Several cancer treatments are shifting from traditional, time-limited, nonspecific cytotoxic chemotherapy cycles to continuous oral treatment with specific proteintargeted therapies. In this line, imatinib mesylate, a selective tyrosine kinases inhibitor (TKI), has excellent efficacy in the treatment of chronic myeloid leukemia. It has opened the way to the development of additional TKIs against chronic myeloid leukemia, including nilotinib and dasatinib. TKIs are prescribed for prolonged periods, often in patients with comorbidities. Therefore, they are regularly co-administered along with treatments at risk of drug-drug interactions. This aspect has been partially addressed so far, calling for a comprehensive review of the published data. We review here the available evidence and pharmacologic mechanisms of interactions between imatinib, dasatinib, and nilotinib and widely prescribed co-medications, including known inhibitors or inducers of cytochromes P450 or drug transporters. Information is mostly available for imatinib mesylate, well introduced in clinical practice. Several pharmacokinetic aspects yet remain insufficiently investigated for these drugs. Regular updates will be mandatory and so is the prospective reporting of unexpected clinical observations. (Blood. 2011;117(8):e75-e87)

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AIMTotal imatinib concentrations are currently measured for the therapeutic drug monitoring of imatinib, whereas only free drug equilibrates with cells for pharmacological action. Due to technical and cost limitations, routine measurement of free concentrations is generally not performed. In this study, free and total imatinib concentrations were measured to establish a model allowing the confident prediction of imatinib free concentrations based on total concentrations and plasma proteins measurements. METHODSOne hundred and fifty total and free plasma concentrations of imatinib were measured in 49 patients with gastrointestinal stromal tumours. A population pharmacokinetic model was built up to characterize mean total and free concentrations with inter-patient and intrapatient variability, while taking into account a1-acid glycoprotein (AGP) and human serum albumin (HSA) concentrations, in addition to other demographic and environmental covariates. RESULTSA one compartment model with first order absorption was used to characterize total and free imatinib concentrations. Only AGP influenced imatinib total clearance. Imatinib free concentrations were best predicted using a non-linear binding model to AGP, with a dissociation constant Kd of 319 ng ml -1 , assuming a 1:1 molar binding ratio. The addition of HSA in the equation did not improve the prediction of imatinib unbound concentrations. CONCLUSIONAlthough free concentration monitoring is probably more appropriate than total concentrations, it requires an additional ultrafiltration step and sensitive analytical technology, not always available in clinical laboratories. The model proposed might represent a convenient approach to estimate imatinib free concentrations. However, therapeutic ranges for free imatinib concentrations remain to be established before it enters into routine practice.