Population pharmacokinetics of doxorubicin and doxorubicinol in patients diagnosed with non-Hodgkin's lymphoma.

AIMS: The aims of the study were: (i) to characterize the pharmacokinetics (PK) of doxorubicin (DOX) and doxorubicinol (DOXol) in patients diagnosed with non-Hodgkin's lymphoma (NHL) using a population approach; (ii) to evaluate the influence of various covariates on the PK of DOX; and (iii) to evaluate the role of DOX and DOXol exposure in haematological toxicity. METHODS: Population PK modelling (using NONMEM) was performed using DOX and DOXol plasma concentration-time data from 45 NHL patients treated with R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone). The influence of drug exposure on haematological toxicity was analysed using the Mann-Whitney-Wilcoxon test. RESULTS: A five-compartment model, three for DOX and two for DOXol, with first-order distribution and elimination for both entities best described the data. Population estimates for parent drug (CL) and metabolite (CLm ) clearance were 62 l h-1 and 27 l h-1 , respectively. The fraction metabolized to DOXol (Fm ) was estimated at 0.22. While bilirubin and aspartate aminotransferase showed an influence on the CL and CLm , the objective function value decrease was not statistically significant. A trend towards an association between the total area under the concentration-time curve (AUCtotal ), the area under the concentration-time curve for DOX (AUC) plus the area under the concentration-time curve for DOXol (AUCm ), and the neutropenia grade (P = 0.068) and the neutrophil counts (P = 0.089) was observed, according to an exponential relationship. CONCLUSIONS: The PK of DOX and DOXol were well characterized by the model developed, which could be used as a helpful tool to optimize the dosage of this drug. The results suggest that the main active metabolite of DOX, DOXol, is involved in the haematological toxicity of the parent drug.

Validation and clinical evaluation of a UHPLC method with fluorescence detector for plasma quantification of doxorubicin and doxorubicinol in haematological patients.

A rapid and simple UHPLC-fluorescence detection method for the quantification of doxorubicin and its main metabolite, doxorubicinol, in human plasma has been developed. The method was also validated for its application in therapeutic drug monitoring, a clinical approach used in the optimization of oncologic treatments. Following a single protein precipitation step, chromatographic separation was achieved using a C18 column (50mm×2.10mm, particle size 1.7µm) at 50°C with a mobile phase consisting of water (containing 0.4% triethylamine and 0.4% orthophosphoric acid)/acetonitrile (77:23, v/v). Flow rate was 0.50mL/min and fluorescence detection with an excitation wavelength of 470nm and an emission wavelength of 548nm was used. The method met the specifications of linearity, selectivity, sensitivity, accuracy, precision and stability of the FDA and EMA guidelines for the validation of bioanalytical methods. Linearity for the drug (8-3000ng/mL) and the metabolite (3-150ng/mL) was observed (R(2)>0.992) and the maximum intra-day and inter-day precision coefficients of variation were less than 14% for both. The lower limits of quantification were 8 and 3ng/mL for doxorubicin and doxorubicinol, respectively. The method was successfully applied to the quantify plasma concentrations of doxorubicin and doxorubicinol in 33 patients diagnosed with haematological malignancies in which broad ranges for drug (8.3-2766.0ng/mL) and metabolite (4.8-104.9ng/mL) levels were measured adequately.

The convergence of therapeutic drug monitoring and pharmacogenetic testing to optimize efavirenz therapy.

The aim of this study was to show the benefits of combining therapeutic drug monitoring (TDM) and pharmacogenetic analyses to optimize efavirenz (EFV) therapy. Patients were selected to minimize nongenetic differences between patients: 32 HIV adherent patients without drug interactions treated with an EFV nonindividualized dose over at least 1 year and included in a TDM program were genotyped according to minimum steady-state concentrations (C ss min). The EFV plasma concentrations (n = 158) were quantified by high-performance liquid chromatography-ultraviolet, and genetic polymorphisms were analyzed using the PHARMAchip. Central nervous system side effects were assessed systematically. Genetic polymorphisms were detected in 79.2% of patients with EFV Css min outside the therapeutic range (1-4 mg/L), showing the high diagnostic efficacy of combining TDM with pharmacogenetic testing. CYP2B6 (516 G>T) polymorphisms were associated with a significant decrease in EFV plasma clearance in 80% of the poor metabolizer patients (G/T, T/T). All homozygous patients had C ss min greater than 4 mg/L, 75% of them showing central nervous system side effects. For such patients, pharmacogenetic testing with TDM could be advantageous because the polymorphism is a determinant of these circumstances and TDM would allow reductions in dose to be specified without assuming an equal dose for any given genotype. In fact, poor metabolizer patients required less than a 600 mg standard starting dose, implying that if CYP2B6 screening were available, EFV therapy could be started at 400 mg and later TDM-individualized. The results of this study clarify the genotype versus phenotype debate for optimizing drug therapy. Pharmacogenetic testing together with TDM links genotype to phenotypic differences in drug concentrations and adverse events, providing additional support for dosage adjustment and a more efficient use of both approaches. As genotype screens become cheaper, and in combination with TDM, adjusting dosages in the light of genetic polymorphisms will become a reality.

Vancomycin dosing assessment in intensive care unit patients based on a population pharmacokinetic/pharmacodynamic simulation.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT * Despite the frequent use of vancomycin in intensive care unit (ICU) patients, few studies aimed at characterizing vancomycin population pharmacokinetics have been performed in this critical population. * Population pharmacokinetics coupled with pharmacodynamic analysis, in order to optimize drug exposure and hence antibacterial effectiveness, has been little applied in these specific patients. WHAT THIS STUDY ADDS * Our population model characterized the pharmacokinetic profile of vancomycin in adult ICU patients, higher distribution volume values (V) being observed when the patient's serum creatinine (Cr(Se)) was greater than 1 mg dl(-1). * Age and creatinine clearance (CL(cr)) were identified as the main covariates explaining the pharmacokinetic variability in vancomycin CL. * Our pharmacokinetic/pharmacodynamic (PK/PD) simulation should aid clinicians to select initial vancomycin doses that will maximize the rate of response in the ICU setting, taking into account the patient's age and renal function as well as the susceptibility of Staphylococcus aureus. AIM To estimate the vancomycin pharmacokinetic profile in adult ICU patients and to assess vancomycin dosages for increasing the likelihood of optimal exposure. METHODS Five hundred and sixty-nine concentration-time data from 191 patients were analysed using a population pharmacokinetic approach (NONMEN). External model evaluation was made in 46 additional patients. The 24 h area under the concentration-time curve (AUC(0,24 h)) was derived from the final model. Minimum inhibitory concentration (MIC) values for S. aureus were obtained from the EUCAST database. AUC(0,24 h) : MIC >/= 400 was considered as PK/PD efficacy index. The probability of different dosages attaining the target considering different strains of S. aureus and patient subgroups was estimated with Monte Carlo simulation. RESULTS Vancomycin CL showed a significant dependence on patient age and renal function whereas Cr(Se) > 1 mg dl(-1) increased V more than twofold. For our representative ICU patient, 61 years, 73 kg, Cr(Se)= 1.4 mg dl(-1), measured CL(Cr)= 74.7 ml min(-1), the estimated values were CL = 1.06 ml min(-1) kg(-1) and V= 2.04 l kg(-1). The cumulative fraction of response for a standard vancomycin dose (2 g day(-1)) was less than 25% for VISA strains, and 33% to 95% for susceptible S. aureus, depending on patient characteristics. CONCLUSIONS Simulations provide useful information regarding the initial assessment of vancomycin dosing, the conventional dosing regimen probably being suboptimal in adult ICU patients. A graphic approach provides the recommended dose for any selected probability of attaining the PK/PD efficacy target or to evaluate the cumulative fraction of response for any dosing regimen in this population.

Evaluation of population pharmacokinetic models for amikacin dosage individualization in critically ill patients.

OBJECTIVES: The aim of this study was to evaluate the reliability for dosage individualization and Bayesian adaptive control of several literature-retrieved amikacin population pharmacokinetic models in patients who were critically ill. METHODS: Four population pharmacokinetic models, three of them customized for critically-ill patients, were applied using pharmacokinetic software to fifty-one adult patients on conventional amikacin therapy admitted to the intensive care unit. An estimation of patient-specific pharmacokinetic parameters for each model was obtained by retrospective analysis of the amikacin serum concentrations measured (n = 162) and different clinical covariates. The model performance for a priori estimation of the area under the serum concentration-time curve (AUC) and maximum serum drug concentration (C(max)) targets was obtained. KEY FINDINGS: Our results provided valuable confirmation of the clinical importance of the choice of population pharmacokinetic models when selecting amikacin dosages for patients who are critically ill. Significant differences in model performance were especially evident when only information concerning clinical covariates was used for dosage individualization and over the two most critical determinants of clinical efficacy of amikacin i.e. the AUC and C(max) values. CONCLUSIONS: Only a single amikacin serum level seemed necessary to diminish the influence of population model on dosage individualization.

Vancomycin dosage optimization in patients with malignant haematological disease by pharmacokinetic/pharmacodynamic analysis.

BACKGROUND: The use of vancomycin against Staphylococcus aureus is currently debated because of the increasing resistance developed by this pathogen. Nevertheless, antibacterial effectiveness is a limited resource that must be protected and restored. Novel dosage strategies based on pharmacokinetic/pharmacodynamic analyses are needed to retain effectiveness that could improve drug exposure in patients infected with such pathogens. OBJECTIVE: The aim of this study was to assess whether standard or higher vancomycin dosages are required to increase the probability of attaining a target pharmacokinetic/pharmacodynamic index for several staphylococcal strains and thus to estimate the minimum vancomycin daily dose related to a high probability of effective treatment in patients with malignant haematological disease. METHODS: Monte Carlo simulation was performed to calculate the cumulative fraction of response (CFR) for different vancomycin daily dosages, using a population pharmacokinetic model previously defined in patients with malignant haematological disease and the minimum inhibitory concentration (MIC) distribution for vancomycin against several staphylococcal species (vancomycin-susceptible S. aureus and vancomycin-intermediate S. aureus [VISA], S. epidermidis, S. haemolyticus and coagulase-negative Staphylococcus [CNS] species) obtained from the European Committee on Antimicrobial Susceptibility Testing (EUCAST) in order to predict the dose that would achieve the pharmacokinetic/pharmacodynamic index value associated with efficacy (the area under the concentration-time curve from 0 to 24 hours divided by the MIC [AUC(24)/MIC >/=400]). RESULTS: CFR values showed dependence on the renal function of the patient and the causative pathogen. Only in patients with a creatinine clearance (CL(CR)) <60 mL/min did the standard vancomycin dosage (2000 mg/day) induce CFRs >60% for all staphylococci, except the VISA strains. CFRs for S. aureus of 90.6%, 47.3% and 31.2% for CL(CR) values of <60, 60-120 and >120 mL/min, respectively, were obtained, whereas for the VISA strains, the corresponding values were only 14.0%, 0.3% and 0%. The impact of potential pathogens on CFRs is also significant. According to our pharmacokinetic/pharmacodynamic analysis, in patients with normal renal function (CL(CR) between 60 and 120 mL/min) vancomycin 2000 mg/day leads to a risk of not achieving the recommended AUC(24)/MIC breakpoint of 52.7%, 70.4%, 74.9% and 80.3% for S. aureus, S. haemolyticus, CNS and S. epidermidis, respectively. Application of our results to clinical practice graphically allows us to obtain the recommended dose for any a priori-selected probability of attaining the AUC(24)/MIC ratio of >/=400 and to evaluate the CFRs for any dosing regimen used in this population group, depending on the patients' renal function. CONCLUSIONS: Application of pharmacokinetic/pharmacodynamic analysis based on Monte Carlo simulation offers an excellent tool for selecting the therapeutic option with the highest probability of clinical success in patients with malignant haematological disease. Thus, for vancomycin-susceptible S. aureus, if a CFR >/=80 is assumed as clinically acceptable, vancomycin doses of 1500, 3000 and 4000 mg/day for a CL(CR) of <60, 60-120 and >120 mL/min, respectively, will be required.

Population pharmacokinetic analysis of vancomycin in patients with hematological malignancies.

This study determines vancomycin (VAN) population pharmacokinetics (PK) in adult patients with hematological malignancies. VAN serum concentration data (n = 1,004) from therapeutic drug monitoring were collected retrospectively from 215 patients. A one-compartment PK model was selected. VAN pharmacokinetics population parameters were generated using the NONMEM program. A graphic approach and stepwise generalized additive modeling were used to elucidate the preliminary relationships between PK parameters and clinical covariates analyzed. Covariate selection revealed that total body weight (TBW) affected V, whereas renal function, estimated by creatinine clearance, and a diagnosis of acute myeloblastic leukemia (AML) influenced VAN clearance. We propose one general and two AML-specific models. The former was defined by CL (liters/h) = 1.08 x CL(CR(Cockcroft and Gault)) (liters/h); CV(CL) = 28.16% and V (liters) = 0.98 x TBW; CV(V) =37.15%. AML models confirmed this structure but with a higher clearance coefficient (1.17). The a priori performance of the models was evaluated in another 59 patients, and clinical suitability was confirmed. The models were fairly accurate, with more than 33% of the measured concentrations being within +/-20% of the predicted value. This therapeutic precision is twofold higher than that of a non-customized population model (16.1%). The corresponding standardized prediction errors included zero and a standard deviation close to unity. The models could be used to estimate appropriate VAN dosage guidelines, which are not clearly defined for this high-risk population. Their simple structure should allow easy implementation in clinical software and application in dosage individualization using the Bayesian approach.

Immunosuppressive therapy for paediatric transplant patients: pharmacokinetic considerations.

Immunosuppressive therapy in paediatric transplant recipients is changing as a consequence of the increasing number of available immunosuppressive agents. Generic and other new formulations are now emerging onto the market, clinical experience is growing, and it is expected that clinicians should tailor immunosuppressive protocols to individual patients by optimising dosages and drugs according to the maturation and clinical status of the child. Most information about the clinical pharmacokinetics of immunosuppressive drugs in paediatrics is centred on cyclosporin, tacrolimus and mycophenolate mofetil in renal and liver transplant recipients; data regarding other immunosuppressants and transplant types are limited. Although the clinical pharmacokinetics of these drugs in paediatric transplant recipients are still under investigation, it is evident that the pharmacokinetic parameters observed in adults may not be applicable to children, especially in younger age groups. In general, patients younger than 5 years old show higher clearance rates irrespective of the organ transplanted or drug used. Another important factor that frequently affects clearance in this patient population is the post-transplant time. In accordance with these findings, and in contrast with the usual under-dosage in children, the need for higher dosages in younger recipients and during the early post-transplant period seems evident. To achieve the best compromise between prevention of rejection and toxicity, dosage individualisation is required and this can be achieved through therapeutic drug monitoring (TDM). This approach is particularly useful to ensure the cost-effective management of paediatric transplant recipients in whom the pharmacokinetic behaviour, target concentrations for clinical use and optimal dosage strategies of a particular drug may not yet be well defined. Although TDM may be a tool for improving immunosuppressive therapy, there is little information concerning its positive contribution to clinical events, including outcomes, for paediatric patients. Substantial information to support the use of TDM exists for cyclosporin and, to a lesser extent, for tacrolimus, but a diversity of options affects their implementation in the clinical setting. The role of TDM in therapy with mycophenolate mofetil and sirolimus has yet to be defined regarding both methods and clinical indications. Pharmacodynamic monitoring appears more suited to other immunosuppressants such as azathioprine, corticosteroids and monoclonal or polyclonal antibodies. If coupled with pharmacokinetic measurements, such monitoring would allow earlier and more precise optimisation of therapy. Very few population pharmacokinetic studies have been carried out in paediatric transplant patients. This type of study is needed so that techniques such as Bayesian forecasting can be applied to optimise immunosuppressive therapy in paediatric transplant patients.