Prediction of the best cosolvents to solubilise fatty acids in supercritical CO2 using the Hansen solubility theory

Tenorio, Maria; Cabañas, Albertina; Tirado, Diego F.

doi:10.1016/j.ces.2018.06.017

Cited by 22 publications

(21 citation statements)

References 23 publications

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“…The distance between coordinates of the target compound (centre of mass of the Hansen sphere represented by δd1, δp1, δh1) and those of the tested compound (δd2, δp2, δh2) is represented by the HSP distance. The HSP distance (Ra) between NFD, solvents (ethanol and ethyl acetate selected for their low toxicity and Food Grade suitability), and filaments (PVA, PLA, and HS) was calculated in order to predict their miscibility (Equation (5)); the smaller the Ra value, the larger the miscibility of two components [25,26].…”

Section: Diffusion Kinetics Mathematical Modellingmentioning

confidence: 99%

“…Hansen Solubility Parameters for solvents, filaments, and NFD were calculated using the van Krevelen contribution method [43], and Ra values determined ( Table 3). The smaller the value of Ra, the larger the miscibility [25,26]. Ethanol possesses a much greater Ra with NFD than ethyl acetate (13.7 versus 3.3) and this can explain why NFD has a much larger solubility in ethyl acetate than in ethanol, as the latter is a more polar solvent with a higher capacity to hydrogen bond.…”

Section: Diffusion Kinetic Studies and Physicochemical Characterisationmentioning

confidence: 99%

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Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms

et al. 2020

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Although not readily accessible yet to many community and hospital pharmacists, fuse deposition modelling (FDM) is a 3D printing technique that can be used to create a 3D pharmaceutical dosage form by employing drug loaded filaments extruded via a nozzle, melted and deposited layer by layer. FDM requires printable filaments, which are commonly manufactured by hot melt extrusion, and identifying a suitable extrudable drug-excipient mixture can sometimes be challenging. We propose here the use of passive diffusion as an accessible loading method for filaments that can be printed using FDM technology to allow for the fabrication of oral personalised medicines in clinical settings. Utilising Hansen Solubility Parameters (HSP) and the concept of HSP distances (Ra) between drug, solvent, and filament, we have developed a facile pre-screening tool for the selection of the optimal combination that can provide a high drug loading (a high solvent-drug Ra, >10, and an intermediate solvent–filament Ra value, ~10). We have identified that other parameters such as surface roughness and stiffness also play a key role in enhancing passive diffusion of the drug into the filaments. A predictive model for drug loading was developed based on Support Vector Machine (SVM) regression and indicated a strong correlation between both Ra and filament stiffness and the diffusion capacity of a model BCS Class II drug, nifedipine (NFD), into the filaments. A drug loading, close to 3% w/w, was achieved. 3D printed tablets prepared using a PVA-derived filament (Hydrosupport, 3D Fuel) showed promising characteristics in terms of dissolution (with a sustained release over 24 h) and predicted chemical stability (>3 years at 25 °C/60% relative humidity), similar to commercially available NFD oral dosage forms. We believe FDM coupled with passive diffusion could be implemented easily in clinical settings for the manufacture of tailored personalised medicines, which can be stored over long periods of time (similar to industrially manufactured solid dosage forms).

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Section: Diffusion Kinetics Mathematical Modellingmentioning

confidence: 99%

Section: Diffusion Kinetic Studies and Physicochemical Characterisationmentioning

confidence: 99%

Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms

et al. 2020

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“…However, it has recently received special attention for its usefulness as a predictive tool for the dissolution of an analyte in a particular solvent. Some recent applications for the extraction of compounds from natural sources include the prediction of the best cosolvents to solubilise fatty acids in supercritical CO2 [25], the selection of bio-based solvents for the selective extraction of tannins from algae [23], carotenoids from microalgae [24], betulin from birch bark [21] and the study of β-carotene and lutein solubility in supercritical CO2 [22]. HSP estimation is based on the principle of "like dissolves like" and it can be very favourable to obtain a first approximation for selective extraction processes, indicating the most suitable solvent(s) for a given application, avoiding the selection of impractical experimental conditions [24].…”

Section: Theoretical Selection Of the Bio-based Solvents For Whitanolmentioning

confidence: 99%

“…The selection of a suitable solvent for the extraction of the target bioactive, in agreement with green chemistry principles, is also a critical issue for the development of a sustainable valorisation process. In this regard, Hansen solubility parameters (HSP) have been recently employed as a useful tool to selectively extract valuable compounds from natural sources, employing PLE as extraction technique [21][22][23][24][25][26]. This theoretical approach is based on the estimation of HSP of the target compound in order to choose the most appropriate extraction solvent, thus reducing the number of experiments and solvent consumption [21,27].…”

Section: Introductionmentioning

confidence: 99%

A multi-analytical platform based on pressurized-liquid extraction, in vitro assays and liquid chromatography/gas chromatography coupled to high resolution mass spectrometry for food by-products valorisation. Part 1: Withanolides-rich fractions from goldenberry (Physalis peruviana L.) calyces obtained after extraction optimization as case study

Ballesteros-Vivas¹,

Álvarez‐Rivera

Sánchez‐Camargo

et al. 2019

Journal of Chromatography A

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In this work, a multi-analytical platform that allows obtaining and characterizing high-added value compounds from natural sources is presented, with a huge potential in traditional medicine, natural products characterization, functional foods, etc. Namely, the proposed multianalytical platform is based on the combination of pressurized liquid extraction (PLE), liquid chromatography (LC) and gas chromatography quadrupole time-of-flight mass spectrometry GC-q-TOF-MS(/MS), in vitro assays and modelling tools for guiding extraction optimization. As case study, goldenberry or cape gooseberry fruit (Physalys peruviana L.) was selected. In particular, the potential of P. peruviana calyces, an important by-product of goldenberry processing, as promising source of bioactive compounds was evaluated. Selection of the most suitable solvent for PLE was based on the Hansen solubility parameters (HSP) approach using 4β-hydroxywithanolide E (4βHWE) and withanolide E (WE) as target compounds due to their bioactive potential. A surface response methodology was further applied for the optimization of the PLE parameters: temperature (50, 100 and 150 ºC) and solvent composition (% EtOH in the mixture EtOH/EtOAc). The effects of the independent variables on extraction yield, withanolides content (4βHWE and WE), total phenolic content (TPC), total flavonoids content (TFC) and antioxidant activity (EC50 and TEAC) were evaluated in order to obtain withanoliderich extracts from P. peruviana calyces. The extract obtained under optimal conditions (at 125 °C and 75% EtOH v/v) exhibited satisfactory extraction yield (14.7 %) and moderate antioxidant activity (with an EC50 value of 77.18 µg mL-1 and 1.08 mM trolox g-1), with 4βHWE and WE concentrations of 8.8 and 2.3 mg g-1 , respectively. LC-q-TOF-MS/MS analysis of the extract allowed the quantitation of 4βHWE and WE and the tentative identification of several other withanolides structures. The obtained results demonstrate the great potential of this multi-analytical approach for developing valorization strategies of food 4 by-products under sustainable conditions, to obtain bioactive-enriched extracts with potential medicinal or health-promoting properties.

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“…The calculation of the Hansen parameter values for scCO 2 -ethanol mixtures has been made previously [14,15] and was used in practice recently [16]. It is clear, that not all aspects are explained only by solubility, for example the solute Antoine constants have an important effect in extraction processes [16]. It is important to mention, that the exact solubility values for different substances may not be predicted by the Hansen method, only a fuzzylike (as good solvent or not) prediction is possible.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Increasing the Prediction Efficiency of Hansen Solubility Parameters in Supercritical Fluids

András¹,

Mátyás

Ráduly

et al. 2019

Period. Polytech. Chem. Eng.

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This work describes a simplified method developed for calculating the Hansen parameters (HSPs) for scCO2-polar modifier solvent mixtures. The method consists in fitting 2nd order equations on the calculated values of HSPs of pure components in function of pressure and temperature. It has been proved that these equations are suitable for the characterization of the above system. The current work also proposes a modified representation method, which eliminates the shortcomings of the original ternary Teas diagram, normally used for the representation of the Hansen parameters. On the one hand, the Teas diagram uses quantities without any physical meaning and, on the other hand, the illustration of the solubility information is distorted because it does not take into account the differences of the Hildebrand parameters of different solvents. The factors we have chosen to represent on the ternary diagram possess physical meaning (cohesion energy density partitions). The distortion was eliminated by extending the Teas diagram to a prismatic three dimensional representation. We proved that the Hansen-ellipsoid from the Cartesian coordinate system (dd = f (δH, dp)) is transformed in an ellipsoid also in the new coordinate system (the transformation is pseudo-isomorphic). Nonetheless, the suggested corrections improve the accuracy of the Hansen method, in some cases the interactions between the solvents and the dissolved materials are still not predicted with sufficient accuracy. Most probably a thermodynamic-based correction of the values of the HSPs of small molecules could lead to a significant improvement of the predictive ability of the newly developed method.

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Prediction of the best cosolvents to solubilise fatty acids in supercritical CO2 using the Hansen solubility theory

Cited by 22 publications

References 23 publications

Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms

Personalised 3D Printed Medicines: Optimising Material Properties for Successful Passive Diffusion Loading of Filaments for Fused Deposition Modelling of Solid Dosage Forms

Increasing the Prediction Efficiency of Hansen Solubility Parameters in Supercritical Fluids

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