Solvent Optimization Studies for a New EURO-GANEX Process with 2,2’-Oxybis( N,N -di- n -decylpropanamide) (mTDDGA) and Its Radiolysis Products

The diglycolamide 2,2’-oxybis(N,N-di-n-decylpropanamide) (mTDDGA) is being studied as an extractant for actinides and lanthanides in the European Grouped Actinide Extraction (EURO-GANEX) process. The aim is the development of a more simplified process using a single extractant instead of a mixture of extractants used in the current EURO-GANEX process. This work presents solvent optimization studies of mTDDGA, with regards to the extraction characteristics of the different diastereomers of mTDGA and of mixed diastereomer solutions. Also radiolysis behavior has been studied by irradiation of solvent extraction systems in a gamma irradiation facility using $^{60}$Co. The availability of irradiated organic solutions made it possible to gain valuable insights into the plutonium loading capacity after gamma-irradiation of the solvent up to 445 kGy and to quantify degradation compounds. Solvent extraction characteristic of the major degradation compounds themselves were determined. Like other methylated diglycolamides, we found a remarkable difference in extraction of up to two orders of magnitude between the two diastereomers. High plutonium loading (36 g L$^{−1}$) is feasible using this single extractant, even after absorbing a dose of 445 kGy. This remarkable observation is possibly promoted by the presence of the main degradation compound which extracts plutonium verywell

Dynamic Modeling of Workforce Requirements for Mass Prophylaxis Under Highly Uncertain Conditions: Cornell Dynamic POD Simulator

The public health response to a bioterrorist attack or other large-scale health emergency may include mass prophylaxis using multiple Points of Dispensing (PODs) to deliver countermeasures rapidly to affected populations. Although computer models exist to determine "optimal" staffing levels at PODs under certain steady-state conditions, no quantitative studies address the requirements of the POD workforce management systems needed to enable efficient, population-wide coverage in the face of a dynamic and uncertain operational environment. Our goal was to investigate quantitatively the impact of dynamic and uncertain patient arrival patterns on workforce requirements and on overall POD effectiveness and efficiency over the duration of a mass prophylaxis campaign. To investigate the dynamic behavior of POD systems, many extensive simulation experiments were conducted using a Monte Carlo simulation model, called the Dynamic POD Simulator (D-PODS). Using this simulation environment, we designed POD station layouts, capacities, staffing patterns, patient types, and work flows and then observed the consequences of operating PODs based on these plans under various patient arrival scenarios. The D-PODS user interface is an Excel worksheet and the model is implemented in Visual Basic. Using several illustrative POD experiments, we demonstrate that uncertain patient arrival patterns require higher staffing levels than might be expected if a stationary environment is assumed. These experiments further show that PODs may develop severe bottlenecks unless staffing levels vary over time to meet changing patient arrival patterns. Because of the unpredictability of the operating environment, efficient POD networks require command and control systems capable of dynamically adjusting intra- and inter-POD staffing levels to meet demand. Furthermore, we show that fewer large PODs require a smaller total staff than many small PODs require to serve the same number of patients. We conclude that modeling environments that capture the effects of fundamental uncertainties in public health disasters are essential for the realistic evaluation of response mechanisms and policies. D-PODS quantifies POD operational efficiency under more realistic conditions than have been modeled previously. Our experiments demonstrate the critical role of variation and uncertainty in POD arrival patterns in establishing effective POD staffing plans. These experiments also highlight the need for command and control systems to be created to manage emergency response successfully.School of Operations Research & Information Engineering Weill Medical Colleg

Transport of treosulfan and temozolomide across an in-vitro blood–brain barrier model

In vitro, treosulfan (TREO) has shown high effectiveness against malignant gliomas. However, a first clinical trial for newly diagnosed glioblastoma did not show any positive effect. Even though dosing and timing might have been the reasons for this failure, it might also be that TREO does not reach the brain in sufficient amount. Surprisingly, there are no published data on TREO uptake into the brain of patients, despite extensive research on this compound. An in-vitro blood-brain barrier (BBB) model consisting of primary porcine brain capillary endothelial cells was used to determine the transport of TREO across the cell monolayer. Temozolomide (TMZ), the most widely used cytotoxic drug for malignant gliomas, served as a reference. An HPLC-ESI-MS/MS procedure was developed to detect TREO and TMZ in cell culture medium. Parallel to the experimental approach, the permeability of TREO and the reference substance across the in-vitro BBB was estimated on the basis of their physicochemical properties. The detection limit was 30 nmol/l for TREO and 10 nmol/l for TMZ. Drug transport was measured in two directions: influx, apical-to-basolateral (A-to-B), and efflux, basolateral-to-apical (B-to-A). For TREO, the A-to-B permeability was lower (1.6%) than the B-to-A permeability (3.0%). This was in contrast to TMZ, which had higher A-to-B (13.1%) than B-to-A (7.2%) permeability values. The in-vitro BBB model applied simulated the human BBB properly for TMZ. It is, therefore, reasonable to assume that the values for TREO are also meaningful. Considering the lack of noninvasive, significant alternative methods to study transport across the BBB, the porcine brain capillary endothelial cell model was efficient to collect first data for TREO that explain the disappointing clinical results for this drug against cerebral tumors

Development and validation of an UHPLC-ESI-QTOF-MS method for quantification of the highly hydrophilic amyloid-β oligomer eliminating all- D -enantiomeric peptide RD2 in mouse plasma

During preclinical drug development, a method for quantification of unlabeled compounds in blood plasma samples from treatment or pharmacokinetic studies in mice is required. In the current work, a rapid, specific, sensitive and validated liquid chromatography mass-spectrometric UHPLC-ESI-QTOF-MS method was developed for the quantification of the therapeutic compound RD2 in mouse plasma. RD2 is an all-D-enantiomeric peptide developed for the treatment of Alzheimer’s disease, a progressive neurodegenerative disease finally leading to dementia. Due to RD2’s highly hydrophilic properties, the sample preparation and the chromatographic separation and quantification were very challenging. The chromatographic separation of RD2 and its internal standard were accomplished on an Acquity UPLC BEH C18 column (2.1 × 100 mm, 1.7 μm particle size) within 6.5 min at 50 °C with a flow rate of 0.5 mL/min. Mobile phases consisted of water and acetonitrile with 1% formic acid and 0.025% heptafluorobutyric acid, respectively. Ions were generated by electrospray ionization (ESI) in the positive mode and the peptide was quantified by QTOF-MS. The developed extraction method for RD2 from mouse plasma revealed complete recovery. The linearity of the calibration curve was in the range of 5.3 ng/mL to 265 ng/mL (r2 > 0.999) with a lower limit of detection (LLOD) of 2.65 ng/mL and a lower limit of quantification (LLOQ) of 5.3 ng/mL. The intra-day and inter-day accuracy and precision of RD2 in plasma ranged from −0.54% to 2.21% and from 1.97% to 8.18%, respectively. Moreover, no matrix effects were observed and RD2 remained stable in extracted mouse plasma at different conditions. Using this validated bioanalytical method, plasma samples of unlabeled RD2 or placebo treated mice were analyzed. The herein developed UHPLC-ESI-QTOF-MS method is a suitable tool for the quantitative analysis of unlabeled RD2 in plasma samples of treated mice