On Molecular-Based Equations of State: Perturbation Theories, Simple Models, and SAFT Modeling

Nezbeda, Ivó

doi:10.3389/fphy.2020.00287

Cited by 12 publications

(7 citation statements)

References 101 publications

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“…Furthermore, even if all relevant interactions were included in the model, it should be kept in mind that SAFT-type models use a general EOS expression derived using perturbation theories from simplified force fields, which typically only qualitatively describe the real interactions of the given substance(s). 83 Therefore, the quantitative results of the SAFT-type models rely on parametrization. Thus, from the results presented in this study, it cannot be clearly identified whether the large errors found for the selfassociating polymers originate from their high M, the absence of description of some type(s) of interactions (intra-HB or others), or other effects.…”

Section: Resultsmentioning

confidence: 99%

Can Pure Predictions of Activity Coefficients from PC-SAFT Assist Drug–Polymer Compatibility Screening?

Pavliš,

Mathers,

Fulem

et al. 2023

Mol. Pharmaceutics

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The bioavailability of poorly water-soluble active pharmaceutical ingredients (APIs) can be improved via the formulation of an amorphous solid dispersion (ASD), where the API is incorporated into a suitable polymeric carrier. Optimal carriers that exhibit good compatibility (i.e., solubility and miscibility) with given APIs are typically identified through experimental means, which are routinely labor- and cost-inefficient. Therefore, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state, a popular thermodynamic model in pharmaceutical applications, is examined in terms of its performance regarding the computational pure prediction of API–polymer compatibility based on activity coefficients (API fusion properties were taken from experiments) without any binary interaction parameters fitted to API–polymer experimental data (that is, k ij = 0 in all cases). This kind of prediction does not need any experimental binary information and has been underreported in the literature so far, as the routine modeling strategy used in the majority of the existing PC-SAFT applications to ASDs comprised the use of nonzero k ij values. The predictive performance of PC-SAFT was systematically and thoroughly evaluated against reliable experimental data for almost 40 API–polymer combinations. We also examined the effect of different sets of PC-SAFT parameters for APIs on compatibility predictions. Quantitatively, the total average error calculated over all systems was approximately 50% in the weight fraction solubility of APIs in polymers, regardless of the specific API parametrization. The magnitude of the error for individual systems was found to vary significantly from one system to another. Interestingly, the poorest results were obtained for systems with self-associating polymers such as poly(vinyl alcohol). Such polymers can form intramolecular hydrogen bonds, which are not accounted for in the PC-SAFT variant routinely applied to ASDs (i.e., that used in this work). However, the qualitative ranking of polymers with respect to their compatibility with a given API was reasonably predicted in many cases. It was also predicted correctly that some polymers always have better compatibility with the APIs than others. Finally, possible future routes to improve the cost–performance ratio of PC-SAFT in terms of parametrization are discussed.

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Section: Resultsmentioning

confidence: 99%

Can Pure Predictions of Activity Coefficients from PC-SAFT Assist Drug–Polymer Compatibility Screening?

Pavliš,

Mathers,

Fulem

et al. 2023

Mol. Pharmaceutics

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“…In theoretical study ( Vlcek and Nezbeda, 2004b ), Vlcek and Nezbeda reported results for the PM up to β ≡ ϵ SW / k B T = 8. Since relating the PM to the full water model is not, in principle, correct ( Nezbeda, 2020 ) and because of ambiguity of its value, we decided to use also the lowest temperature, β = 8. As regards density, as a consequence of its relatively open structure, liquid water packing fraction is lower than that of, e.g., argon-like fluids.…”

Section: Resultsmentioning

confidence: 99%

Structure of Simple Dipolar Water-Like Fluids: Primitive Model and Hard Tetrahedra

Nezbeda

2021

Front. Chem.

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Dipolar versions of two qualitatively different types of simple short range model fluids which exhibit the phenomenon of hydrogen bonding and which could thus serve as a reference in equations of state for associating fluids have been considered: the primitive model of water descending from the TIP4P model and the fluid of hard tetrahedra. The hydrogen bonding structure exhibited by the latter model results from purely repulsive interactions whereas in the first model the “hydrogen bonding interaction” is explicitly incorporated in the model. Since the water molecules bear a strong dipole moment, the effect of the added dipole-dipole interaction on the structure of the two short-range models is therefore examined considering them both in the full and screened dipole-dipole modifications. It is found that the hydrogen bonding structure in the primitive model resulting from the site-site interactions is so strong that the additional dipole-dipole interaction has only a marginal effect on its structure and contributes thus only to the internal energy. On the contrary, even only a weak dipole-dipole interaction destroys the original hydrogen bonding structure of the hard tetrahedron fluid; to preserve it, a screened dipole-dipole interaction has to be used in the equation of state development.

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“…This also applies to PC-SAFT, as it is based on the fitting of experimental data as a result of its semi-empirical nature. 37 PC-SAFT parameters for solvents are routinely identified by fitting them to experimental data on liquid density (ρ liq ) and vapor pressure (p s ). APIs and other low-volatile and high-melting chemicals, for which ρ liq and p s data may be hardly accessible, are parametrized against their experimental solubility data in pure solvents.…”

Section: Introductionmentioning

confidence: 99%

“…For a model to perform reasonably, not only is the underlying theory critical but also the parametrization approach concerning individual chemicals and mixtures. This also applies to PC-SAFT, as it is based on the fitting of experimental data as a result of its semi-empirical nature . PC-SAFT parameters for solvents are routinely identified by fitting them to experimental data on liquid density (ρ liq ) and vapor pressure ( p s ).…”

Section: Introductionmentioning

confidence: 99%

Purely Predicting the Pharmaceutical Solubility: What to Expect from PC-SAFT and COSMO-RS?

Klajmon

2022

Mol. Pharmaceutics

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A pair of popular thermodynamic models for pharmaceutical applications, namely, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state and the conductor-like screening model for real solvents (COSMO-RS), are thoroughly benchmarked for their performance in predicting the solubility of active pharmaceutical ingredients (APIs) in pure solvents. The ultimate goal is to provide an illustration of what to expect from these progressive frameworks when applied to the thermodynamic solubility of APIs based on activity coefficients in a purely predictive regime without specific experimental solubility data (the fusion properties of pure APIs were taken from experiments). While this kind of prediction represents the typical modus operandi of the first-principles-aided COSMO-RS, PC-SAFT is a relatively highly parametrized model that relies on experimental data, against which its pure-substance and binary interaction parameters (kij) are fitted. Therefore, to make this benchmark as fair as possible, we omitted any binary parameters of PC-SAFT (that is, kij = 0 in all cases) and preferred pure-substance parameter sets for APIs not trained to experimental solubility data. This computational approach, together with a detailed assessment of the obtained solubility predictions against a large experimental data set, revealed that COSMO-RS convincingly outperformed PC-SAFT both qualitatively (that is, COSMO-RS was better in solvent ranking) and quantitatively, even though the former is independent of both substance-and mixture-specific experimental data. Regarding quantitative comparison, COSMO-RS outperformed PC-SAFT for nine of the ten APIs and for 63 % of the API-solvent systems, with root-mean-square deviations of the predicted data from the entire experimental data set being 0.82 and 1.44 log units, respectively.The results were further analyzed to expand the picture of the performance of both models with respect to the individual APIs and solvents. Interestingly, in many cases, both models were found to qualitatively incorrectly predict the direction of deviations from ideality. Furthermore, we examined how the solubility predictions from both models are sensitive to different API parametrizations.

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On Molecular-Based Equations of State: Perturbation Theories, Simple Models, and SAFT Modeling

Cited by 12 publications

References 101 publications

Can Pure Predictions of Activity Coefficients from PC-SAFT Assist Drug–Polymer Compatibility Screening?

Can Pure Predictions of Activity Coefficients from PC-SAFT Assist Drug–Polymer Compatibility Screening?

Structure of Simple Dipolar Water-Like Fluids: Primitive Model and Hard Tetrahedra

Purely Predicting the Pharmaceutical Solubility: What to Expect from PC-SAFT and COSMO-RS?

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