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    Empirical correlations of drug-and plant-based bioactive compound solubility in supercritical CO2: A comparative evaluation study

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    1-s2.0-S0378381224000384-main.pdf (1.866Mb)
    Date
    2024
    Author
    Obek, Christine Ann
    Saptoro, Agus
    Tiong, Angnes Ngieng Tze
    Jawad, Zeinab Abbas
    Kong, Zong Yang
    Ismadji, Suryadi
    Sunarso, Jaka
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    Abstract
    Over the last few decades, supercritical fluid extraction process has greatly assisted the search for more medicinal and therapeutic properties of bioactive compounds from an extensive range of botanical matrices. The yield of supercritical fluid extraction is often limited by the solubility of a targeted solute in the solvent and thus knowledge on solubility has become one of the fundamental variables of interest in the extraction process. However, the studies to evaluate the performance of density-based empirical models in estimating the solubility of different drug- and plant-based bioactive compounds were scarce. Therefore, this study aimed to gather the solubility data of 33 drugs and 40 plant-based bioactive compounds at varying temperatures and pressures and correlated them with 26 most widely used density-based models. The solubility data were critically analysed and reported from two perspectives: well-studied solubility-influencing factors such as pressure, temperature, and additional influencing factors what o such as molecular structure and weight. Then, a thorough evaluation of the existing empirical solubility models involving 26 predictive models for 73 bioactive compounds was performed. From the results and findings, it was evident that the 8-parameter Belghait et al. model showed the overall highest accuracies indicated by the lowest absolute average relative deviation of 7.42 %, 10.16 %, and 6.57 %, respectively for all bioactive compounds, drug-based bioactive compounds, and plant-based bioactive compounds. Belghait et al. model is also superior since its predictive performances are the best for 54 % of the bioactive compounds studied. Meanwhile, Kumar and Johnston's, Sung and Shim's, and Sodeifian et al's models demonstrated the best solubility predictions for 3-, 4-, and 6-parameter empirical models, respectively, for both plant and drug-based compounds. As the effects of pressure and temperature on solubility have widely acknowledged, this study also highlights the influence of molecular structure complexity on solubility. The main findings from this comparative evaluation proved that density-based models are efficacious in predicting solubility of both plant and drug-based bioactive compounds.
    DOI/handle
    http://dx.doi.org/10.1016/j.fluid.2024.114061
    http://hdl.handle.net/10576/53982
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    • Chemical Engineering [‎1198‎ items ]

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