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BackgroundPhysiologically-based pharmacokinetic (PBPK) models are considered a promising approach to better characterize and anticipate the effect of physiological changes on pharmacokinetics in pregnant women. Consequently, multiple pregnancy PBPK models have been developed and verified over the past years. Using acetaminophen (paracetamol) as example, PBPK modeling can provide specific insights into the expected pharmacokinetic changes throughout pregnancy.MethodsTo obtain an overview of pregnancy PBPK models, the scientific literature was systematically screened for publications with a focus on pharmaceutical applications using relevant keywords. Additionally, a pregnancy PBPK model for acetaminophen was developed with the Open Systems Pharmacology software suite (www.open-systems-pharmacology.org) following an established workflow. After model verification around gestational week 30, the model was scaled to earlier stages of pregnancy and molar dose fractions converted to acetaminophen metabolites were estimated for each trimester.ResultsOver the past years, more than 60 different pregnancy PBPK models for more than have 40 drugs been published. More than 70% of these models were developed for the third trimester, while few models have been applied to the first trimester. The developed PBPK model for acetaminophen indicated that the median dose fraction of acetaminophen converted to the reactive metabolite N-acetyl-p-benzoquinonimine (NAPQI) was 11%, 9.0% and 8.2% in the first, second and third trimester, respectively, while for non-pregnant women a value of 7.7% was simulated.ConclusionWhile the overall availability and quality of pregnancy PBPK models is varying considerably, the efforts to establish such models are promising in that they reflect an increased awareness of the necessity to better characterize pharmacokinetics during pregnancy. This is illustrated by the developed PBPK model for acetaminophen where information on NAPQI-formation in vivo is hitherto lacking. Although PBPK models are not a substitute for clinical trials, they constitute an important tool for clinicians in case of missing or incomplete information.Disclosure(s)Nothing to disclose

BackgroundPhysiologic changes associated with pregnancy may have a large impact on drug disposition. The goal of this study was to build PBPK maternal-fetal models to predict the fetal exposure to antiviral drugs including emtricitabine and acyclovir.MethodsPBPK models were built in the Open Systems Pharmacology Software Suite version 7.3 (www.open-systems-pharmacology.org). The maternal-fetal PBPK model structure was developed in MoBi and exported to PK-Sim for population simulations. Placental transfer was parameterized based on data from ex vivo cotyledon perfusion experiments. The predictive performance of the PBPK models was evaluated via comparison with in vivo data. The pregnancy data for those drugs were from in vivo maternal and fetal blood samples taken at delivery.ResultsIn the acyclovir ex vivo experimental data simulation, the fitted was 0.056 L/h (95% confidence interval: 0.043 - 0.069 L/h) and the fitted was 0.49 (95% confidence interval: 0.39 - 0.59). The predicted ratio between acyclovir in vivo concentrations in the umbilical vein plasma and the maternal plasma ranged from 0.37 - 0.77, whereas the observed ratios were slightly higher and ranged from 0.61 - 1.1.1 The previously published, and CLpl (1.49 1/h) parameters2 were applied to the emtricitabine maternal-fetal PBPK model, and the emtricitabine concentrations in the umbilical cord were adequately predicted.ConclusionThese results increase the confidence in applying PBPK models to predict maternal and fetal drug exposure. Improved maternal-fetal PBPK models may streamline and accelerate the performance of pharmacokinetic and safety studies for drugs in pregnant women.ReferencesFrenkel LM, et al. Pharmacokinetics of acyclovir in the term human pregnancy and neonate. Am J Obstet Gynecol 1991;164:569–76.De Sousa Mendes M, et al. Prediction of human fetal pharmacokinetics using ex vivo human placenta perfusion studies and physiologically based models. Brit J Clin Pharmacol 2016;81:646–57.Disclosure(s)The opinions expressed in this article are those of the authors and should not be interpreted as the position of the U.S. Food and Drug Administration or of the National Institutes of Health. The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

BackgroundLittle is known about the pharmacokinetics (PK) of acetaminophen during different stages of pregnancy. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict acetaminophen PK throughout pregnancy.MethodsPBPK models for acetaminophen and its metabolites were developed in non-pregnant and pregnant women. Physiological and enzymatic changes in pregnant women expected to impact acetaminophen PK were considered. The models were evaluated using goodness-of-fit-plots and through comparison of predicted PK profiles with in-vivo PK data. Predictions were performed to illustrate the concentrations at steady state (Css-mean), used as indicator for efficacy of acetaminophen achieved following 1000 mg q6h. Furthermore, as measurement for potential hepatotoxicity, the molar dose fraction of acetaminophen converted to NAPQI was estimated.ResultsPBPK models successfully predicted the PK of acetaminophen and its metabolites in populations of non-pregnant and pregnant women. Predictions resulted in lowest Css-mean in the third trimester (4.5 mg/L), while Css-mean was 6.7, 5.6 and 4.9 mg/L in non-pregnant, first and second trimester populations, respectively. Assuming a constant increased activity of CYP2E1 throughout pregnancy, the molar dose fraction of acetaminophen converted to NAPQI was highest during the first (11.0%), followed by second (9.0%) and third trimester (8.2%), compared to non-pregnant women (7.1%).ConclusionRisk for drug related hepatotoxicity in pregnant women might be increased as more NAPQI is produced during pregnancy compared to non-pregnant women, especially during the first trimester. However, lack of information on the detoxifying capacity precludes any strong conclusions.Disclosure(s)Paola Mian received a Short term Minor (STM-2017) grant from the Stichting Sophia Kinderziekenhuis fonds to conduct this research.

BackgroundLittle is known about fetal acetaminophen (paracetamol) pharmacokinetics and its potential for toxicity, despite the frequent use of acetaminophen during pregnancy. The aim of this study was to develop a feto-maternal physiologically based pharmacokinetic model (f-m PBPK) to predict placental transfer and PK of acetaminophen and its metabolites in fetus at term pregnancy.MethodsPreviously, a pregnancy PBPK model was developed for prediction of maternal PK of acetaminophen and its metabolites. This model was structurally extended with the fetal liver, and quantitative information on the maturation of relevant enzymes was integrated. Three different approaches (ex vivo placenta perfusion experiments, scaling of passive diffusion transfer rates, and the Mobi® default method) to describe placental drug transfer were tested. Predicted maternal and fetal acetaminophen concentrations were compared with those observed in the literature. umbilical cord data at birth.ResultsThe 3 different approaches to predicted acetaminophen PK in the umiblical vein were found to yield broadly similar results. Acetaminophen exposure was similar in maternal blood compared to venous umbilical cord blood. Prediction of the median dose fraction of acetaminophen converted to its metabolites (fm) revealed higher maternal acetaminophen-glucuronide formation clearance and sulphate formation compared to that in the fetal liver (fm_glucuronide52.2 vs 0% and fm_sulphate30.4 vs 0.8%, respectively) and higher fraction of acetaminophen converted to the reactive metabolite N-acetyl-p-benzoquinone-imine (fm_NAPQI, 6.5 vs 0.06%) in pregnant women compared to their fetus.ConclusionNo differences were observed in the 3 approaches for integration of placental drug transfer. Differences in acetaminophen biotransformation to its metabolites between pregnant women and their fetuses were quantitatively predicted.Disclosure(s)Paola Mian received a Short term Minor (STM-2017) grant from the Stichting Sophia Kinderziekenhuis fonds to conduct this research.

This work is concerned with how best to reconstruct images from limited angle tomographic measurements. An introduction to tomography and to limited angle tomography will be provided and a brief overview of the many fields to which this work may contribute is given. The traditional tomographic image reconstruction approach involves Fourier domain representations. The classic Filtered Back Projection algorithm will be discussed and used for comparison throughout the work. Bayesian statistics and information entropy considerations will be described. The Maximum Entropy reconstruction method will be derived and its performance in limited angular measurement scenarios will be examined. Many new approaches become available once the reconstruction problem is placed within an algebraic form of Ax=b in which the measurement geometry and instrument response are defined as the matrix A, the measured object as the column vector x, and the resulting measurements by b. It is straightforward to invert A. However, for the limited angle measurement scenarios of interest in this work, the inversion is highly underconstrained and has an infinite number of possible solutions x consistent with the measurements b in a high dimensional space. The algebraic formulation leads to the need for high performing regularization approaches which add constraints based on prior information of what is being measured. These are constraints beyond the measurement matrix A added with the goal of selecting the best image from this vast uncertainty space. It is well established within this work that developing satisfactory regularization techniques is all but impossible except for the simplest pathological cases. There is a need to capture the \"character\" of the objects being measured. The novel result of this effort will be in developing a reconstruction approach that will match whatever reconstruction approach has proven best for the types of objects being measured given full angular coverage. However, when confronted with limited angle tomographic situations or early in a series of measurements, the approach will rely on a prior understanding of the \"character\" of the objects measured. This understanding will be learned by a parallel Deep Neural Network from examples.

Purpose: To evaluate the efficacy of vena cava filters and to compare them with the new TrapEase filter. Methods: Thrombus capture rates of 10 permanent and retrievable vena cava filters were tested in vitro in vertical and horizontal positions with thrombus diameters of 3 and 5 mm (length 30 mm) and tube diameters of 21 and 28 mm. Testing included the new TrapEase filter. Results were compared statistically using Fisher’s exact test (capture rates) and the Kruskal–Wallis test (construction). Results: Best-ranked filters were the Bird’s Nest, the TrapEase and the Simon Nitinol filters. The Tempofilter, the Greenfield and the Keeper filter performed worst. Thrombus capture rates were significantly higher in the vertical position and also higher for large thrombi and in the small cava diameter. Conical filters performed worse than filters with two or more filtration levels. Conclusion: Filters with two or more filtration levels show the highest filtration efficiency in vitro and can be recommended, especially for the critically ill who will probably not tolerate even small emboli. The TrapEase filter is a promising device and should be evaluated clinically.

Neutron and gamma-ray spectroscopy (NGRS) is a well established technique for studying the geochemical composition and volatile abundance relevant to planetary structure and evolution of planetary bodies. Previous NGRS instruments have used separate gamma-ray and neutron spectrometers. The Elpasolite Planetary Ice and Composition Spectrometer (EPICS) instrument is an innovative and fully integrated NGRS with low resource requirements. EPICS utilizes elpasolite scintillator read out by silicon photomultipliers to combine the gamma-ray and neutron spectrometer into a single instrument, leading to a significant reduction in instrument size, weight, and power. An overview and motivation for the EPICS instrument, current status of the EPICS development, and a discussion of the expected sensitivity and performance are presented.

A 42-kDa endochitinase encoding gene, Tham-ch, was cloned by screening the genomic library of Trichoderma hamatum strain Tam-61 with a PCR-amplified chitinase sequence from the same fungus. Tham-ch with its own regulatory sequences was reintroduced into the host strain. The integration of the transforming construct was stable only in one copy. Homologous integration occurred in nine transformants, while non-homologous integration was detected in one transformant. All but one transformant expressed higher levels of chitinase activity in comparison to the wild-type recipient strain; the maximum level of increase was 5-fold. Duplicating the copy number of the highly conserved approximately 42-kDa endochitinase encoding gene appears to be one potential means by which the biocontrol capability of the Trichoderma species might be improved.

In this paper I investigate the effect of weather variations in the exporter and importer countries separately, as well as a the difference between weather variations in both countries, on bilateral trade flows. The analysis is done at the country, sectoral and product levels, worldwide, and over the 1992–2014 period. I find a negative effect of temperature variations in the exporter country and in the difference between exporter and importer countries, on bilateral trade, at the country level. At the product level, both negative and positive effects arise, but the negative effect of temperature dominates. The temperature effects are on the agricultural and manufacturing sectors, especially in the textile and metals sectors. I show that possible channels are the impact of temperature on output and labour productivity. The negative impacts are larger in exporter countries that are closer to the Equator, that have lower quality of institutions, and that export to more remote countries. If countries are able to adapt to climate change, the long term effects of temperature variations should be lower than the contemporaneous effect. Nevertheless, my results on the long term effects analysis do not support this hypothesis, suggesting no or very low adaptation. Moreover, the negative effect of temperature is persistent and cumulative through several years after the temperature shock. Concerning precipitation variation effects, they are found mainly at the product level, with the positive effect dominating for the affected products.

Synchronisation of radar systems can be used to suppress interference and enable communication between radars. In this paper, a generalised Kuramoto model is proposed, which can be used to synchronise pulse repetition frequencies of two radars over‐the‐air. The generalised approach allows the adjustment of a sampling factor which influences the convergence of the two pulse repetition frequencies. Furthermore, sampling criteria are derived, which can be used to estimate whether convergence occurs. Finally, it is shown by means of simulation that the model together with the criteria allows to reliably predict convergence and to perform synchronisation.