Ganciclovir Exposure under a 450 mg Daily Dosage of Valganciclovir for the Prevention of Cytomegalovirus Disease in Kidney Transplant Recipients.

Background: It is suggested that a low dose of valganciclovir can be equally effective than a standard dose for cytomegalovirus (CMV) prophylaxis after kidney transplantation. The aim of our study was to determine the ganciclovir exposure observed under a routine daily dosage of 450 mg valganciclovir in kidney transplant recipients with a wide range of renal function. Methods: In this prospective study, kidney transplant recipients with a GFR MDRD above 25 mL/min at risk for CMV (donor or recipient seropositive for CMV) received a dose of valganciclovir (450 mg daily) prophylaxis for 3 months. Ganciclovir levels at trough (Ctrough) and at peak (C3h) were measured monthly. Ganciclovir exposure (AUC0-24) was estimated using Bayesian non-linear mixed-effect modelling (NONMEM) and compared between 3 groups of patients according to their kidney function: GFRMDRD 26-39 mL/min (Group 1), GFRMDRD 40-59 mL/min (Group 2) and GFRMDRD 60-90 mL/min (Group 3). CMV DNAemia was assessed during and after prophylaxis using PCR. Results: Thirty-six patients received 450 mg daily of valganciclovir for 3 months. Median ganciclovir C3h was 3.9 mg/L (range: 1.3-7.1) and Ctrough was 0.4 mg/L (range 0.1-2.7). Median (range) AUC0-24 of ganciclovir was 59.3 mg.h/L (39.0-85.3) in Group 1 patients, 35.8 mg.h/L (24.9-55.8) in Group 2 patients and 29.6 mg.h/L (22.0- 43.2) in Group 3 patients (p<0.001). Anemia was more common in Group 1 patients compared to patients on the other groups (p=0.01). No differences in other adverse events according to ganciclovir exposure were observed. CMV DNAemia was not detected during prophylaxis. After discontinuing prophylaxis, CMV DNAemia was seen in 8/34 patients (23.5%) and 4/36 patients (11%) developed CMV disease. Conclusion: A routine dosage of valganciclovir achieved plasma levels of ganciclovir in patients with GFR>60 mL/min similar to those previously reported using oral ganciclovir. A daily dose of 450 mg valganciclovir appears to be acceptable for CMV prophylaxis in most kidney transplant recipients.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.

Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.

Techniques for CT and MR, post-processing, radiation

Brain perfusion can be assessed by CT and MR. For CT, two major techniques are used. First, Xenon CT is an equilibrium technique based on a freely diffusible tracer. First pass of iodinated contrast injected intravenously is a second method, more widely available. Both methods are proven to be robust and quantitative, thanks to the linear relationship between contrast concentration and x-ray attenuation. For the CT methods, concern regarding x-ray doses delivered to the patients need to be addressed. MR is also able to assess brain perfusion using the first pass of gadolinium based contrast agent injected intravenously. This method has to be considered as a semi-quantitative because of the non linear relationship between contrast concentration and MR signal changes. Arterial spin labeling is another MR method assessing brain perfusion without injection of contrast. In such case, the blood flow in the carotids is magnetically labelled by an external radiofrequency pulse and observed during its first pass through the brain. Each of this various CT and MR techniques have advantages and limits that will be illustrated and summarized.Learning Objectives:1. To understand and compare the different techniques for brain perfusion imaging.2. To learn about the methods of acquisition and post-processing of brain perfusion by first pass of contrast agent for CT and MR.3. To learn about non contrast MR methods (arterial spin labelling).

Population pharmacokinetics of imatinib in CML and GIST patients under long-term treatment

Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumour (GIST). However, the treatment must be taken indefinitely and is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P glycoprotein (product of the MDR1 gene), and is also bound to the alpha1-acid glycoprotein (AAG) in plasma. Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualisation. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations were measured in 59 patients receiving Glivec® at diverse dosage regimens, using a validated chromatographic method developed for this study. The results were analysed by non-linear mixed effect modelling (NONMEM). A one-compartment model with first-order absorption described the data appropriately, with an average apparent clearance of 12.4 l/h, a volume of distribution of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. The MDR1 polymorphism 3435C>T and the AAG phenotype appears to modulate the disposition of imatinib. Large inter-individual variability (CV %) remained unexplained by the demographic covariates considered, both on clearance (40%) and distribution volume (71%). Together with intra-patient variability (34%), this translates into an 8-fold width of the 90%-prediction interval of plasma concentrations expected under a fixed dosing regimen. This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring programme for imatinib. It may help in individualising the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.

Identification of pharmaceutical tablets by Raman spectroscopy and chemometrics

Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.

Population pharmacokinetic study of gentamicin in a large cohort of premature and term neonates.

AIM: This study aims to investigate the clinical and demographic factors influencing gentamicin pharmacokinetics in a large cohort of unselected premature and term newborns and to evaluate optimal regimens in this population. METHODS: All gentamicin concentration data, along with clinical and demographic characteristics, were retrieved from medical charts in a Neonatal Intensive Care Unit over 5 years within the frame of a routine therapeutic drug monitoring programme. Data were described using non-linear mixed-effects regression analysis ( nonmem®). RESULTS: A total of 3039 gentamicin concentrations collected in 994 preterm and 455 term newborns were included in the analysis. A two compartment model best characterized gentamicin disposition. The average parameter estimates, for a median body weight of 2170 g, were clearance (CL) 0.089 l h(-1) (CV 28%), central volume of distribution (Vc ) 0.908 l (CV 18%), intercompartmental clearance (Q) 0.157 l h(-1) and peripheral volume of distribution (Vp ) 0.560 l. Body weight, gestational age and post-natal age positively influenced CL. Dopamine co-administration had a significant negative effect on CL, whereas the influence of indomethacin and furosemide was not significant. Both body weight and gestational age significantly influenced Vc . Model-based simulations confirmed that, compared with term neonates, preterm infants need higher doses, superior to 4 mg kg(-1) , at extended intervals to achieve adequate concentrations. CONCLUSIONS: This observational study conducted in a large cohort of newborns confirms the importance of body weight and gestational age for dosage adjustment. The model will serve to set up dosing recommendations and elaborate a Bayesian tool for dosage individualization based on concentration monitoring.

Ganciclovir exposure under a 450mg daily dosage of valganciclovir for cytomegalovirus prevention in kidney transplantation: a prospective study.

Manuel O, Pascual M, Perrottet N, Lamoth F, Venetz J-P, Decosterd LA, Buclin T, Meylan PR. Ganciclovir exposure under a 450 mg daily dosage of valganciclovir for cytomegalovirus prevention in kidney transplantation: a prospective study. 
Clin Transplant 2010: 24: 794-800. Abstract:  This prospective study aimed at determining the ganciclovir exposure observed under a daily dosage of 450 mg valganciclovir routinely applied to kidney transplant recipients with a GFR above 25 mL/min at risk for cytomegalovirus (CMV) disease. Ganciclovir levels at trough (C(trough) ) and at peak (C(3 h) ) were measured monthly. Ganciclovir exposure (area under the curve [AUC(0-24) ]) was estimated using Bayesian non-linear mixed-effect modeling (NONMEM). Thirty-six patients received 450 mg of valganciclovir daily for three months. Median ganciclovir C(3 h) was 3.9 mg/L (range: 1.3-7.1), and C(trough) was 0.4 mg/L (range 0.1-2.7). Median AUC(0-24) of ganciclovir was 59.3 mg h/L (39.0-85.3) in patients with GFR(MDRD) 26-39 mL/min, 35.8 mg h/L (24.9-55.8) in patients with GFR(MDRD) 40-59 mL/min, and 29.6 mg h/L (22.0-43.2) in patients with GFR(MDRD)  ≥ 60 mL/min. No major differences in adverse events according to ganciclovir exposure were observed. CMV viremia was not detected during prophylaxis. After discontinuing prophylaxis, CMV viremia was seen in 8/36 patients (22%), and 4/36 patients (11%) developed CMV disease. Ganciclovir exposure after administration of valganciclovir 450 mg daily in recipients with GFR ≥60 mL/min was comparable to those previously reported with oral ganciclovir. A routine daily dose of 450 mg valganciclovir appears to be acceptable for CMV prophylaxis in most kidney transplant recipients.

Imatinib plasma concentrations variability in oncologic patients

Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukemia (CML) and gastrointestinal stromal tumor (GIST). However, the treatment must be taken indefinitely, it is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P-glycoprotein (product of the MDR1 gene). Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualization. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations, taken at various sampling times after the latest dose, were measured in 59 patients receiving Glivec at diverse regimens, using a validated HPLC-UV method developed for this study. The results were analyzed by non-linear mixed effect modeling (NONMEM). A one-compartment model with first-order absorption appeared appropriate to describe the data, with an average apparent clearance of 12.4 l/h, a distribution volume of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. At present, only the MDR1 polymorphism has been assessed and seems to affect the pharmacokinetic parameters of imatinib. Large inter-individual variability remained unexplained by the demographic covariates considered, both on clearance (40 %) and distribution volume (71 %). Together with intra-patient variability (34 %), this translates into an 8-fold width of the 90 %-prediction interval of plasma concentrations expected under a fixed dosing regimen. This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring program for imatinib. It may help to individualize the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.

Population pharmacokinetics of imatinib in CML and GIST patients under long-term treatment

Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukaemia (CML) and gastro-intestinal stromal tumour (GIST). However, the treatment must be taken indefinitely, it is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occur in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P glycoprotein (product of the MDR1 gene). Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualisation. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations, taken at various sampling times after latest dose, were measured in 59 patients receiving Glivec® at diverse regimens, using a validated chromatographic method (HPLC-UV) developed for this study. The results were analysed by non-linear mixed effect modelling (NONMEM). A one- compartment model with first-order absorption appeared appropriate to describe the data, with an average apparent clearance of 12.4 l/h, a distribution volume of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. The MDR1 polymorphism 3435C>T appears to affect the disposition of imatinib. Large inter-individual variability remained unexplained by the demographic covariates considered, both on clearance (40%) and distribution volume (71%). Together with intra-patient variability (34%), this translates into an 8-fold width of the 90%-prediction interval of plasma concentrations expected under a fixed dosing regimen ! This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring programme for imatinib. It may help to individualise the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.

Self-potential investigations of a gravel bar in a restored river corridor

Self-potentials (SP) are sensitive to water fluxes and concentration gradients in both saturated and unsaturated geological media, but quantitative interpretations of SP field data may often be hindered by the superposition of different source contributions and time-varying electrode potentials. Self-potential mapping and close to two months of SP monitoring on a gravel bar were performed to investigate the origins of SP signals at a restored river section of the Thur River in northeastern Switzerland. The SP mapping and subsequent inversion of the data indicate that the SP sources are mainly located in the upper few meters in regions of soil cover rather than bare gravel. Wavelet analyses of the time-series indicate a strong, but non-linear influence of water table and water content variations, as well as rainfall intensity on the recorded SP signals. Modeling of the SP response with respect to an increase in the water table elevation and precipitation indicate that the distribution of soil properties in the vadose zone has a very strong influence. We conclude that the observed SP responses on the gravel bar are more complicated than previously proposed semi-empiric relationships between SP signals and hydraulic head or the thickness of the vadose zone. We suggest that future SP monitoring in restored river corridors should either focus on quantifying vadose zone processes by installing vertical profiles of closely spaced SP electrodes or by installing the electrodes within the river to avoid signals arising from vadose zone processes and time-varying electrochemical conditions in the vicinity of the electrodes.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

BME-based uncertainty assessment of the Chernobyl fallout

The vast territories that have been radioactively contaminated during the 1986 Chernobyl accident provide a substantial data set of radioactive monitoring data, which can be used for the verification and testing of the different spatial estimation (prediction) methods involved in risk assessment studies. Using the Chernobyl data set for such a purpose is motivated by its heterogeneous spatial structure (the data are characterized by large-scale correlations, short-scale variability, spotty features, etc.). The present work is concerned with the application of the Bayesian Maximum Entropy (BME) method to estimate the extent and the magnitude of the radioactive soil contamination by 137Cs due to the Chernobyl fallout. The powerful BME method allows rigorous incorporation of a wide variety of knowledge bases into the spatial estimation procedure leading to informative contamination maps. Exact measurements (?hard? data) are combined with secondary information on local uncertainties (treated as ?soft? data) to generate science-based uncertainty assessment of soil contamination estimates at unsampled locations. BME describes uncertainty in terms of the posterior probability distributions generated across space, whereas no assumption about the underlying distribution is made and non-linear estimators are automatically incorporated. Traditional estimation variances based on the assumption of an underlying Gaussian distribution (analogous, e.g., to the kriging variance) can be derived as a special case of the BME uncertainty analysis. The BME estimates obtained using hard and soft data are compared with the BME estimates obtained using only hard data. The comparison involves both the accuracy of the estimation maps using the exact data and the assessment of the associated uncertainty using repeated measurements. Furthermore, a comparison of the spatial estimation accuracy obtained by the two methods was carried out using a validation data set of hard data. Finally, a separate uncertainty analysis was conducted that evaluated the ability of the posterior probabilities to reproduce the distribution of the raw repeated measurements available in certain populated sites. The analysis provides an illustration of the improvement in mapping accuracy obtained by adding soft data to the existing hard data and, in general, demonstrates that the BME method performs well both in terms of estimation accuracy as well as in terms estimation error assessment, which are both useful features for the Chernobyl fallout study.

Cytogenetic response to imatinib in chronic myeloid leukaemia patients: concentration dependency and associated influences under field-conditions

Introduction: Imatinib, a first-line drug for chronic myeloid leukaemia (CML), has been increasingly proposed for therapeutic drug monitoring (TDM), as trough concentrations >=1000 ng/ml (Cmin) have been associated with improved molecular and complete cytogenetic response (CCyR). The pharmacological monitoring project of EUTOS (European Treatment and Outcome Study) was launched to validate retrospectively the correlation between Cmin and response in a large population of patients followed by central TDM in Bordeaux.¦Methods: 1898 CML patients with first TDM 0-9 years after imatinib initiation, providing cytogenetic data along with demographic and comedication (37%) information, were included. Individual Cmin, estimated by non-linear regression (NONMEM), was adjusted to initial standard dose (400 mg/day) and stratified at 1000 ng/ml. Kaplan-Meier estimates of overall cumulative CCyR rates (stratified by sex, age, comedication and Cmin) were compared using asymptotic logrank k-sample test for interval-censored data. Differences in Cmin were assessed by Wilcoxon test.¦Results: There were no significant differences in overall cumulative CCyR rates between Cmin strata, sex and comedication with P-glycoprotein inhibitors/inducers or CYP3A4 inhibitors (p >0.05). Lower rates were observed in 113 young patients <30 years (p = 0.037; 1-year rates: 43% vs 60% in older patients), as well as in 29 patients with CYP3A4 inducers (p = 0.001, 1-year rates: 40% vs 66% without). Higher rates were observed in 108 patients on organic-cation-transporter-1 (hOCT-1) inhibitors (p = 0.034, 1-year rates: 83% vs 56% without). Considering 1-year CCyR rates, a trend towards better response for Cmin above 1000 ng/ml was observed: 64% (95%CI: 60-69%) vs 59% (95%CI: 56-61%). Median Cmin (400 mg/day) was significantly reduced in male patients (732 vs 899ng/ml, p <0.001), young patients <30 years (734 vs 802 ng/ml, p = 0.037) and under CYP3A4 inducers (758 vs 859 ng/ml, p = 0.022). Under hOCT-1 inhibitors, Cmin was increased (939 vs 827 ng/ml, p = 0.038).¦Conclusion: Based on observational TDM data, the impact of imatinib Cmin >1000 ng/ml on CCyR was not salient. Young CML patients (<30 years) and patients taking CYP3A4 inducers probably need close monitoring and possibly higher imatinib doses, due to lower Cmin along with lower CCyR rates. Patients taking hOCT-1 inhibitors seem in contrast to have improved CCyR response rates. The precise role for imatinib TDM remains to be established prospectively.