sunitinib exposure sufficiently. However, the correlation between sunitinib clearance and the occurrence of severe toxicity suggests a direct exposure-toxicity relationship