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.

Suomalaisen naisyrittäjän historia - ruokaa, vaatteita ja hoivaa

ELEKTRA-lisenssi

Vancomycin exposure from active calcium sulfate bone filler

Objective: Bone cements and substitutes are commonly used in surgery to deliver antibiotics locally. The objective of this study was to assess the systemic absorption and disposition of vancomycin in patients treated with active calcium sulfate bone filler and to predict systemic concentrations under various conditions. Method: 277 blood samples were taken from 42 patients receiving vancomycin in bone cement during surgery. Blood samples were collected from 3h to 10 days after implantation. Vancomycin was measured by immunoenzymatic assay. Population pharmacokinetic (PK) analysis was performed using NONMEM to assess average estimates and variability of PK parameters. Based on the final model, simulations with various doses and renal function levels were performed. Results: The patients were 64 ± 20 years old, their body weight was 81 ± 22 kg and Cockcroft-Gault creatinine clearance (CLcr) 98 ± 55 mL/min. Vancomycin doses ranged from 200 mg to 6000 mg and implantation sites were hip (n=16), tibia (10) or others (16). Concentration profiles remained low and consistent with absorption rate-limited first-order release, while showing prominent variability. Mean clearance (CL) was 3.87 L/h (CV 35%), absorption rate constant (ka) 0.004 h-1 (66%) and volume of distribution (V) 9.5 L. Simulations with up to 8000 mg vancomycin implant showed systemic concentrations exceeding 20 mg/L for 3.5 days in 43% of the patients with CLcr 15 mL/min, whereas 7% of the patients with normal renal function had a concentration above 20 mg/L for 1.1 days. Subtherapeutic concentrations (0.4-4 mg/L) were predicted during a median of 22 days in patients with normal renal function and 4000 mg vancomycin implant, with limited influence of dose or renal function. Conclusion: Vancomycin-laden calcium sulfate implant does not raise toxicity concern. Selection of resistant bacteria, such as Enterococcus and Staphylococcus species, might however be a concern, as simulations show persistent subtherapeutic systemic concentrations during 3 to 4 weeks in these patients.

Improvement of therapeutic drug monitoring of imatinib by Bayesian prediction of trough levels. Personalized drug dosage

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).

A combined computational and functional approach identifies new residues involved in pH-dependent gating of ASIC1a.

Acid-sensing ion channels (ASICs) are key receptors for extracellular protons. These neuronal nonvoltage-gated Na(+) channels are involved in learning, the expression of fear, neurodegeneration after ischemia, and pain sensation. We have applied a systematic approach to identify potential pH sensors in ASIC1a and to elucidate the mechanisms by which pH variations govern ASIC gating. We first calculated the pK(a) value of all extracellular His, Glu, and Asp residues using a Poisson-Boltzmann continuum approach, based on the ASIC three-dimensional structure, to identify candidate pH-sensing residues. The role of these residues was then assessed by site-directed mutagenesis and chemical modification, combined with functional analysis. The localization of putative pH-sensing residues suggests that pH changes control ASIC gating by protonation/deprotonation of many residues per subunit in different channel domains. Analysis of the function of residues in the palm domain close to the central vertical axis of the channel allowed for prediction of conformational changes of this region during gating. Our study provides a basis for the intrinsic ASIC pH dependence and describes an approach that can also be applied to the investigation of the mechanisms of the pH dependence of other proteins.

Lapatax: Safety profile of neoadjuvant lapatinib combined with docetaxel in Her 2/neu overexpressing breast cancer - EORTC protocol 10054

Objective: To assess the safety/tolerability of the combination lapatinib (L) and docetaxel (D) in patients with Her 2/neu overexpressing breast cancer (BC). This study is important as it will define how to deliver lapatinib with taxotere, a highly active drug in breast cancer. Patients and Methods: Female patients (pts) with locally advanced, inflammatory or large operable BC were treated with escalating doses of L from 1000 to 1250 mg/day, in combination with D given IV every 21 days at doses ranging from 75 to 100 mg/m2 for 4 cycles. At least 3 pts were treated at each dose level. The definition of dose limiting toxicity (DLT) is based on the toxicity assessed at cycle 1 as follows: any grade 3−4 non hematological toxicity, ANC < 0.5 G/L lasting for 7 days or more, febrile neutropenia or thrombocytopenia <25 G/L. GCSF was not permitted as primary prophylaxis. Core biopsies were mandatory at baseline and after cycle 4. Pharmcokinetic (PK) samples were collected on day 1 of cycles 1 and 2. Results: To date, 18 pts with a median age of 53 years (range 36−65) have been enrolled at 5 Dose Levels (DLs). The toxicity profile for 18 patients (68 documented cycles) is summarized below. At DL5 (1000/100), 2 pts had DLTs (neutropenia grade 4 _7 days and febrile neutropenia), and 3 additional pts were enrolled with primary prophylactic G-CSF. As expected, the safety profile improved and the dose escalation will continue with prophylactic G-CSF to investigate DL6 (1250/100). These findings are consistent with published Phase I data for this combination [1]. N= 18 patients n (%) Grade 1 Grade 2 Grade 3 Grade 4 neutropenia 1 (6) 3 (17) 13 (72) febrile neutropenia 2 (11) fatigue 8 (44) 7 (39) diarrhoea 9 (50) 3 (17) pain: joint/muscle/other 5 (28)/4 (22)/3 (17) 4 (22)/4 (22)/3 (17) 0/0/1 (6) constipation 2 (11) 3 (17) 1 (6) elevated transaminases SGPT/SGOT 7 (39)/5 (28) Conclusions: The main toxicity of the L + D combination is haematological and was reached at DL5 (1000/100), without primary GCSF. An additional DL6 with primary prophylactic GCSF is being investigated (1250/100). PK data will be presented at the meeting plus the recommended dose for phase II studies.