Self-Consistent Field study of Polyelectrolyte Brushes

We formulate a self-consistent field theory for polyelectrolyte brushes in the presence of counterions. We numerically solve the self-consistent field equations and study the monomer density profile, the distribution of counterions, and the total charge distribution. We study the scaling relations for the brush height and compare them to the prediction of other theories. We find a weak dependence of the brush height on the grafting density.We fit the counterion distribution outside the brush by the Gouy-Chapman solution for a virtual charged wall. We calculate the amount of counterions outside the brush and find that it saturates as the charge of the polyelectrolytes increases

Validation and clinical application of a multiplex high performance liquid chromatography - tandem mass spectrometry assay for the monitoring of plasma concentrations of 12 antibiotics in patients with severe bacterial infections.

Unpredictable pharmacokinetics of antibiotics in patients with life-threatening bacterial infections is associated with drug under- or overdosing. Therapeutic drug monitoring (TDM) may guide dosing adjustment aimed at maximizing antibacterial efficacy and minimizing toxicity. Rapid and accurate analytical methods are key for real-time TDM. Our objective was to develop a robust high-performance liquid chromatography-tandem mass spectrometry method (HPLC-MS/MS) for multiplex quantification of plasma concentrations of 12 antibiotics: imipenem/cilastatin, meropenem, ertapenem, cefepime, ceftazidime, ceftriaxone, piperacillin/tazobactam, amoxicillin, flucloxacillin, rifampicin, daptomycin. A single extraction procedure consisting in methanol plasma protein precipitation and H <sub>2</sub> O dilution was used for all analytes. After chromatographic separation on an Acquity UPLC HSS-T3 2.1 × 50 mm, 1.8 µm (Waters®) column, quantification was performed by electro-spray ionisation-triple quadrupole mass spectrometry with selected reaction monitoring detection. Antibiotics were divided in two pools of calibration according to the frequency of analyses requests in the hospital routine antibiotic TDM program. Stable isotopically-labelled analogues were used as internal standards. A single analytical run lasted less than 9 min. The method was validated based on FDA recommendations, including assessment of extraction yield (96-113.8%), matrix effects, and analytical recovery (86.3-99.6%). The method was sensitive (lower limits of quantification 0.02-0.5 µg/mL), accurate (intra/inter-assay bias -11.3 to +12.7%) and precise (intra/inter-assay CVs 2.1-11.5%) over the clinically relevant plasma concentration ranges (upper limits of quantification 20-160 µg/mL). The application of the TDM assay was illustrated with clinical cases that highlight the impact on patients' management of an analytical assay providing information with short turn-around time on antibiotic plasma concentration. This simple, robust high-throughput multiplex HPLC-MS/MS assay for simultaneous quantification of plasma concentrations of 12 daily used antibiotics is optimally suited for clinically efficient real-time TDM

Efficient Dynamic Importance Sampling of Rare Events in One Dimension

Exploiting stochastic path integral theory, we obtain \emph{by simulation} substantial gains in efficiency for the computation of reaction rates in one-dimensional, bistable, overdamped stochastic systems. Using a well-defined measure of efficiency, we compare implementations of ``Dynamic Importance Sampling'' (DIMS) methods to unbiased simulation. The best DIMS algorithms are shown to increase efficiency by factors of approximately 20 for a $5 k_B T$ barrier height and 300 for $9 k_B T$, compared to unbiased simulation. The gains result from close emulation of natural (unbiased), instanton-like crossing events with artificially decreased waiting times between events that are corrected for in rate calculations. The artificial crossing events are generated using the closed-form solution to the most probable crossing event described by the Onsager-Machlup action. While the best biasing methods require the second derivative of the potential (resulting from the ``Jacobian'' term in the action, which is discussed at length), algorithms employing solely the first derivative do nearly as well. We discuss the importance of one-dimensional models to larger systems, and suggest extensions to higher-dimensional systems.Comment: version to be published in Phys. Rev.

Useful pharmacodynamic endpoints in children: selection, measurement, and next steps.

Pharmacodynamic (PD) endpoints are essential for establishing the benefit-to-risk ratio for therapeutic interventions in children and neonates. This article discusses the selection of an appropriate measure of response, the PD endpoint, which is a critical methodological step in designing pediatric efficacy and safety studies. We provide an overview of existing guidance on the choice of PD endpoints in pediatric clinical research. We identified several considerations relevant to the selection and measurement of PD endpoints in pediatric clinical trials, including the use of biomarkers, modeling, compliance, scoring systems, and validated measurement tools. To be useful, PD endpoints in children need to be clinically relevant, responsive to both treatment and/or disease progression, reproducible, and reliable. In most pediatric disease areas, this requires significant validation efforts. We propose a minimal set of criteria for useful PD endpoint selection and measurement. We conclude that, given the current heterogeneity of pediatric PD endpoint definitions and measurements, both across and within defined disease areas, there is an acute need for internationally agreed, validated, and condition-specific pediatric PD endpoints that consider the needs of all stakeholders, including healthcare providers, policy makers, patients, and families.Pediatric Research advance online publication, 11 April 2018; doi:10.1038/pr.2018.38

Population pharmacokinetic modelling and evaluation of different dosage regimens for darunavir and ritonavir in HIV-infected individuals

Objectives Darunavir is a protease inhibitor that is administered with low-dose ritonavir to enhance its bioavailability. It is prescribed at standard dosage regimens of 600/100 mg twice daily in treatment-experienced patients and 800/100 mg once daily in naive patients. A population pharmacokinetic approach was used to characterize the pharmacokinetics of both drugs and their interaction in a cohort of unselected patients and to compare darunavir exposure expected under alternative dosage regimens. Methods The study population included 105 HIV-infected individuals who provided darunavir and ritonavir plasma concentrations. Firstly, a population pharmacokinetic analysis for darunavir and ritonavir was conducted, with inclusion of patients' demographic, clinical and genetic characteristics as potential covariates (NONMEM®). Then, the interaction between darunavir and ritonavir was studied while incorporating levels of both drugs into different inhibitory models. Finally, model-based simulations were performed to compare trough concentrations (Cmin) between the recommended dosage regimen and alternative combinations of darunavir and ritonavir. Results A one-compartment model with first-order absorption adequately characterized darunavir and ritonavir pharmacokinetics. The between-subject variability in both compounds was important [coefficient of variation (CV%) 34% and 47% for darunavir and ritonavir clearance, respectively]. Lopinavir and ritonavir exposure (AUC) affected darunavir clearance, while body weight and darunavir AUC influenced ritonavir elimination. None of the tested genetic variants showed any influence on darunavir or ritonavir pharmacokinetics. The simulations predicted darunavir Cmin much higher than the IC50 thresholds for wild-type and protease inhibitor-resistant HIV-1 strains (55 and 550 ng/mL, respectively) under standard dosing in >98% of experienced and naive patients. Alternative regimens of darunavir/ritonavir 1200/100 or 1200/200 mg once daily also had predicted adequate Cmin (>550 ng/mL) in 84% and 93% of patients, respectively. Reduction of darunavir/ritonavir dosage to 600/50 mg twice daily led to a 23% reduction in average Cmin, still with only 3.8% of patients having concentrations below the IC50 for resistant strains. Conclusions The important variability in darunavir and ritonavir pharmacokinetics is poorly explained by clinical covariates and genetic influences. In experienced patients, treatment simplification strategies guided by drug level measurements and adherence monitoring could be propose

Relationship of imatinib-free plasma levels and target genotype with efficacy and tolerability

Imatinib has revolutionised the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumours (GIST). Using a nonlinear mixed effects population model, individual estimates of pharmacokinetic parameters were derived and used to estimate imatinib exposure (area under the curve, AUC) in 58 patients. Plasma-free concentration was deduced from a model incorporating plasma levels of alpha1-acid glycoprotein. Associations between AUC (or clearance) and response or incidence of side effects were explored by logistic regression analysis. Influence of KIT genotype was also assessed in GIST patients. Both total (in GIST) and free drug exposure (in CML and GIST) correlated with the occurrence and number of side effects (e.g. odds ratio 2.7±0.6 for a two-fold free AUC increase in GIST; P<0.001). Higher free AUC also predicted a higher probability of therapeutic response in GIST (odds ratio 2.6±1.1; P=0.026) when taking into account tumour KIT genotype (strongest association in patients harbouring exon 9 mutation or wild-type KIT, known to decrease tumour sensitivity towards imatinib). In CML, no straightforward concentration–response relationships were obtained. Our findings represent additional arguments to further evaluate the usefulness of individualising imatinib prescription based on a therapeutic drug monitoring programme, possibly associated with target genotype profiling of patients

Pharmacometrics-based decision tools facilitate mHealth implementation.

The healthcare system is experiencing a paradigm shift in delivering its services, evolving from a reactive 'one size-fits-all' structure to a patient-centric model focusing on individualized medicine. This change is driven by scientific progress, including quantitative evaluation and optimization of treatment strategies through pharmacometric approaches, harnessing the power of the digital revolution. Areas covered: This review describes four main steps to apply pharmacometrics-based decision support tools, consisting of validated scientific components, available technical options, consideration of regulatory aspects, and achievement of efficient commercialization. Examples of pharmacometrics-based decision tools that support monitoring of patients and individualization of treatment strategies in neonates, children and adults are presented. Expert commentary: We envision that user-friendly decision support tools will facilitate implementation of mobile health approaches (mHealth) realizing benefits to paediatric and adult patients and their caregivers

[Reflexions before the introduction of a drug prescription survey at hospitals]

The need to know about drug prescribing practices, in order to assess their relevance, has led us to perform a drug prescription study in two medical departments of Cardiology at 'Neuro-Cardiologique Hospital' in Lyon (France). In moving from theoretical project design to its practical achievement, important methodological problems, initially unsuspected, were encountered. For each main point of the study (choices regarding medical department, the person holding the inquiry, data collection, etc.) and any subsidiary operations (data key-boarding, codification and analysis), the main problems encountered are described after considering advantages and limits of potential solutions. We propose useful and relevant questions to be asked, before performing a drug prescription study, even a modest one, or interpreting the results of such a study

Plasma and cerebrospinal fluid population pharmacokinetics of temozolomide in malignant glioma patients

PURPOSE: Scarce information is available on the brain penetration of temozolomide (TMZ), although this novel methylating agent is mainly used for the treatment of malignant brain tumors. The purpose was to assess TMZ pharmacokinetics in plasma and cerebrospinal fluid (CSF) along with its inter-individual variability, to characterize covariates and to explore relationships between systemic or cerebral drug exposure and clinical outcomes. EXPERIMENTAL DESIGN: TMZ levels were measured by high-performance liquid chromatography in plasma and CSF samples from 35 patients with newly diagnosed or recurrent malignant gliomas. The population pharmacokinetic analysis was performed with nonlinear mixed-effect modeling software. Drug exposure, defined by the area under the concentration-time curve (AUC) in plasma and CSF, was estimated for each patient and correlated with toxicity, survival, and progression-free survival. RESULTS: A three-compartment model with first-order absorption and transfer rates between plasma and CSF described the data appropriately. Oral clearance was 10 liter/h; volume of distribution (V(D)), 30.3 liters; absorption constant rate, 5.8 h(-1); elimination half-time, 2.1 h; transfer rate from plasma to CSF (K(plasma--&gt;CSF)), 7.2 x 10(-4)h(-1) and the backwards rate, 0.76 h(-1). Body surface area significantly influenced both clearance and V(D), and clearance was sex dependent. The AUC(CSF) corresponded to 20% of the AUC(plasma). A trend toward an increased K(plasma--&gt;CSF) of 15% was observed in case of concomitant radiochemotherapy. No significant correlations between AUC in plasma or CSF and toxicity, survival, or progression-free survival were apparent after deduction of dose-effect. CONCLUSIONS: This is the first human pharmacokinetic study on TMZ to quantify CSF penetration. The AUC(CSF)/AUC(plasma) ratio was 20%. Systemic or cerebral exposures are not better predictors than the cumulative dose alone for both efficacy and safety