961 resultados para Drug-monitoring


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The micellar electrokinetic capillary chromatography (MEKC) separation and analysis of voriconazole and UK 115794 (internal standard) were examined and an assay for determination of voriconazole in human plasma and serum was developed. The MEKC medium comprises a 2:15 (v/v) mixture of methanol and a pH 9.3 buffer composed of 5mM Na(2)B(4)O(7), 7 mM Na(2)HPO(4) and 54 mM SDS. Sample preparation is based upon liquid/liquid extraction with ethylacetate and dichloromethane (75%/25%) at physiological pH. Using this approach with 250 microl serum or plasma and reconstitution of the dried extract into 100 microl of a buffer composed of 0.5mM Na(2)B(4)O(7) and 0.7 mM Na(2)HPO(4) (pH 9.3), the detection and quantitation limits were determined to be 0.1 and 0.2 microg/ml, respectively, a sensitivity that is suitable for therapeutic drug monitoring of voriconazole (provisional therapeutic range: 1-6 microg/ml) in human plasma and serum samples. The method was validated and compared to an HPLC method, showing excellent agreement between the two for a set of 91 samples that stemmed from patients being treated with voriconazole. The MEKC assay is also demonstrated to be suitable to explore pharmacokinetic data of voriconazole.

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The aim of this study was to identify the mechanisms of hypocarnitinemia in patients treated with valproate.

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BACKGROUND AND OBJECTIVE: Protease inhibitors are highly bound to orosomucoid (ORM) (alpha1-acid glycoprotein), an acute-phase plasma protein encoded by 2 polymorphic genes, which may modulate their disposition. Our objective was to determine the influence of ORM concentration and phenotype on indinavir, lopinavir, and nelfinavir apparent clearance (CL(app)) and cellular accumulation. Efavirenz, mainly bound to albumin, was included as a control drug. METHODS: Plasma and cells samples were collected from 434 human immunodeficiency virus-infected patients. Total plasma and cellular drug concentrations and ORM concentrations and phenotypes were determined. RESULTS: Indinavir CL(app) was strongly influenced by ORM concentration (n = 36) (r2 = 0.47 [P = .00004]), particularly in the presence of ritonavir (r2 = 0.54 [P = .004]). Lopinavir CL(app) was weakly influenced by ORM concentration (n = 81) (r2 = 0.18 [P = .0001]). For both drugs, the ORM1 S variant concentration mainly explained this influence (r2 = 0.55 [P = .00004] and r2 = 0.23 [P = .0002], respectively). Indinavir CL(app) was significantly higher in F1F1 individuals than in F1S and SS patients (41.3, 23.4, and 10.3 L/h [P = .0004] without ritonavir and 21.1, 13.2, and 10.1 L/h [P = .05] with ritonavir, respectively). Lopinavir cellular exposure was not influenced by ORM abundance and phenotype. Finally, ORM concentration or phenotype did not influence nelfinavir (n = 153) or efavirenz (n = 198) pharmacokinetics. CONCLUSION: ORM concentration and phenotype modulate indinavir pharmacokinetics and, to a lesser extent, lopinavir pharmacokinetics but without influencing their cellular exposure. This confounding influence of ORM should be taken into account for appropriate interpretation of therapeutic drug monitoring results. Further studies are needed to investigate whether the measure of unbound drug plasma concentration gives more meaningful information than total drug concentration for indinavir and lopinavir.

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Total plasma concentrations are currently measured for therapeutic drug monitoring of HIV protease inhibitors (PIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs). However, the pharmacological target of antiretroviral drugs reside inside cells. To study the variability of their cellular accumulation, and to determine to which extent total plasma concentrations (TPC) correlate with cellular concentrations (CC), plasma and peripheral blood mononuclear cells (PBMCs) were simultaneously collected at single random times after drug intake from 133 HIV infected patients. TPC levels were analysed by high-performance liquid chromatography with ultraviolet detection and CC by LC-MS/MS from peripheral blood mononuclear cells. The best correlations between TPC and CC were observed for nelfinavir (NFV, slope=0.93, r=0.85), saquinavir (SQV, slope=0.76, r=0.80) and lopinavir (LPV, slope=0.87, r=0.63). By contrast, TPC of efavirenz (EFV) exhibited a moderate correlation with CC (slope=0.69, r=0.58), while no correlation was found for nevirapine (NVP, slope=-0.3, r=0.1). Interindividual variability in the CC/TPC ratio was lower for protease inhibitors (coefficients of variation 76%, 61%, and 80% for SQV, NFV and LPV, respectively) than for nonnucleoside reverse transcriptase inhibitors (coefficients of variation 101% and 318%, for EFV and NVP). As routine CC measurement raises practical difficulties, well-correlated plasma concentrations (ie, NFV, SQV and LPV) can probably be considered as appropriate surrogates for cellular drug exposure. For drugs such as EFV or NVP, there may be room for therapeutic drug monitoring improvement using either direct CC determination or other predictive factors such as genotyping of transporters or metabolizing enzyme genes.

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Because of the large variability in the pharmacokinetics of anti-HIV drugs, therapeutic drug monitoring in patients may contribute to optimize the overall efficacy and safety of antiretroviral therapy. An LC–MS/MS method for the simultaneous assay in plasma of the novel antiretroviral agents rilpivirine (RPV) and elvitegravir (EVG) has been developed to that endeavor. Plasma samples (100 μL) extraction is performed by protein precipitation with acetonitrile, and the supernatant is subsequently diluted 1:1 with 20-mM ammonium acetate/MeOH 50:50. After reverse-phase chromatography, quantification of RPV and EVG, using matrix-matched calibration samples, is performed by electrospray ionization–triple quadrupole mass spectrometry by selected reaction monitoring detection using the positive mode. The stable isotopic-labeled compounds RPV-13C6 and EVG-D6 were used as internal standards. The method was validated according to FDA recommendations, including assessment of extraction yield, matrix effects variability (<6.4%), as well as EVG and RPV short and long-term stability in plasma. Calibration curves were validated over the clinically relevant concentrations ranging from 5 to 2500 ng/ml for RPV and from 50 to 5000 ng/ml for EVG. The method is precise (inter-day CV%: 3–6.3%) and accurate (3.8–7.2%). Plasma samples were found to be stable (<15%) in all considered conditions (RT/48 h, +4°C/48 h, −20°C/3 months and 60°C/1 h). Selected metabolite profiles analysis in patients' samples revealed the presence of EVG glucuronide, that was well separated from parent EVG, allowing to exclude potential interferences through the in-source dissociation of glucuronide to parent drug. This new, rapid and robust LCMS/MS assay for the simultaneous quantification of plasma concentrations of these two major new anti-HIV drugs EVG and RPV offers an efficient analytical tool for clinical pharmacokinetics studies and routine therapeutic drug monitoring service.

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BACKGROUND After heart transplantation (HTx), the interindividual pharmacokinetic variability of immunosuppressive drugs represents a major therapeutic challenge due to the narrow therapeutic window between over-immunosuppression causing toxicity and under-immunosuppression leading to graft rejection. Although genetic polymorphisms have been shown to influence pharmacokinetics of immunosuppressants, data in the context of HTx are scarce. We thus assessed the role of genetic variation in CYP3A4, CYP3A5, POR, NR1I2, and ABCB1 acting jointly in immunosuppressive drug pathways in tacrolimus (TAC) and ciclosporin (CSA) dose requirement in HTx recipients. METHODS Associations between 7 functional genetic variants and blood dose-adjusted trough (C0) concentrations of TAC and CSA at 1, 3, 6, and 12 months after HTx were evaluated in cohorts of 52 and 45 patients, respectively. RESULTS Compared with CYP3A5 nonexpressors (*3/*3 genotype), CYP3A5 expressors (*1/*3 or *1/*1 genotype) required around 2.2- to 2.6-fold higher daily TAC doses to reach the targeted C0 concentration at all studied time points (P ≤ 0.003). Additionally, the POR*28 variant carriers showed higher dose-adjusted TAC-C0 concentrations at all time points resulting in significant differences at 3 (P = 0.025) and 6 months (P = 0.047) after HTx. No significant associations were observed between the genetic variants and the CSA dose requirement. CONCLUSIONS The CYP3A5*3 variant has a major influence on the required TAC dose in HTx recipients, whereas the POR*28 may additionally contribute to the observed variability. These results support the importance of genetic markers in TAC dose optimization after HTx.

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BACKGROUND Ribavirin (RBV) is an essential component of most current hepatitis C (HCV) treatment regimens and still standard of care in the combination with pegylated interferon (pegIFN) to treat chronic HCV in resource limited settings. Study results in HIV/HCV-coinfected patients are contradicting as to whether RBV concentration correlates with sustained virological response (SVR). METHODS We included 262 HCV treatment naïve HIV/HCV-coinfected Swiss HIV Cohort Study (SHCS) participants treated with RBV and pegIFN between 01.01.2001-01.01.2010, 134 with HCV genotype (GT) 1/4, and 128 with GT 2/3 infections. RBV levels were measured retrospectively in stored plasma samples obtained between HCV treatment week 4 and end of therapy. Uni- and multivariable logistic regression analyses were used to evaluate the association between RBV concentration and SVR in GT 1/4 and GT 2/3 infections. The analyses were repeated stratified by treatment phase (week 4-12, 13-24, >24) and IL28B genotype (CC versus CT/TT). RESULTS SVR rates were 35.1% in GT 1/4 and 70.3% in GT 2/3 infections. Overall, median RBV concentration was 2.0 mg/L in GT 1/4, and 1.9 mg/L in GT 2/3, and did not change significantly across treatment phases. Patients with SVR had similar RBV concentrations compared to patients without SVR in both HCV genotype groups. SVR was not associated with RBV levels ≥2.0 mg/L (GT 1/4, OR 1.19 [0.5-2.86]; GT 2/3, 1.94 [0.78-4.80]) and ≥2.5 mg/L (GT 1/4, 1.56 [0.64-3.84]; GT 2/3 2.72 [0.85-8.73]), regardless of treatment phase, and IL28B genotype. CONCLUSION In HIV/HCV-coinfected patients treated with pegIFN/RBV, therapeutic drug monitoring of RBV concentrations does not enhance the chance of HCV cure, regardless of HCV genotype, treatment phase and IL28B genotype.

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OBJECTIVE To systematically review evidence on genetic variants influencing outcomes during warfarin therapy and provide practice recommendations addressing the key questions: (1) Should genetic testing be performed in patients with an indication for warfarin therapy to improve achievement of stable anticoagulation and reduce adverse effects? (2) Are there subgroups of patients who may benefit more from genetic testing compared with others? (3) How should patients with an indication for warfarin therapy be managed based on their genetic test results? METHODS A systematic literature search was performed for VKORC1 and CYP2C9 and their association with warfarin therapy. Evidence was critically appraised, and clinical practice recommendations were developed based on expert group consensus. RESULTS Testing of VKORC1 (-1639G>A), CYP2C9*2, and CYP2C9*3 should be considered for all patients, including pediatric patients, within the first 2 weeks of therapy or after a bleeding event. Testing for CYP2C9*5, *6, *8, or *11 and CYP4F2 (V433M) is currently not recommended. Testing should also be considered for all patients who are at increased risk of bleeding complications, who consistently show out-of-range international normalized ratios, or suffer adverse events while receiving warfarin. Genotyping results should be interpreted using a pharmacogenetic dosing algorithm to estimate the required dose. SIGNIFICANCE This review provides the latest update on genetic markers for warfarin therapy, clinical practice recommendations as a basis for informed decision making regarding the use of genotype-guided dosing in patients with an indication for warfarin therapy, and identifies knowledge gaps to guide future research.

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Currently no pharmacogenomics-based criteria exist to guide clinicians in identifying individuals who are at risk of hearing loss from cisplatin-based chemotherapy. This review summarizes findings from pharmacogenomic studies that report genetic polymorphisms associated with cisplatin-induced hearing loss and aims to (1) provide up-to-date information on new developments in the field; (2) provide recommendations for the use of pharmacogenetic testing in the prevention, assessment and management of cisplatin-induced hearing loss in children and adults; and (3) identify knowledge gaps to direct and prioritize future research. These practice recommendations for pharmacogenetic testing in the context of cisplatin-induced hearing loss reflect a review and evaluation of recent literature and are designed to assist clinicians in providing optimal clinical care for patients receiving cisplatin based chemotherapy.

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A lamotrigina (LTG) é um fármaco pertencente à classe das feniltriazinas utilizado no tratamento de crises epilépticas generalizadas e focais e no tratamento adjunto da epilepsia refratária. Devido à alta variabilidade interindividual, às interações medicamentosas e aos efeitos adversos apresentados durante a administração da LTG, a monitorização terapêutica nos pacientes que fazem uso deste fármaco é necessária para ajuste de dose individual e evitar os efeitos adversos. Assim, o objetivo deste trabalho foi a avaliação de duas técnicas de microextração: a microextração em fase líquida com fibras ocas (HF-LPME) e a microextração líquido-líquido dispersiva (DLLME) para análise da lamotrigina em amostras de plasma de pacientes epilépticos. Primeiramente foram definidas as condições eletroforéticas: foi utilizado um capilar de sílica fundida de 75 ?m de diâmetro interno e 50 cm de comprimento efetivo. O eletrólito de corrida (BGE) foi composto por ácido 2-morfolinoetanosulfônico (MES), na concentração de 130 mmol L-1 e pH 5,0. As análises foram realizadas à temperatura de 20°C e tensão de 15 kV. A amostra foi injetada hidrodinamicamente (0,5 psi por 10 s) e a detecção foi feita em 214 nm. Nestas condições a LTG e o padrão interno (PI), lidocaína, puderam ser analisados em menos de 7 minutos. A HF-LPME foi avaliada no modo de 3 fases, usando 500 ?L de plasma e 3,5 mL de solução fosfato de sódio 50 mmol L-1 pH 9,0 como fase doadora. O solvente utilizado para impregnar a fibra foi o 1-octanol. Como fase aceptora foram utilizados 60 ?L de solução de ácido clorídrico pH 4,0. Para avaliação da DLLME, foi necessária uma etapa de pré-tratamento da amostra (500 ?L de plasma) com 1 mL de acetonitrila. Após isto, 1,3 mL do sobrenadante foram adicionados a 4 mL de solução fosfato de sódio 50 mmol L-1 pH 9,0 e 120 ?L de clorofórmio (solvente extrator) foram injetados nesta amostra aquosa e 165 ?L de fase sedimentada foram recuperados. As características de desempenho analítico para ambos os métodos foram avaliadas, sendo obtida linearidade na faixa de concentração plasmática de 1-20 ?g/mL e limite inferior de quantificação (LIQ) de 1 ?g mL-1. Os ensaios de precisão e exatidão apresentaram valores de acordo com os guias oficiais. Além disso, os métodos foram seletivos, não apresentaram efeito residual e as amostras foram estáveis. Os valores de recuperação foram de 54,3 e 23% para HF-LPME e DLLME, respectivamente. Os métodos validados foram aplicados com sucesso em amostras de plasma de pacientes epilépticos em tratamento com a LTG. Além disso, as duas técnicas foram comparadas e a HF-LPME apresentou vantagens em relação à DLLME, mostrando ser uma técnica promissora para análise de matrizes complexas, com reduzido consumo de solvente orgânico e possibilidade de automação.

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Objective: To identify factors influencing the prescribing of medicines by general practitioners in rural and remote Australia. Design: A qualitative study using a questionnaire to determine attitudes about prescribing, specific prescribing habits and comments on prescribing in ‘rural practice’. Setting: General practice in rural and remote Queensland. Subjects: General practitioners practising in rural and remote settings in Queensland (n = 258). Main outcome measures: The factors perceived to influence the prescribing of medicines by medical practitioners in rural environments. Results: A 58% response rate (n = 142) was achieved. Most respondents agreed that they prescribe differently in rural compared with city practice. The majority of respondents agreed that their prescribing was influenced by practice location, isolation of patient home location, limited diagnostic testing and increased drug monitoring. Location issues and other issues were more likely to be identified as ‘influential’ by the more isolated practitioners. Factors such as access to continuing medical education and specialists were confirmed as having an influence on prescribing. The prescribing of recently marketed drugs was more likely by doctors practising in less remote rural areas. Conclusion: Practising in rural and remote locations is perceived to have an effect on prescribing. These influences need to be considered when developing quality use of medicines policies and initiatives for these locations. What is already known: Anecdotal and audit based studies have shown that rural general practice differs to urban-based practice in Australia, including some limited data showing some variations in prescribing patterns. No substantiated explanations for these variations have been offered. It is known that interventions to change prescribing behaviour are more likely to be effective if they are perceived as relevant and hence increasing our knowledge of rural doctors’ perceptions of differences in rural practice prescribing is required. What this study adds: Rural doctors believed that they prescribe differently in rural compared with city practice and they described a range of influences. The more remotely located doctors were more likely to report the ‘rural’ influences on prescribing, however, most results failed to reach statistical significance when compared to the less remotely located doctors. These perceptions should be considered when developing medicines policy and education for rural medical practitioners to ensure it is perceived rurally relevant.

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The aim of this review is to analyse critically the recent literature on the clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplant recipients. Dosage and target concentration recommendations for tacrolimus vary from centre to centre, and large pharmacokinetic variability makes it difficult to predict what concentration will be achieved with a particular dose or dosage change. Therapeutic ranges have not been based on statistical approaches. The majority of pharmacokinetic studies have involved intense blood sampling in small homogeneous groups in the immediate post-transplant period. Most have used nonspecific immunoassays and provide little information on pharmacokinetic variability. Demographic investigations seeking correlations between pharmacokinetic parameters and patient factors have generally looked at one covariate at a time and have involved small patient numbers. Factors reported to influence the pharmacokinetics of tacrolimus include the patient group studied, hepatic dysfunction, hepatitis C status, time after transplantation, patient age, donor liver characteristics, recipient race, haematocrit and albumin concentrations, diurnal rhythm, food administration, corticosteroid dosage, diarrhoea and cytochrome P450 (CYP) isoenzyme and P-glycoprotein expression. Population analyses are adding to our understanding of the pharmacokinetics of tacrolimus, but such investigations are still in their infancy. A significant proportion of model variability remains unexplained. Population modelling and Bayesian forecasting may be improved if CYP isoenzymes and/or P-glycoprotein expression could be considered as covariates. Reports have been conflicting as to whether low tacrolimus trough concentrations are related to rejection. Several studies have demonstrated a correlation between high trough concentrations and toxicity, particularly nephrotoxicity. The best predictor of pharmacological effect may be drug concentrations in the transplanted organ itself. Researchers have started to question current reliance on trough measurement during therapeutic drug monitoring, with instances of toxicity and rejection occurring when trough concentrations are within 'acceptable' ranges. The correlation between blood concentration and drug exposure can be improved by use of non-trough timepoints. However, controversy exists as to whether this will provide any great benefit, given the added complexity in monitoring. Investigators are now attempting to quantify the pharmacological effects of tacrolimus on immune cells through assays that measure in vivo calcineurin inhibition and markers of immuno suppression such as cytokine concentration. To date, no studies have correlated pharmacodynamic marker assay results with immunosuppressive efficacy, as determined by allograft outcome, or investigated the relationship between calcineurin inhibition and drug adverse effects. Little is known about the magnitude of the pharmacodynamic variability of tacrolimus.

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The current approach for therapeutic drug monitoring in renal transplant recipients receiving mycophenolate mofetil (MMF) is measurement of total mycophenolic acid (MPA) concentration. Because MPA is highly bound, during hypoalbuminemia the total concentration no longer reflects the free (pharmacologically active) concentration. The authors investigated what degree of hypoalbuminemia causes a significant change in protein binding and thus percentage free MPA. Forty-two renal transplant recipients were recruited for the study. Free and total concentrations of MPA (predose, and 1, 3, and 6 hours post-MMF dose samples) and plasma albumin concentrations were determined on day 5 posttransplantation. Six-hour area under the concentration-time curve (AUC(0-6)) values were calculated for free and total MPA, and percentage free MPA was determined for each patient. The authors found a significant relationship between low albumin concentrations and increased percentage free MPA (Spearman correlation = -0.54, P < 0.0001). Receiver operating characteristic (ROC) curve analysis was performed on the albumin versus percentage free MPA data. The cutoff value of albumin determined from the ROC analysis that differentiated normal from elevated percentage free MPA (defined as greater than or equal to3%) in this patient population was 31 g/L. At this cutoff value albumin was found to be a good predictor of altered free MPA percentage, with a sensitivity and specificity of 0.75 and 0.80, respectively, and an area under the ROC curve of 0.79. To rationalize MMF dosing regimens in hypoalbuminemic patients (plasma albumin less than or equal to 31 g/L), clinicians should consider monitoring the free MPA concentration.

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The role of the therapeutic drug monitoring laboratory in support of immunosuppressant drug therapy is well established, and the introduction of sirolimus (SRL) is a new direction in this field. The lack of an immunoassay for several years has restricted the availability of SRL assay services. The recent availability of a CEDIA (R) SRL assay has the potential to improve this situation. The present communication has compared the CEDIA (R) SRL method with 2 established chromatographic methods, HPLC-UV and HPLC-MS/MS. The CEDIA (R) method, run on a Hitachi 917 analyzer, showed acceptable validation criteria with within-assay precision of 9.1% and 3.3%, and bias of 17.1% and 5.8%, at SRL concentrations of 5.0 mu g/L and 20 mu g/L, respectively. The corresponding between-run precision values were 11.5% and 3.3% and bias of 7.1% and 2.9% at 5.0 mu g/L and 20 mu g/L, respectively, The lower limit of quantification was found to be 3.0 mu g/L. A series of 96 EDTA whole-blood samples predominantly from renal transplant recipients were assayed by the 3 methods for comparison. It was found that the CEDIA (R) method showed a Deming regression line of CEDIA = 1.20 X HPLC-MS/MS - 0.07 (r = 0.934, SEE = 1.47), with a mean bias of 20.4%. Serial blood samples from 8 patients included in this evaluation showed that the CEDIA (R) method reflected the clinical fluctuations in the chromatographic methods, albeit with the variable bias noted. The CEDIA (R) method on the H917 analyzer is therefore a useful adjunct to SRL dosage individualization in renal transplant recipients.