990 resultados para Drug-monitoring


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Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).

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Therapeutic drug monitoring (TDM) and pharmacogenetic tests play a major role in minimising adverse drug reactions and enhancing optimal therapeutic response. The response to medication varies greatly between individuals, according to genetic constitution, age, sex, co-morbidities, environmental factors including diet and lifestyle (e.g. smoking and alcohol intake), and drug-related factors such as pharmacokinetic or pharmacodynamic drug-drug interactions. Most adverse drug reactions are type A reactions, i.e. plasma-level dependent, and represent one of the major causes of hospitalisation, in some cases leading to death. However, they may be avoidable to some extent if pharmacokinetic and pharmacogenetic factors are taken into consideration. This article provides a review of the literature and describes how to apply and interpret TDM and certain pharmacogenetic tests and is illustrated by case reports. An algorithm on the use of TDM and pharmacogenetic tests to help characterise adverse drug reactions is also presented. Although, in the scientific community, differences in drug response are increasingly recognised, there is an urgent need to translate this knowledge into clinical recommendations. Databases on drug-drug interactions and the impact of pharmacogenetic polymorphisms and adverse drug reaction information systems will be helpful to guide clinicians in individualised treatment choices.

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Therapeutic drug monitoring (TDM), i. e., the quantification of serum or plasma concentrations of medications for dose optimization, has proven a valuable tool for the patient-matched psychopharmacotherapy. Uncertain drug adherence, suboptimal tolerability, non-response at therapeutic doses, or pharmacokinetic drug-drug interactions are typical situations when measurement of medication concentrations is helpful. Patient populations that may predominantly benefit from TDM in psychiatry are children, pregnant women, elderly patients, individuals with intelligence disabilities, forensic patients, patients with known or suspected genetically determined pharmacokinetic abnormalities or individuals with pharmacokinetically relevant comorbidities. However, the potential benefits of TDM for optimization of pharmacotherapy can only be obtained if the method is adequately integrated into the clinical treatment process. To promote an appropriate use of TDM, the TDM expert group of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) issued guidelines for TDM in psychiatry in 2004. Since then, knowledge has advanced significantly, and new psychopharmacologic agents have been introduced that are also candidates for TDM. Therefore the TDM consensus guidelines were updated and extended to 128 neuropsychiatric drugs. 4 levels of recommendation for using TDM were defined ranging from "strongly recommended" to "potentially useful". Evidence-based "therapeutic reference ranges" and "dose related reference ranges" were elaborated after an extensive literature search and a structured internal review process. A "laboratory alert level" was introduced, i. e., a plasma level at or above which the laboratory should immediately inform the treating physician. Supportive information such as cytochrome P450 substrate and inhibitor properties of medications, normal ranges of ratios of concentrations of drug metabolite to parent drug and recommendations for the interpretative services are given. Recommendations when to combine TDM with pharmacogenetic tests are also provided. Following the guidelines will help to improve the outcomes of psychopharmacotherapy of many patients especially in case of pharmacokinetic problems. Thereby, one should never forget that TDM is an interdisciplinary task that sometimes requires the respectful discussion of apparently discrepant data so that, ultimately, the patient can profit from such a joint eff ort.

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Rapport de synthèse1. Partie de laboratoireCette première étude décrit le développement et la validation, selon les standards internationaux, de deux techniques de mesure des concentrations sanguines de voriconazole, un nouvel agent antifongique à large spectre: 1) la chromatographic en phase liquide à haute pression et 2) le bio-essai utilisant une souche mutante de Candida hypersensible au voriconazole. Ce travail a aussi permis de mettre en évidence une importante et imprévisible variabilité inter- et intra-individuelle des concentrations sanguines de voriconazole malgré l'utilisation des doses recommandées par le fabriquant. Ce travail a été publié dans un journal avec "peer-review": "Variability of voriconazole plasma levels measured by new high- performance liquid chromatography and bioassay methods" by A. Pascual, V. Nieth, T. Calandra, J. Bille, S. Bolay, L.A. Decosterd, T. Buclin, P.A. Majcherczyk, D. Sanglard, 0. Marchetti. Antimicrobial Agents Chemotherapy, 2007; 51:137-432. Partie CliniqueCette deuxième étude a évalué de façon prospective l'impact clinique des concentrations sanguines de voriconazole sur l'efficacité et sécurité thérapeutique chez des patients atteints d'infections fongiques. Des concentrations sanguines élevées étaient significativement associés à la survenue d'une toxicité neurologique (encéphalopathie avec confusion, hallucinations et myoclonies) et des concentrations sanguines basses à une réponse insuffisante au traitement antifongique (persistance ou progression des signes cliniques et radiologiques de l'infection). Dans la majorité des cas, un ajustement de la dose de voriconazole, sur la base des concentrations mesurées, a abouti à une récupération neurologique complète ou à une résolution de l'infection, respectivement. Ce travail a été publié dans un journal avec "peer-review": " Voriconazole Therapeutic Drug Monitoring in Patients with Invasive Mycoses Improves Efficacy and Safety Outcomes" by A. Pascual, T. Calandra, S. Bolay, T. Buclin, J. Bille, and O. Marchetti. Clinical Infectious Diseases, 2008 January 15; 46(2): 201-11.Ces deux études, financées de façon conjointe par un "grant" international de la Société suisse d'infectiologie et la Société internationale de maladies infectieuses et par la Fondation pour le progrès en microbiologie médicale et maladies infectieuses (FAMMID, Lausanne), ont été réalisées au sein du Service des Maladies Infectieuses, Département de Médecine, au CHUV, en étroite collaboration avec la Division de Pharmacologie Clinique, Département de Médecine, au CHUV et l'Institut de Microbiologie du CHUV et de l'Université de Lausanne.

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Therapeutic drug monitoring (TDM), i. e., the quantification of serum or plasma concentrations of medications for dose optimization, has proven a valuable tool for the patient-matched psychopharmacotherapy. Uncertain drug adherence, suboptimal tolerability, non-response at therapeutic doses, or pharmacokinetic drug-drug interactions are typical situations when measurement of medication concentrations is helpful. Patient populations that may predominantly benefit from TDM in psychiatry are children, pregnant women, elderly patients, individuals with intelligence disabilities, forensic patients, patients with known or suspected genetically determined pharmacokinetic abnormalities or individuals with pharmacokinetically relevant comorbidities. However, the potential benefits of TDM for optimization of pharmacotherapy can only be obtained if the method is adequately integrated into the clinical treatment process. To promote an appropriate use of TDM, the TDM expert group of the Arbeitsgemeinschaft für Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) issued guidelines for TDM in psychiatry in 2004. Since then, knowledge has advanced significantly, and new psychopharmacologic agents have been introduced that are also candidates for TDM. Therefore the TDM consensus guidelines were updated and extended to 128 neuropsychiatric drugs. 4 levels of recommendation for using TDM were defined ranging from "strongly recommended" to "potentially useful". Evidence-based "therapeutic reference ranges" and "dose related reference ranges" were elaborated after an extensive literature search and a structured internal review process. A "laboratory alert level" was introduced, i. e., a plasma level at or above which the laboratory should immediately inform the treating physician. Supportive information such as cytochrome P450 substrate- and inhibitor properties of medications, normal ranges of ratios of concentrations of drug metabolite to parent drug and recommendations for the interpretative services are given. Recommendations when to combine TDM with pharmacogenetic tests are also provided. Following the guidelines will help to improve the outcomes of psychopharmacotherapy of many patients especially in case of pharmacokinetic problems. Thereby, one should never forget that TDM is an interdisciplinary task that sometimes requires the respectful discussion of apparently discrepant data so that, ultimately, the patient can profit from such a joint effort.

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In October 2011 the Task Force Therapeutic Drug Monitoring of the Association for Neuropsychopharmacology and Pharmacopsychiatry (AGNP) published an update (Pharmacopsychiatry 2011, 44: 195-235) of the first version of the consensus paper on therapeutic drug monitoring (TDM) published in 2004. This article summarizes the essential statements to make them accessible to a wider readership in German speaking countries.

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Five selective serotonin reuptake inhibitors (SSRIs) have been introduced recently: citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline. Although no therapeutic window has been defined for SSRIs, in contrast to tricyclic antidepressants, analytical methods for therapeutic drug monitoring of SSRIs are useful in several instances. SSRIs differ widely in their chemical structure and in their metabolism. The fact that some of them have N-demethylated metabolites, which are also SSRIs, requires that methods be available which allow therapeutic drug monitoring of the parent compounds and of these active metabolites. most procedures are based on prepurification of the SSRIs by liquid-liquid extraction before they are submitted to separation by chromatographic procedures (high-performance liquid chromatography, gas chromatography, thin layer chromatography) and detection by various detectors (UV, fluorescence, electrochemical detector, nitrogen-phosphorus detector, mass spectrometry). This literature review shows that most methods allow quantitative determination of SSRIs in plasma, in the lower ng/ml range, and that they are, therefore, suitable for therapeutic drug monitoring purposes of this category of drugs.

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Background: As imatinib pharmacokinetics are highly variable, plasma levels differ largely between patients under the same dosage. Retrospective studies in chronic myeloid leukemia (CML) patients showed significant correlations between low levels and suboptimal response, and between high levels and poor tolerability. Monitoring of plasma levels is thus increasingly advised, targeting trough concentrations of 1000 μg/L and above. Objectives: Our study was launched to assess the clinical usefulness of systematic imatinib TDM in CML patients. The present preliminary evaluation questions the appropriateness of dosage adjustment following plasma level measurement to reach the recommended trough level, while allowing an interval of 4-24 h after last drug intake for blood sampling. Methods: Initial blood samples from the first 9 patients in the intervention arm were obtained 4-25 h after last dose. Trough levels in 7 patients were predicted to be significantly away from the target (6 <750 μg/L, and 1 >1500 μg/L with poor tolerance), based on a Bayesian approach using a population pharmacokinetic model. Individual dosage adjustments were taken up in 5 patients, who had a control measurement 1-4 weeks after dosage change. Predicted trough levels were confronted to anterior model-based extrapolations. Results: Before dosage adjustment, observed concentrations extrapolated at trough ranged from 359 to 1832 μg/L (median 710; mean 804, CV 53%) in the 9 patients. After dosage adjustment they were expected to target between 720 and 1090 μg/L (median 878; mean 872, CV 13%). Observed levels of the 5 recheck measurements extrapolated at trough actually ranged from 710 to 1069 μg/L (median 1015; mean 950, CV 16%) and had absolute differences of 21 to 241 μg/L to the model-based predictions (median 175; mean 157, CV 52%). Differences between observed and predicted trough levels were larger when intervals between last drug intake and sampling were very short (~4 h). Conclusion: These preliminary results suggest that TDM of imatinib using a Bayesian interpretation is able to bring trough levels closer to 1000 μg/L (with CV decreasing from 53% to 16%). While this may simplify blood collection in daily practice, as samples do not have to be drawn exactly at trough, the largest possible interval to last drug intake yet remains preferable. This encourages the evaluation of the clinical benefit of a routine TDM intervention in CML patients, which the randomized Swiss I-COME study aims to.

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PURPOSE: Adequate empirical antibiotic dose selection for critically ill burn patients is difficult due to extreme variability in drug pharmacokinetics. Therapeutic drug monitoring (TDM) may aid antibiotic prescription and implementation of initial empirical antimicrobial dosage recommendations. This study evaluated how gradual TDM introduction altered empirical dosages of meropenem and imipenem/cilastatin in our burn ICU. METHODS: Imipenem/cilastatin and meropenem use and daily empirical dosage at a five-bed burn ICU were analyzed retrospectively. Data for all burn admissions between 2001 and 2011 were extracted from the hospital's computerized information system. For each patient receiving a carbapenem, episodes of infection were reviewed and scored according to predefined criteria. Carbapenem trough serum levels were characterized. Prior to May 2007, TDM was available only by special request. Real-time carbapenem TDM was introduced in June 2007; it was initially available weekly and has been available 4 days a week since 2010. RESULTS: Of 365 patients, 229 (63%) received antibiotics (109 received carbapenems). Of 23 TDM determinations for imipenem/cilastatin, none exceeded the predefined upper limit and 11 (47.8%) were insufficient; the number of TDM requests was correlated with daily dose (r=0.7). Similar numbers of inappropriate meropenem trough levels (30.4%) were below and above the upper limit. Real-time TDM introduction increased the empirical dose of imipenem/cilastatin, but not meropenem. CONCLUSIONS: Real-time carbapenem TDM availability significantly altered the empirical daily dosage of imipenem/cilastatin at our burn ICU. Further studies are needed to evaluate the individual impact of TDM-based antibiotic adjustment on infection outcomes in these patients.

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The variability observed in drug exposure has a direct impact on the overall response to drug. The largest part of variability between dose and drug response resides in the pharmacokinetic phase, i.e. in the dose-concentration relationship. Among possibilities offered to clinicians, Therapeutic Drug Monitoring (TDM; Monitoring of drug concentration measurements) is one of the useful tool to guide pharmacotherapy. TDM aims at optimizing treatments by individualizing dosage regimens based on blood drug concentration measurement. Bayesian calculations, relying on population pharmacokinetic approach, currently represent the gold standard TDM strategy. However, it requires expertise and computational assistance, thus limiting its large implementation in routine patient care. The overall objective of this thesis was to implement robust tools to provide Bayesian TDM to clinician in modern routine patient care. To that endeavour, aims were (i) to elaborate an efficient and ergonomic computer tool for Bayesian TDM: EzeCHieL (ii) to provide algorithms for drug concentration Bayesian forecasting and software validation, relying on population pharmacokinetics (iii) to address some relevant issues encountered in clinical practice with a focus on neonates and drug adherence. First, the current stage of the existing software was reviewed and allows establishing specifications for the development of EzeCHieL. Then, in close collaboration with software engineers a fully integrated software, EzeCHieL, has been elaborated. EzeCHieL provides population-based predictions and Bayesian forecasting and an easy-to-use interface. It enables to assess the expectedness of an observed concentration in a patient compared to the whole population (via percentiles), to assess the suitability of the predicted concentration relative to the targeted concentration and to provide dosing adjustment. It allows thus a priori and a posteriori Bayesian drug dosing individualization. Implementation of Bayesian methods requires drug disposition characterisation and variability quantification trough population approach. Population pharmacokinetic analyses have been performed and Bayesian estimators have been provided for candidate drugs in population of interest: anti-infectious drugs administered to neonates (gentamicin and imipenem). Developed models were implemented in EzeCHieL and also served as validation tool in comparing EzeCHieL concentration predictions against predictions from the reference software (NONMEM®). Models used need to be adequate and reliable. For instance, extrapolation is not possible from adults or children to neonates. Therefore, this work proposes models for neonates based on the developmental pharmacokinetics concept. Patients' adherence is also an important concern for drug models development and for a successful outcome of the pharmacotherapy. A last study attempts to assess impact of routine patient adherence measurement on models definition and TDM interpretation. In conclusion, our results offer solutions to assist clinicians in interpreting blood drug concentrations and to improve the appropriateness of drug dosing in routine clinical practice.