Molecular architecture influences on material properties of pharmaceutical compounds

Salt formation has extensively been studied as a strategy to improve drug solubility but it has not been explored as a strategy to improve mechanical properties. A better understanding of which factors of the solid state can have an influence in the mechanical properties of pharmaceutical powders can help to optimise and reduce cost of tablet manufacturing. The aim of this study was to form different series of amine salts of flurbiprofen, gemfibrozil and diclofenac and to establish predictive relationships between architectural characteristics and physicochemical and mechanical properties of the salts. For this purpose, three different carboxylic acid drugs were selected: flurbiprofen, gemfibrozil and diclofenac, similar in size but varying in flexibility and shape and three different series of counterions were also chosen: one with increasing bulk and no hydroxyl groups to limit the hydrogen bonding potential; a second one with increasing number of hydroxyl groups and finally a third series, related to the latter in number of hydroxyl groups but with different molecular shape and flexibility. Physico-chemical characterization was performed (DSC, TGA, solubility, intrinsic dissolution rate, particle size, true density) and mechanical properties measured using a compaction replicator. Strained molecular conformations produce weaker compacts as they have higher energy than preferred conformations that usually lie close to energy minimums and oppose plastic deformation. It was observed that slip planes, which correspond to regions of weakest interaction between the planes, were associated with improved plasticity and stronger compacts. Apart from hydrogen bonds, profuse van der Waals forces can result in ineffective slip planes. Salts displaying two-dimensional densely hydrogen bonded layers produced stronger compacts than salts showing one-dimensional networks of non-bonded columns, probably by reducing the attachment energy between layers. When hydrogen bonds are created intramolecularly, it is possible that the mechanical properties are compromised as they do not contribute so much to create twodimensional densely bonded layers and they can force molecules into strained conformations. Some types of hydrogen bonding network may be associated with improved mechanical properties, such as type II, or R (10) 3 4 using graph-set notation, versus type III, or R (12) 4 8 , columns. This work clearly demonstrates the potential of investigating crystal structure-mechanical property relationship in pharmaceutical materials.

Use of amino acids as counterions improves the solubility of the BCS II model drug, indomethacin

The number of new chemical entities (NCE) is increasing every day after the introduction of combinatorial chemistry and high throughput screening to the drug discovery cycle. One third of these new compounds have aqueous solubility less than 20µg/mL [1]. Therefore, a great deal of interest has been forwarded to the salt formation technique to overcome solubility limitations. This study aims to improve the drug solubility of a Biopharmaceutical Classification System class II (BCS II) model drug (Indomethacin; IND) using basic amino acids (L-arginine, L-lysine and L-histidine) as counterions. Three new salts were prepared using freeze drying method and characterised by FT-IR spectroscopy, proton nuclear magnetic resonance ((1)HNMR), Differential Scanning Calorimetry (DSC) and Thermogravimetric analysis (TGA). The effect of pH on IND solubility was also investigated using pH-solubility profile. Both arginine and lysine formed novel salts with IND, while histidine failed to dissociate the free acid and in turn no salt was formed. Arginine and lysine increased IND solubility by 10,000 and 2296 fold, respectively. An increase in dissolution rate was also observed for the novel salts. Since these new salts have improved IND solubility to that similar to BCS class I drugs, IND salts could be considered for possible waivers of bioequivalence.

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Maintained larval growth in mussel larvae exposed to acidified undersaturated seawater

Ocean acidification (OA) is known to affect bivalve early life-stages. We tested responses of blue mussel larvae to a wide range of pH in order to identify their tolerance threshold. Our results confirmed that decreasing seawater pH and decreasing saturation state increases larval mortality rate and the percentage of abnormally developing larvae. Virtually no larvae reared at average pHT 7.16 were able to feed or reach the D-shell stage and their development appeared to be arrested at the trochophore stage. However larvae were capable of reaching the D-shell stage under milder acidification (pHT=7.35, 7.6, 7.85) including in under-saturated seawater with omega Aragonite as low as 0.54±0.01 (mean±s. e. m.), with a tipping point for normal development identified at pHT 7.765. Additionally growth rate of normally developing larvae was not affected by lower pHT despite potential increased energy costs associated with compensatory calcification in response to increased shell dissolution. Overall, our results on OA impacts on mussel larvae suggest an average pHT of 7.16 is beyond their physiological tolerance threshold and indicate a shift in energy allocation towards growth in some individuals revealing potential OA resilience.

Interações da trancinolona com ciclodextrinas em sistemas multicomponentes

Triamcinolone is a relevant anti-inflammatory costicosteroid drug, used mainly by injectable suspensions due its poor water solubility. The association of triamcinolone with cyclodextrins and co-solvents (triethanolamine TEA and N-methylpirrolidone NMP) was held to solubilize the drug and explain the involved interactions. Phase-solubility diagrams showed that triamcinolone was solubilized forming incredible stable complexes with cyclodextrins, in which bests results were observed applying randomyl-methylated-beta-cyclodextrin (RMβCD) (161 fold on increased solubility). The co-solvents TEA and NMP also enhanced drug solubility 1.4 and 6.7 fold, respectively. The association of both co-solvents with CDs seems decreased complexation stability, but enables higher amount of uncomplexed drug. Experimental magnetic resonance 2D-ROESY and theoretical molecular modeling studies demonstrated TRI-CDs interactions and elucidated the structure of formed complex, which occurred due to the inclusion of ring A of TRI on CDs cavity. Physicochemical aspects of solid binary and ternary complexes prepared by spray drying were assessed by using FTIR, X-ray diffraction and SEM photographs. Dissolution studies showed that binary and ternary associations presented higher dissolution efficacy in detrimental to pure drug system. In addition, the ternary complex containing TEA and RMβCD allowed drug dissolution faster than binary complex with RMβCD. Therefore, given the higher solubility and drug dissolution rate, binary and ternary complexes are new raw materials with great potential for pharmaceuticals containing triamcinolone.

Seawater carbonate chemistry and microbioerosion of coral skeletons

Biological mediation of carbonate dissolution represents a fundamental component of the destructive forces acting on coral reef ecosystems. Whereas ocean acidification can increase dissolution of carbonate substrates, the combined impact of ocean acidification and warming on the microbioerosion of coral skeletons remains unknown. Here, we exposed skeletons of the reef-building corals, Porites cylindrica and Isopora cuneata, to present-day (Control: 400 µatm - 24 °C) and future pCO2-temperature scenarios projected for the end of the century (Medium: +230 µatm - +2 °C; High: +610 µatm - +4 °C). Skeletons were also subjected to permanent darkness with initial sodium hypochlorite incubation, and natural light without sodium hypochlorite incubation to isolate the environmental effect of acidic seawater (i.e., Omega aragonite <1) from the biological effect of photosynthetic microborers. Our results indicated that skeletal dissolution is predominantly driven by photosynthetic microborers, as samples held in the dark did not decalcify. In contrast, dissolution of skeletons exposed to light increased under elevated pCO2-temperature scenarios, with P. cylindrica experiencing higher dissolution rates per month (89%) than I. cuneata (46%) in the high treatment relative to control. The effects of future pCO2-temperature scenarios on the structure of endolithic communities were only identified in P. cylindrica and were mostly associated with a higher abundance of the green algae Ostreobium spp. Enhanced skeletal dissolution was also associated with increased endolithic biomass and respiration under elevated pCO2-temperature scenarios. Our results suggest that future projections of ocean acidification and warming will lead to increased rates of microbioerosion. However, the magnitude of bioerosion responses may depend on the structural properties of coral skeletons, with a range of implications for reef carbonate losses under warmer and more acidic oceans.

A Study of the Effect of Oxygen on the Rate of Dissolution of Gold in Cyanide Solutions.

The accepted chemical reactions in the dissolution of gold by cyanide solutions require the presence of gold, cyanide, water, and oxygen. The importance of dissolved oxygen in cyanide solutions as a factor is recognized by those familiar with cyanidation. Manufacturers of cyanidation equipment realize the necessity of oxygen, as shown by the appliances they have developed which are attached to the agitators in order to saturate the cyanide solutions with air.

The Effect of Temperature on the Rate of Dissolution of Gold in Cyanide Solutions which have a Constant Oxygen Content.

Since the development of cyanidation into a highly efficient process for treating gold ores, many papers have been written on its various aspects. Although, there has been much work done on it, the chemistry of the reaction is not yet completely understood.

Seawater carbonate chemistry, survival rate, shell mass growth, shell dissolution and locomotory speed of Limacina retroversa in a laboratory experiment

Anthropogenic carbon dioxide emissions induce ocean acidification, thereby reducing carbonate ion concentration, which may affect the ability of calcifying organisms to build shells. Pteropods, the main planktonic producers of aragonite in the worlds' oceans, may be particularly vulnerable to changes in sea water chemistry. The negative effects are expected to be most severe at high-latitudes, where natural carbonate ion concentrations are low. In this study we investigated the combined effects of ocean acidification and freshening on Limacina retroversa, the dominant pteropod in sub polar areas. Living L. retroversa, collected in Northern Norwegian Sea, were exposed to four different pH values ranging from the pre-industrial level to the forecasted end of century ocean acidification scenario. Since over the past half-century the Norwegian Sea has experienced a progressive freshening with time, each pH level was combined with a salinity gradient in two factorial, randomized experiments investigating shell degradation, swimming behavior and survival. In addition, to investigate shell degradation without any physiologic influence, one perturbation experiments using only shells of dead pteropods was performed. Lower pH reduced shell mass whereas shell dissolution increased with pCO2. Interestingly, shells of dead organisms had a higher degree of dissolution than shells of living individuals. Mortality of Limacina retroversa was strongly affected only when both pH and salinity reduced simultaneously. The combined effects of lower salinity and lower pH also affected negatively the ability of pteropods to swim upwards. Results suggest that the energy cost of maintaining ion balance and avoiding sinking (in low salinity scenario) combined with the extra energy cost necessary to counteract shell dissolution (in high pCO2 scenario), exceed the available energy budget of this organism causing the pteropods to change swimming behavior and begin to collapse. Since L. retroversa play an important role in the transport of carbonates to the deep oceans these findings have significant implications for the mechanisms influencing the inorganic carbon cycle in the sub-polar area.