Development of a new computer model for the simulation of cooking organic aerosol formation from heated cooking oils using aspen plus

Cooking is an important source of particulate matter with adverse effects on human health, particularly in developing countries where simple stoves burning biomass (wood, animal dung, and crop waste) and coal are used [1]. Depending on the components of the food, the composition of cooking organic aerosol (COA) may vary drastically. However, due to loss of volatile organic compounds (VOC) during experiments and numbers of other uncertainties, the exact compositions and rates of COA formation are difficult to be determined. In this thesis, a simulation model for heating corn, soybean and sunflower oils and stir-frying myrcia was developed using Aspen Plus

Solvent-based approaches to evaluate the ABE extractive fermentation

The reindustrialization of ABE fermentation is hampered by significant production costs, linked to high product inhibition and limited intrinsic yield. The reduction of these costs depends on the effective application of integrated toxic product removal techniques. The evaluation of ABE extractive fermentation with solvents of different nature in terms of extraction capacity or biocompatibility is the main objective of this thesis. Attention is focused on the assessment of the solvent influence, not only on the physical effects but also on the metabolism and microbial population dynamics evolution. A mathematical model based on the evolution of the heterogeneous culture inside the bioreactor was proposed and validated ABE extractive fermentation is techno and economically evaluated on a solvent-based comparative basis. The integration of this process within a LCB biorefinery using a 2G type substrate is also considered

Quantum Chemical Lipophilicities of Antimalarial Drugs in Relation to Terminal Half-Life

According to the WHO, artemisinin-based combination therapies (ACTs) have been integral to the recent reduction in deaths due to Plasmodium falciparum malaria. ACT-resistant strains are an emerging problem and have evolved altered developmental stages, reducing exposure of the most susceptible stages to artemisinin drugs in popular ACTs. Lipophilicity, log Kow, is a guide in understanding and predicting pharmacokinetic properties such as terminal half-life which alters drug exposure. Consistent log Kow values are not necessarily available for artemisinin derivatives designed to extend terminal half-life, increase bioavailability, and reduce neurotoxicity. For other drugs used in ACTs, an assortment of experimental and computational log Kow values are available in the literature and in some cases, do not account for subtle but important differences between closely related structures such as between diastereomers. Quantum chemical methods such as density functional theory (DFT) used with an implicit solvent model allow for consistent comparison of physical properties including log Kow and distinguish between closely related structures. To this end, DFT, B3LYP/6-31G(d), with an implicit solvent model (SMD) was used to compute ΔGowo and ΔGvowo for 1-octanol–water and olive oil–water partitions, respectively, for 21 antimalarial drugs: 12 artemisinin-based, 4 4-aminoquinolines and structurally similar pyronaridine, and 4 amino alcohols. The computed ΔGowo was close to ΔGowo calculated from experimental log Kow values from the literature where available, with a mean signed error of 2.3 kJ/mol and mean unsigned error of 3.7 kJ/mol. The results allow assignment of log Kow for α-and β-diastereomers of arteether, and prediction of log Kow for β-DHA and five experimental drugs. Linear least square analysis of log Kow and log Kvow versus terminal elimination half-life showed strong linear relationships, once the data points for the 4-aminoquinoline drugs, mefloquine and pyronaridine were found to follow their own linear relationship, which is consistent with their different plasma protein binding. The linear relationship between the computed log Kvow and terminal elimination half-life was particularly strong, R2 = 0.99 and F = 467, and can be interpreted in terms of a simple pharmacokinetic model. Terminal elimination half-life for β-DHA and four experimental artemisinin drugs were estimated based on this linear relationship between log Kvow and terminal t1/2. The computed log Kow and log Kvow values for epimers α- and β-DHA and α and β-arteether provide physical data that may be helpful in understanding their different pharmacokinetics and activity based on their different molecular geometries. Relative solubility of quinine and quinidine are found to be sensitive to thermal corrections to enthalpy and to vibrational entropy and do not follow the general trend of longer terminal t1/2 with greater predicted log Kow. Geometric relaxation of α- and β-DHA in solvent and inclusion of thermal correction for enthalpy and entropy results in correct prediction that α-DHA is favored in aqueous environments compared to β-DHA. Predictions made regarding experimental drugs have implications regarding their potential use in response to artemisinin drug-resistant strains

Recent Applications of Quantitative Structure-Activity Relationships in Drug Design

One of the most important challenges that face medicinal chemists today is the design of new drugs with improved properties and diminished side-effects for treating human disease such as AIDS and others. Medicinal chemists began the process by taking a lead structure and then finding analogs exhibiting the preferred biological activities. Next, they used their experience and chemical insight to eventually choose a nominee analog for further development. This process is difficult, expensive and took a long time. The conventional methods of drug discovery are now being supplemented by shortest approaches made possible by the accepting of the molecular processes involved in the original disease. In this view, the preliminary point in drug design is the molecular target which is receptor or enzyme in the body as an option of the existence of known lead structure

The distribution of compounds between blood or the gas phase and various biological tissues.

Distribution coefficients, Kbi00d and KtiSSues (or biophase), from the gas phase to blood and gas phase to tissues (plasma, brain, fat, heart, liver, lung, kidney, muscle, urine, saline and olive oil) have been collected for large number of volatile organic compounds (VOCs). For these datasets of VOCs, linear free energy relationships (LFERs) have been established and Abraham equations have successfully been constructed to predict these distributions. It has also been shown that human and rat data for the air to blood and air to tissue distribution of VOCs can be combined. The differences in the two data sets, for the common compounds are smaller than the estimated inter-laboratory experimental error. The combination of the log KtiSSue values with values for air to blood yields distribution coefficients from blood to tissue, as log PtiSSue-Equations have successfully been constructed to predict these distributions. From a large amount of collected data on the distribution of drugs from blood, plasma or serum to tissue (brain, fat, heart, kidney, lung, liver, muscle and skin) at steady-state concentration in rats, it is shown that the three datasets of data can be combined. Predictive LFER equations for blood/plasma/serum to tissue for a large number of drugs, has been achieved and their predictive capability has been assessed. Finally, it has been shown that the in vitro data on VOCs and the in vivo data on drugs can be combined LFERs on the total data yield correlative and predictive Abraham equations. Because the descriptors used in the LFERs can be calculated from structure, distribution coefficients for air to blood or tissue for VOCs and for blood/plasma/serum to tissue for VOCs and drugs can be predicted directly from the molecular structures of the VOCs and drugs

Air to Blood Distribution of Volatile Organic Compounds: A Linear Free Energy Analysis

Partition coefficients, K blood , for volatile organic compounds from air to blood have been collected for 155 compounds (air to human blood) and 127 compounds (air to rat blood). For 86 common compounds, the average error, AE, between the two sets of log K blood values is 0.12 log units, somewhat smaller than our estimated interlaboratory average SD value of around 0.16 log units. We conclude that with regard to experimental errors, there is no significant difference between K blood values in human blood and in rat blood. There are 196 compounds for which either or both K blood (human) and K blood (rat) are available. A training set of 98 compounds could be fitted with the Abraham solvation parameters with R 2 ) 0.933 and SD ) 0.34 log units. The training equation was then used to predict the test set of values with AE ) 0.04 log units, SD ) 0.33 log units, and an average absolute error, AAE, of 0.25 log units. A second training and test set yielded similar values: AE ) 0.01, SD ) 0.39, and AAE ) 0.29 log units. It is concluded that it is possible to construct an equation capable of predicting further values of log K blood to around 0.30 log units. Because the descriptors used in the correlation equations can be predicted from structure, it is now possible to predict log K blood for any chemical structure

Modeling Biphasic Reactors, Emulsions and Selecetion of Solvents

Modeling biphasic reactors (BPRs) facilitates understanding the dynamics between the kinetics and component phase distribution between the two partially miscible phases of the reactor. Using experimental results for bio oil upgrading, an algorithm for the modeling of biphasic reactors describing both reaction kinetics and phase separation was implemented using the simulation of a heterogeneous liquid phase hydrogenation of p-hydroxy benzaldehyde to 4-methylcyclohexanol in a water-decalin mixture. The reaction was represented by the Eley-Rideal type surface reaction mechanism. The Non-Random Two-Liquid (NRTL) phase equilibria model and an interfacial mass transfer model based on the two-film theory was used to assess for representation of the component phase distribution. Aspen Plus and Excel-VBA were used for simulation the reactor. Optimizations was performed to estimate the volumetric interfacial area available for mass transfer. Gibbs energy test was performed to confirm if simultaneous reaction and phase distribution is thermodynamically possible. Quantitative Structure Property Relation (QSPR) based Linear and non-linear models were used to model emulsion properties such as drop size, emulsion fraction, and emulsion type. The model was validated using experimental data, which includes the effects of the water fraction and the organic compounds used on the emulsion properties. The results of the emulsion modeling were used as a basis for selecting a new solvent with the desired emulsion properties such as selective solubility, drop size and type of emulsion, for use in an emulsion formulation and a BPR. QSPR models for emulsion properties, partition and mass transfer coefficient correlation were used to evaluate performances of different solvents for emulsion development for biphasic reactor. The simulation results showed that biphasic reactor could offer selectivity of reaction in the desired phase, separation of products with increased organic phase solubility, and continuation of the upgrading process in the presence of component phase-distribution. The coefficient of determination values for emulsion property modeling are also comparable or better than values reported for QSPR modeling for other emulsion properties. The importance of emulsion modeling and solvent selection for BPRs was demonstrated successfully.Chemical Engineerin

Practical guidelines on the application of migration modelling for the estimation of specific migration

The aim of this practical guidance document is to assist the users of the described diffusion models to predict conservative, upper bound specific migration values from plastic food contact materials for compliance purposes. Explanatory guidance tables and practical examples of migration modelling are provided. This document is an updated version of the report "Estimation of specific migration by generally recognised diffusion models in support of EU Directive 2002/72/EC" (Simoneau, 2010) concerning the current legal basis (Regulation (EU) No 10/2011) and the use of migration models for the estimation of specific migration from plastic multi-layers. This document represents the current validity of the models based on constant periodical evaluations of new experimental migration data performed by the Task Force on Migration Modelling chaired by the Directorate General Joint Research Centre of the European Commission on behalf of Directorate General Health and Consumers. The members of the Task Force are R. Brandsch, C. Dequatre, E.J. Hoekstra, P. Mercea, M.R. Milana, A. Schäfer, C. Simoneau, A. Störmer, X. Trier and O. Vitrac.JRC.I.1-Chemical Assessment and Testin