Suivi thérapeutique de l'imatinib = Therapeutische Drug-Monitoring von Imatinib

Monitoring spielt eine wichtige Rolle zur Therapieevaluierung und Behandlungsentscheidung - solange es auf der Basis der Messung von entsprechenden klinischen oder validierten Surrogat-Markern stattfindet. Im Hinblick auf die Imatinib-Therapie scheint das «Therapeutische Drug-Monitoring» (TDM) ein nützlicher Ansatz zum Therapie-Monitoring der CML-Behandlung zu sein, welches die Plasmakonzentration des Arzneimittels als Marker zur Therapieüberwachung verwendet. Imatinib-Plasmakonzentrationen variieren beträchtlich von Patient zu Patient unter dem gleichen Dosierungsschema, aufgrund der interindividuell unterschiedlichen Pharmakokinetik des Arzneimittels. Für die Plasmaexposition wurde gezeigt, dass sie mit dem klinischen Outcome von CML-Patienten korreliert - sowohl im Bezug auf das Therapieansprechen als auch auf das Nebenwirkungsprofil. Es ist noch unklar, ob das TDM von Imatinib nur im Falle von klinischen Problemen Verwendung finden sollte oder ob CML-Patienten bereits von einem systematischen, präventiven «Routine»-Monitoring zur Therapieindividualisierung - zur Steuerung der Plasmakonzentration in einen therapeutischen Bereich - profitieren könnten, welches in letzter Zeit immer häufiger empfohlen wird. Um diese Fragestellung zu beantworten, nimmt eine prospektive, randomisiert kontrollierte Schweizer Studie CML-Patienten auf, die seit weniger als 5 Jahren mit Imatinib behandelt werden, und bietet das TDM zudem für alle Patienten im Falle von klinischen Problemen an.

Therapeutic drug monitoring of seven psychotropic drugs and four metabolites in human plasma by HPLC-MS.

A simple and sensitive LC-MS method was developed and validated for the simultaneous quantification of aripiprazole (ARI), atomoxetine (ATO), duloxetine (DUL), clozapine (CLO), olanzapine (OLA), sertindole (STN), venlafaxine (VEN) and their active metabolites dehydroaripiprazole (DARI), norclozapine (NCLO), dehydrosertindole (DSTN) and O-desmethylvenlafaxine (OVEN) in human plasma. The above mentioned compounds and the internal standard (remoxipride) were extracted from 0.5 mL plasma by solid-phase extraction (mix mode support). The analytical separation was carried out on a reverse phase liquid chromatography at basic pH (pH 8.1) in gradient mode. All analytes were monitored by MS detection in the single ion monitoring mode and the method was validated covering the corresponding therapeutic range: 2-200 ng/mL for DUL, OLA, and STN, 4-200 ng/mL for DSTN, 5-1000 ng/mL for ARI, DARI and finally 2-1000 ng/mL for ATO, CLO, NCLO, VEN, OVEN. For all investigated compounds, good performance in terms of recoveries, selectivity, stability, repeatability, intermediate precision, trueness and accuracy, was obtained. Real patient plasma samples were then successfully analysed.

Therapeutic drug monitoring in cancer - Are we missing a trick?

Therapeutic drug monitoring (TDM) can be defined as the measurement of drug in biological samples to individualise treatment by adapting drug dose to improve efficacy and/or reduce toxicity. The cytotoxic drugs are characterised by steep dose-response relationships and narrow therapeutic windows. Inter-individual pharmacokinetic (PK) variability is often substantial. There are, however, a multitude of reasons why TDM has never been fully implemented in daily oncology practice. These include difficulties in establishing appropriate concentration target, common use of combination chemotherapies and the paucity of published data from pharmacological trials. The situation is different with targeted therapies. The large interindividual PK variability is influenced by the pharmacogenetic background of the patient (e.g. cytochrome P450 and ABC transporters polymorphisms), patient characteristics such as adherence to treatment and environmental factors (drug-drug interactions). Retrospective studies have shown that targeted drug exposure correlates with treatment response in various cancers. Evidence for imatinib currently exists, others are emerging for compounds including nilotinib, dasatinib, erlotinib, sunitinib, sorafenib and mammalian target of rapamycin (mTOR) inhibitors. Applications for TDM during oral targeted therapies may best be reserved for particular situations including lack of therapeutic response, severe or unexpected toxicities, anticipated drug-drug interactions and concerns over adherence treatment. There are still few data with monoclonal antibodies (mAbs) in favour of TDM approaches, even if data showed encouraging results with rituximab and cetuximab. TDM of mAbs is not yet supported by scientific evidence. Considerable effort should be made for targeted therapies to better define concentration-effect relationships and to perform comparative randomised trials of classic dosing versus pharmacokinetically-guided adaptive dosing.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Introduction: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on measurement of blood concentrations. Maintaining concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. In the last decades computer programs have been developed to assist clinicians in this assignment. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Method: Literature and Internet search was performed to identify software. All programs were tested on common personal computer. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software's characteristics. Numbers of drugs handled vary widely and 8 programs offer the ability to the user to add its own drug model. 10 computer programs are able to compute Bayesian dosage adaptation based on a blood concentration (a posteriori adjustment) while 9 are also able to suggest a priori dosage regimen (prior to any blood concentration measurement), based on individual patient covariates, such as age, gender, weight. Among those applying Bayesian analysis, one uses the non-parametric approach. The top 2 software emerging from this benchmark are MwPharm and TCIWorks. Other programs evaluated have also a good potential but are less sophisticated (e.g. in terms of storage or report generation) or less user-friendly.¦Conclusion: Whereas 2 integrated programs are at the top of the ranked listed, such complex tools would possibly not fit all institutions, and each software tool must be regarded with respect to individual needs of hospitals or clinicians. Interest in computing tool to support therapeutic monitoring is still growing. Although developers put efforts into it the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capacity of data storage and report generation.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

Intrathecal drug delivery systems for cancer pain

Introduction: A substantial number of patients with cancer suffer considerable pain at some point during their disease, and approximately 25% of cancer patients die in pain. In cases of uncontrolled pain or intolerable side effects, intrathecal drug delivery system (IDDS) is a recognised management option. Indeed, IDDS offer rapid and effective pain relief with less drug side effects compared to oral or parenteral administration. The aim of this study is to retrospectively review our series of cancer patients treated with IDDS. Method: Data was extracted from the institutional neuromodulation registry. Patients with cancer pain treated with IDDS from 01.01.1997 to 30.12.2009 were analysed for subjective improvement, changes in pain intensity (VAS) and survival time after implantation. Measurements were available for a decreasing number of patients as time since baseline increased. Results: During the studied period, 78 patients were implanted with IDDS for cancer pain. The mean survival time was 11.1 months (median: 3.8 months) and 14 patients (18%) were still alive at the end of the studied period. Subjective improvement was graded between 55 and 83% during the first year. Mean VAS during the first year remained lower than VAS at baseline. Discussion: IDDS has been shown to be cost-effective in several studies. Although initial costs of implantation are high, the cost benefits favour analgesia with implanted intrathecal pumps over epidural external systems after 3 to 6 months in cancer patients. Improved survival has been associated with IDDS and in this series both the mean and median survival times were above the cut-off value of three months. The mean subjective improvement was above 50% during the whole first year, suggesting a good efficacy of the treatment, a finding that is consistent with the results from other groups. Changes in pain intensity are difficult to interpret in the context of rapidly progressive disease such as in terminal cancer. However, mean VAS from 1 thru12 months were lower than baseline, suggesting improved pain control with IDDS, or at least a stabilisation of the pain symptoms. Conclusion: Our retrospective series suggests IDDS is effective in intractable cancer pain and we believe it should be considered even in terminally ill patients with limited life expectancies.

Fast quantification of ten psychotropic drugs and metabolites in human plasma by ultra-high performance liquid chromatography tandem mass spectrometry for therapeutic drug monitoring.

A sensitive and selective ultra-high performance liquid chromatography (UHPLC) tandem mass spectrometry (MS/MS) method was developed for the fast quantification of ten psychotropic drugs and metabolites in human plasma for the needs of our laboratory (amisulpride, asenapine, desmethyl-mirtazapine, iloperidone, mirtazapine, norquetiapine, olanzapine, paliperidone, quetiapine and risperidone). Stable isotope-labeled internal standards were used for all analytes, to compensate for the global method variability, including extraction and ionization variations. Sample preparation was performed by generic protein precipitation with acetonitrile. Chromatographic separation was achieved in less than 3.0min on an Acquity UPLC BEH Shield RP18 column (2.1mm×50mm; 1.7μm), using a gradient elution of 10mM ammonium formate buffer pH 3.0 and acetonitrile at a flow rate of 0.4ml/min. The compounds were quantified on a tandem quadrupole mass spectrometer operating in positive electrospray ionization mode, using multiple reaction monitoring. The method was fully validated according to the latest recommendations of international guidelines. Eight point calibration curves were used to cover a large concentration range 0.5-200ng/ml for asenapine, desmethyl-mirtazapine, iloperidone, mirtazapine, olanzapine, paliperidone and risperidone, and 1-1500ng/ml for amisulpride, norquetiapine and quetiapine. Good quantitative performances were achieved in terms of trueness (93.1-111.2%), repeatability (1.3-8.6%) and intermediate precision (1.8-11.5%). Internal standard-normalized matrix effects ranged between 95 and 105%, with a variability never exceeding 6%. The accuracy profiles (total error) were included in the acceptance limits of ±30% for biological samples. This method is therefore suitable for both therapeutic drug monitoring and pharmacokinetic studies.