Using a State-Bounding Observer to Predict the Guaranteed Limits of Drug Amounts in Rats after Oral Administration Based on an Uncertain Pharmacokinetic Model

In the first part of this paper, the problem of using an uncertain pharmacokinetic model is resolved to determine drug concentrations in rats after the oral administration of drug suspensions with and without added tenside. To this end, a generalized pharmacokinetic model determining the guaranteed limits of drug concentrations was designed. Based on this, the design of the so-called state-bounding observer is described in the second part. Rather than being driven by the output of the pharmacokinetic model, the observer can be driven exclusively by a concentration collected from a suitable part of the body and predict the possible risk of the drug concentration not remaining within the therapeutic range for a sufficiently long time. Specifically, the observer determines the upper and lower limits of the concentrations in all the compartments, especially those that are inaccessible for the collection of samples. The proposed approaches are demonstrated by examples

Association, Distribution, Liberation, and Rheological Balances of Alkyldimethylbenzylammonium Chlorides (C12–C16)

It is known that cationic surfactants have an antimicrobial effect and act as enhancers. This paper studies three cationic surfactants from the group of alkyldimethylbenzylammonium chlorides (dodecyl-, tetradecyl-, and hexadecyl). Interest is focused on the association of the surfactants with respect to temperature, partition balances and their influence on drug release, rheological properties, and the pH of hydrogels. The critical micelle concentrations (CMC) of the surfactants were estimated from dependencies of conductivity, density, spectrofluorimetry, and UV–VIS spectrophotometry on molarity in the temperature range of 25–50 °C. It was found that the temperature dependence of a CMC is U-shaped, with its minimum at 30 °C, and the CMC value decreases as the length of the chain increases. The pseudo-phase separation model was used for the calculation of various thermodynamic parameters, such as the Gibbs free energies (spontaneous process), enthalpies (exothermic process), and entropies of the micelles’ formation, CMCs, and the degree of counterion binding. All thermodynamic parameters, as functions of the temperature, were estimated. It was found that partition coefficients increase as the length of the alkyl chain and the pH = (5.0–7.0) increase. The influences of surfactants, below and above the CMC, on drug (chlorhexidine dihydrochloride) release from hydrogels, rheological properties, and pH at 30 °C were studied. Also, the amounts of the released drug increase as the alkyl chains of the surfactants prolongate. The amounts of the released drug with the surfactant below the CMC are greater than that above the CMC. All hydrogels (regardless of the length of the alkyl chain) exhibit a non-Newtonian pseudo-plastic flow. The results obtained will be used in the formulation of the drug and surfactants into dosage forms

Robust Control of Repeated Drug Administration with Variable Doses Based on Uncertain Mathematical Model

The aim of this paper was to design a repeated drug administration strategy to reach and maintain the requested drug concentration in the body. Conservative designs require an exact knowledge of pharmacokinetic parameters, which is considered an unrealistic demand. The problem is usually resolved using the trial-and-error open-loop approach; yet, this can be considered insufficient due to the parametric uncertainties as the dosing strategy may induce an undesired behavior of the drug concentrations. Therefore, the presented approach is rather based on the paradigms of system and control theory. An algorithm was designed that computes the required doses to be administered based on the blood samples. Since repeated drug dosing is essentially a discrete time process, the entire design considers the discrete time domain. We have also presented the idea of applying this methodology for the stabilization of an unstable model, for instance, a model of tumor growth. The simulation experiments demonstrated that all variants of the proposed control algorithm can reach and maintain the desired drug concentration robustly, i.e., despite the presence of parametric uncertainties, in a way that is superior to that of the traditional open-loop approach. It was shown that the closed-loop control with the integral controller and stabilizing state feedback is robust against large parametric uncertainties

Effect of Molecular Composition of Head Group and Temperature on Micellar Properties of Ionic Surfactants with C12 Alkyl Chain

The paper analyses influences of the temperature and hydrophilic groups on micellar properties of ionic surfactants with 12-carbonic hydrophobic chains. The aim is to assess the impact of hydrophilic groups and temperature on thermodynamic parameters and micellization. This knowledge is indispensable for the formulation of new dosage forms. The method uses conductometric measurements. The following hydrophilic groups are analyzed: trimethylammonium bromide, trimethylammonium chloride, ethyldimethylammonium bromide, didodecyldimethylammonium bromide, pyridinium chloride, benzyldimethyl-ammonium chloride, methylephedrinium bromide, cis and trans-[(2-benzyloxy)-cyclohexyl-methyl]-N, N-dimethylammonium bromide, sodium sulphate and lithium sulphate. Except for a few cases, there is a good agreement between values of critical micellar concentrations (CMC) and critical vesicle concentration (CVC) obtained here and those which were obtained by other authors and/or by other physicochemical methods. Values of the CMC are compared with respect to the molar masses of hydrophilic groups. It was found that CMC values increased non-linearly with increasing system temperature. The degrees of counterion binding and thermodynamic parameters, like the standard molar Gibbs energy, enthalpy and entropy of micellization are determined and discussed in detail. The results obtained will be incorporated into in silico processes of modeling and design of optimal dosage forms, a current interdisciplinary research focus of the team

Effects of the application of biochar on the soil erosion of plots of sloping agricultural and with silt loam soil

The application of biochar is considered to be a beneficial strategy for improving soil ecosystem services. The objectives of this study are to evaluate the differences in the soil erosion of silt loam soil with or without the application of biochar and to compare the impact of the application of biochar on soil erosion for different agricultural practices, namely, bare soil, silage corn, and sown peas. Specifically, the physically-based EROSION 3D model was used to estimate the soil erosion of small plots of sloping agricultural land. In considering various combinations of agricultural practices and rainfalls with different durations and intensities, several scenarios were used to assess the impact of the application of biochar on soil erosion

The testing of a multivariate probabilistic framework for reservoir safety evaluation and flood risks assessment in Slovakia: A study on the Parná and Belá Rivers

Intense floods represent a challenge to risk management. While they are multivariate in their nature, they are often studied in practice from univariate perspectives. Classical frequency analyses, which establish a relation between the peak flow or volume and the frequency of exceedance, may lead to improper risk estimations and mitigations. Therefore, it is necessary to study floods as multivariate stochastic events having mutually correlated characteristics, such as peak flood flow, corresponding volume and duration. The joint distribution properties of these characteristics play an important role in the assessment of flood risk and reservoir safety evaluation. In addition, the study of flood hydrographs is useful because of the inherent dependencies among their practice-relevant characteristics present on-site and in the regional records. This study aims to provide risk analysts with a consistent multivariate probabilistic framework using a copula-based approach. The framework respects and describes the dependence structures among the flood peaks, volumes, and durations of observed and synthetic control flood hydrographs. The seasonality of flood generation is respected by separate analyses of floods in the summer and winter seasons. A control flood hydrograph is understood as a theoretical/synthetic discharge hydrograph, which is determined by the flood peak with the chosen probability of exceedance, the corresponding volume, and the time duration with the corresponding probability. The framework comprises five steps: 1. Separation of the observed hydrographs, 2. Analysis of the flood characteristics and their dependence, 3. Modelling the marginal distributions, 4. A copula-based approach for modelling joint distributions of the flood peaks, volumes and durations, 5. Construction of synthetic flood hydrographs. The flood risk assessment and reservoir safety evaluation are described by hydrograph analyses and the conditional joint probabilities of the exceedance of the flood volume and duration conditioned on flood peak. The proposed multivariate probabilistic framework was tested and demonstrated based on data from two contrasting catchments in Slovakia. Based on the findings, the study affirms that the trivariate copula-based approach is a practical option for assessing flood risks and for reservoir safety

The testing of a multivariate probabilistic framework for reservoir safety evaluation and flood risks assessment in Slovakia: A study on the Parná and Belá Rivers

Intense floods represent a challenge to risk management. While they are multivariate in their nature, they are often studied in practice from univariate perspectives. Classical frequency analyses, which establish a relation between the peak flow or volume and the frequency of exceedance, may lead to improper risk estimations and mitigations. Therefore, it is necessary to study floods as multivariate stochastic events having mutually correlated characteristics, such as peak flood flow, corresponding volume and duration. The joint distribution properties of these characteristics play an important role in the assessment of flood risk and reservoir safety evaluation. In addition, the study of flood hydrographs is useful because of the inherent dependencies among their practice-relevant characteristics present on-site and in the regional records. This study aims to provide risk analysts with a consistent multivariate probabilistic framework using a copula-based approach. The framework respects and describes the dependence structures among the flood peaks, volumes, and durations of observed and synthetic control flood hydrographs. The seasonality of flood generation is respected by separate analyses of floods in the summer and winter seasons. A control flood hydrograph is understood as a theoretical/synthetic discharge hydrograph, which is determined by the flood peak with the chosen probability of exceedance, the corresponding volume, and the time duration with the corresponding probability. The framework comprises five steps: 1. Separation of the observed hydrographs, 2. Analysis of the flood characteristics and their dependence, 3. Modelling the marginal distributions, 4. A copula-based approach for modelling joint distributions of the flood peaks, volumes and durations, 5. Construction of synthetic flood hydrographs. The flood risk assessment and reservoir safety evaluation are described by hydrograph analyses and the conditional joint probabilities of the exceedance of the flood volume and duration conditioned on flood peak. The proposed multivariate probabilistic framework was tested and demonstrated based on data from two contrasting catchments in Slovakia. Based on the findings, the study affirms that the trivariate copula-based approach is a practical option for assessing flood risks and for reservoir safety