Репозиторий Университета

© 2019 American Pharmacists Association® Various drug delivery systems (DDSs) are often used in modern medicine to achieve controlled and targeted drug release. Diffusional release of drugs from DDSs is often the main mechanism, especially at early times. Generally, average dimensions of DDS are used to model the drug release, but our recent work on drug release from fibers demonstrated that taking into account diameter distribution is essential. This work systematically investigated the effect of size distribution on diffusional drug release from DDSs of various geometric forms such as membranes, fibers, and spherical particles. The investigation clearly demonstrated that the size distribution has the largest effect on the drug release profiles from spherical particles compared to other geometric forms. Published experimental data for drug release from polymer microparticles and nanoparticles were fitted, and the diffusion coefficients were determined assuming reported radius distributions. Assuming the average radius when fitting the data leads to up to 5 times underestimation of the diffusion coefficient of drug in the polymer.

© 2018 Pirogov Russian National Research Medical University. All rights reserved. Mathematical modeling of pharmacokinetic (PK) and pharmacodynamic (PD) parameters essential for establishing correct dosing regimens is an alternative to pharmacokinetic studies (PKS) adopted in the clinical setting. The aim of this work was to compare the values of PK parameters for vancomycin obtained in an actual PKS and through MM in postoperative patients with kidney injury. Our prospective study included 61 patients (47 males and 14 females aged 60.59 ± 12.23 years). During PKS, drug concentrations at steady state Сtrough and Cpeak were measured by high-performance liquid chromatography followed by the calculation of the area under the plasma concentration-time curve AUC24. For mathematical modeling, a single-compartment model was employed; PK parameters were estimated using R 3.4.0. The values of Ctrough measured 48 h after the onset of antibiotic therapy during PKS were significantly lower than those predicted by MM (р = 0.004). In a group of patients with acute kidney injury (AKI), AUC24 measured at the end of treatment was significantly higher than its value predicted by MM (р = 0.011). The probability of achieving the target AUC24 to MIC ratio of over 400 µg•h /ml is higher in the group of patients with Ctrough = 10–15 µg /ml. Our findings confirm that the use of MM in postoperative patients with renal dysfunction is limited and therapeutic drug monitoring should be used instead.

© 2018 Media Sphera Publishing Group. All rights reserved. The relevance of the investigation is due to the need to optimize the system for the primary prevention of drug addiction and use because of its insufficient efficiency in the Russian Federation. This problem is manifested in the low awareness of the population, primarily young people, about the negative consequences of the use of narcotic drugs and psychotropic substances and about the high associated risk of their involvement in the use of narcotics, including new types of psychotropic substances (synthetic narcotics). In this connection, the aim of our investigation was to develop a method for determining the potential efficiency of measures for the primary prevention of drug addiction and use, by applying mathematical modeling. The Kermak - McKendrick epidemic model of the susceptible infected removed (SIR) - like type was used as a basis to build a drug use spread model that represented as transition of groups of individuals from one state to another in relation to drug use. This gave rise to a simulation model estimating the magnitude of a drug use reduction in the risk group in relation to the initial one if varying effective preventive measures were implemented. The drug abuse scenario in case of effective measures was analyzed. Enhancing the effectiveness of measures for primary prevention of drug addiction was shown to lead to a stronger rather than linear decline in the size of a group at risk for drug and in the number of drug users. This model may be used to prepare programs, strategies for the primary prevention of drug addiction to evaluate their potential effectiveness.

© 2018 Sergey S. Simakov. The study of the physiological and pathophysiological processes in the cardiovascular system is one of the important contemporary issues, which is addressed in many works. In this work, several approaches to the mathematical modelling of the blood flow are considered. They are based on the spatial order reduction and/or use a steady-state approach. Attention is paid to the discussion of the assumptions and suggestions, which are limiting the scope of such models. Some typical mathematical formulations are considered together with the brief review of their numerical implementation. In the first part, we discuss the models, which are based on the full spatial order reduction and/or use a steady-state approach. One of the most popular approaches exploits the analogy between the flow of the viscous fluid in the elastic tubes and the current in the electrical circuit. Such models can be used as an individual tool. They also used for the formulation of the boundary conditions in the models using one dimensional (1D) and three dimensional (3D) spatial coordinates. The use of the dynamical compartment models allows describing haemodynamics over an extended period (by order of tens of cardiac cycles and more). Then, the steady-state models are considered. They may use either total spatial reduction or two dimensional (2D) spatial coordinates. This approach is used for simulation the blood flow in the region of microcirculation. In the second part, we discuss the models, which are based on the spatial order reduction to the 1D coordinate. The models of this type require relatively small computational power relative to the 3D models. Within the scope of this approach, it is also possible to include all large vessels of the organism. The 1D models allow simulation of the haemodynamic parameters in every vessel, which is included in the model network. The structure and the parameters of such a network can be set according to the literature data. It also exists methods of medical data segmentation. The 1D models may be derived from the 3D Navier - Stokes equations either by asymptotic analysis or by integrating them over a volume. The major assumptions are symmetric flow and constant shape of the velocity profile over a cross-section. These assumptions are somewhat restrictive and arguable. Some of the current works paying attention to the 1D model's validation, to the comparing different 1D models and the comparing 1D models with clinical data. The obtained results reveal acceptable accuracy. It allows concluding, that the 1D approach can be used in medical applications. 1D models allow describing several dynamical processes, such as pulse wave propagation, Korotkov's tones. Some physiological conditions may be included in the 1D models: gravity force, muscles contraction force, regulation and autoregulation.

© 2018 Limited Liability Company KlinMed Consulting. All Rights Reserved. Nowadays an invasive evaluation of fractional flow reserve (FFR) is one of the main methods used for detecting lesions that cause ischemia. Invasively obtained FFR <0.75 has the specificity of 100%, and FFR >0.80 has the sensitivity >90%. Recent achievements in computational fluid dynamics and computer simulations allow noninvasive assessment of FFR using data obtained by CT angiography performed according to standard protocol at rest without additional radiation, modification of image acquisition protocols, or added medications for vasodilatation. The present review covers the results of the DISCOVER, the NXT, the DEFACTO and the PLATFORM randomized multicenter studies as well as the prospects of using a noninvasive method for measuring FFR developed by specialists of the Institute of Numerical Mathematics in collaboration with specialists of the I. M. Sechenov First Moscow State Medical University.