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The ionizable-lipid component of RNA-containing nanoparticles controls the pH-dependent behavior necessary for an efficient delivery of the cargo—the so-called endosomal escape. However, it is still an empirical exercise to identify optimally performing lipids. Here, we study two well-known ionizable lipids, DLin-MC3-DMA and DLin-DMA using a combination of experiments, multiscale computer simulations, and electrostatic theory. All-atom molecular dynamics simulations, and experimentally measured polar headgroup pKa values, are used to develop a coarse-grained representation of the lipids, which enables the investigation of the pH-dependent behavior of lipid nanoparticles (LNPs) through Monte Carlo simulations, in the absence and presence of RNA molecules. Our results show that the charge state of the lipids is determined by the interplay between lipid shape and headgroup chemistry, providing an explanation for the similar pH-dependent ionization state observed for lipids with headgroup pKa values about one-pH-unit apart. The pH dependence of lipid ionization is significantly influenced by the presence of RNA, whereby charge neutrality is achieved by imparting a finite and constant charge per lipid at intermediate pH values. The simulation results are experimentally supported by measurements of α-carbon 13C-NMR chemical shifts for eGFP mRNA LNPs of both DLin-MC3-DMA and DLin-DMA at various pH conditions. Further, we evaluate the applicability of a mean-field Poisson–Boltzmann theory to capture these phenomena. [ABSTRACT FROM AUTHOR]

Lipid nanoparticles (LNPs) are advanced core-shell particles for messenger RNA (mRNA) based therapies that are made of polyethylene glycol (PEG) lipid, distearoylphosphatidylcholine (DSPC), cationic ionizable lipid (CIL), cholesterol (chol), and mRNA. Yet the mechanism of pH-dependent response that is believed to cause endosomal release of LNPs is not well understood. Here, we show that eGFP (enhanced green fluorescent protein) protein expression in the mouse liver mediated by the ionizable lipids DLin-MC3-DMA (MC3), DLin-KC2-DMA (KC2), and DLinDMA (DD) ranks MC3 = KC2 > DD despite similar delivery of mRNA per cell in all cell fractions isolated. We hypothesize that the three CIL-LNPs react differently to pH changes and hence study the structure of CIL/chol bulk phases in water. Using synchrotron X-ray scattering a sequence of ordered CIL/chol mesophases with lowering pH values are observed. These phases show isotropic inverse micellar, cubic Fd3m inverse micellar, inverse hexagonal HII and bicontinuous cubic Pn3m symmetry. If polyadenylic acid, as mRNA surrogate, is added to CIL/chol, excess lipid coexists with a condensed nucleic acid lipid Hc II phase. The next-neighbor distance in the excess phase shows a discontinuity at the Fd3m inverse micellar to inverse hexagonal HII transition occurring at pH 6 with distinctly larger spacing and hydration for DD vs. MC3 and KC2. In mRNA LNPs, DD showed larger internal spacing, as well as retarded onset and reduced level of DD-LNP-mediated eGFP expression in vitro compared to MC3 and KC2. Our data suggest that the pH-driven Fd3m-H II transition in bulk phases is a hallmark of CIL-specific differences in mRNA LNP efficacy. [ABSTRACT FROM AUTHOR]

Lipid nanoparticles (LNPs) are currently used to transport functional mRNAs, such as COVID‐19 mRNA vaccines. The delivery of angiogenic molecules, such as therapeutic VEGF‐A mRNA, to ischemic tissues for producing new blood vessels is an emerging strategy for the treatment of cardiovascular diseases. Here, the authors deliver VEGF‐A mRNA via LNPs and study stoichiometric quantification of their uptake kinetics and how the transport of exogenous LNP‐mRNAs between cells is functionally extended by cells' own vehicles called extracellular vesicles (EVs). The results show that cellular uptake of LNPs and their mRNA molecules occurs quickly, and that the translation of exogenously delivered mRNA begins immediately. Following the VEGF‐A mRNA delivery to cells via LNPs, a fraction of internalized VEGF‐A mRNA is secreted via EVs. The overexpressed VEGF‐A mRNA is detected in EVs secreted from three different cell types. Additionally, RNA‐Seq analysis reveals that as cells' response to LNP‐VEGF‐A mRNA treatment, several overexpressed proangiogenic transcripts are packaged into EVs. EVs are further deployed to deliver VEGF‐A mRNA in vitro and in vivo. Upon equal amount of VEGF‐A mRNA delivery via three EV types or LNPs in vitro, EVs from cardiac progenitor cells are the most efficient in promoting angiogenesis per amount of VEGF‐A protein produced. Intravenous administration of luciferase mRNA shows that EVs could distribute translatable mRNA to different organs with the highest amounts of luciferase detected in the liver. Direct injections of VEGF‐A mRNA (via EVs or LNPs) into mice heart result in locally produced VEGF‐A protein without spillover to liver and circulation. In addition, EVs from cardiac progenitor cells cause minimal production of inflammatory cytokines in cardiac tissue compared with all other treatment types. Collectively, the data demonstrate that LNPs transform EVs as functional extensions to distribute therapeutic mRNA between cells, where EVs deliver this mRNA differently than LNPs. [ABSTRACT FROM AUTHOR]

The free energy perturbation method is employed to study the free energy of solvation of a drug molecule in its pure drug melt, which is supposed to be considered the second step in predicting the solubility of drugs in water. The analysis reveals contradictory results, revealing that the Coulomb interactions are much weaker in pure drug systems, whereas the van der Waals interactions are extremely important and highly influence the interaction.

The study uses the free energy of the perturbation method and the optimized potential for the liquid simulations to take the first step for the computational prediction of drug solubility by measuring the free energy of hydration. The analysis provides an accurate demonstration of the macroscopic surface tension of water, which is not in agreement with the surface tension for water around a spherical cavity that normally is supposed to be dependent on the size of the cavity.

The RNA that is packaged into exosomes is termed as exosomal-shuttle RNA (esRNA); however, the players, which take this subset of RNA (esRNA) into exosomes, remain largely unknown. We hypothesized that RNA binding proteins (RBPs) could serve as key players in this mechanism, by making complexes with RNAs and transporting them into exosomes during the biosynthesis of exosomes. Here, we demonstrate the presence of 30 RBPs in exosomes that were shown to form RNA–RBP complexes with both cellular RNA and exosomal-RNA species. To assess the involvement of these RBPs in RNA-transfer into exosomes, the gene transcripts encoding six of the proteins identified in exosomes (HSP90AB1, XPO5, hnRNPH1, hnRNPM, hnRNPA2B1, and MVP) were silenced by siRNA and subsequent effect on esRNA was assessed. A significant reduction of total esRNA was observed by post-transcriptional silencing of MVP, compared to other RBPs. Furthermore, to confirm the binding of MVP with esRNA, a biotinylated-MVP was transiently expressed in HEK293F cells. Higher levels of esRNA were recovered from MVP that was eluted from exosomes of transfected cells, as compared to those of non-transfected cells. Our data indicate that these RBPs could end up in exosomes together with RNA molecules in the form of RNA–ribonucleoprotein complexes, which could be important for the transport of RNAs into exosomes and the maintenance of RNAs inside exosomes. This type of maintenance may favor the shuttling of RNAs from exosomes to recipient cells in the form of stable complexes. [ABSTRACT FROM AUTHOR]

Secondary nucleation, wherein crystal seeds are used to induce crystallization, is widely employed in industrial crystallizations. Despite its significance, our understanding of the process, particularly at the molecular level, remains rudimentary. An outstanding question is why do a few seeds give rise to a many-fold increase in new crystals? Using molecular simulation coupled with experiments we have uncovered the molecular processes that give rise to this autocatalytic behavior The simulations reveal formation of molecular aggregates in solution, which on coming in contact with the surface of the seed undergo nucleation to form new crystallites. These crystallites are weakly bound to the crystal surface and can be readily sheared by fluid, making the seed surfaces available again to repeat the process. Further, the new crystallites on development can in turn serve as seeds. This mechanistic insight will enable better control in engineering crystalline products to design. [ABSTRACT FROM AUTHOR]

A proper mechanistic understanding of the deaggregation process of small colloidal particle aggregates is of generic importance within many fields of science and engineering. The methodology for modeling colloidal deaggregation is currently limited to analytical solutions in the two-particle case and time consuming numerical algorithms, such as Brownian Dynamics (BD) simulations, for many-particle aggregates. To address this issue, a simplified alternative model that describes deaggregation of few-particle aggregates is presented. The model includes end-particle deaggregation and a particle reconfiguration mechanism, which are the two most important mechanisms for deaggregation. Comparison of the calculated first passage time distribution for various two-, three-, four-, and five-particle aggregates with the corresponding result using BD simulations confirms the validity of the model. It is concluded that the dominating mechanism behind deaggregation can be quantified using a deaggregation number, which reflects the time scale for reconfiguration relative to the time scale for end-particle deaggregation. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1863-1869, 2014 [ABSTRACT FROM AUTHOR]

In view of the extreme importance of reliable computational prediction of aqueous drug solubility, we have established a Monte Carlo simulation procedure which appears, in principle, to yield reliable solubilities even for complex drug molecules. A theory based on judicious application of linear response and mean field approximations has been found to reproduce the computationally demanding free energy determinations by simulation while at the same time offering mechanistic insight. The focus here is on the suitability of the model of both drug and solvent, i.e., the force fields. The optimized potentials for liquid simulations all atom (OPLS-AA) force field, either intact or combined with partial charges determined either by semiempirical AM1/CM1A calculations or taken from the condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field has been used. The results illustrate the crucial role of the force field in determining drug solubilities. The errors in interaction energies obtained by the simple force fields tested here are still found to be too large for our purpose but if a component of this error is systematic and readily removed by empirical adjustment the results are significantly improved. In fact, consistent use of the OPLS-AA Lennard-Jones force field parameters with partial charges from the COMPASS force field will in this way produce good predictions of amorphous drug solubility within 1 day on a standard desktop PC. This is shown here by the results of extensive new simulations for a total of 47 drug molecules which were also improved by increasing the water box in the hydration simulations from 500 to 2000 water molecules. © 2008 Wiley Periodicals, Inc. J Comput Chem, 2009 [ABSTRACT FROM AUTHOR]

A stabilized high drug load intravenous formulation could allow compounds with less optimal pharmacokinetic profiles to be developed. Polyethylene glycol (PEG)-ylation is a frequently used strategy for particle delivery systems to avoid the liver, thereby extending blood circulation time. The present work reports the mouse in vivo distribution after i.v. administration of a series of nanocrystals prepared with the bead milling technique and PEG-ylated with DSPE-PEG2000 and Pluronic F127, with and without polyvinylpyrrolidone K30 (PVP)/Aerosol OT (AOT) as primary stabilizers. While all formulations were cleared significantly faster than expected from nanocrystal dissolution alone, purely DSPE-PEG2000 PEG-ylated particles displayed prolonged circulation time (particles elimination half-life of 9 min) compared to DSPE-PEG2000/PVP/AOT formulation (half-life of 3 min). The two Pluronic F127 stabilized formulations displayed similar half-lives (9 min with and without PVP/AOT, respectively). Whole tissue kinetics shows that clearance of particles could be attributed to accumulation in the liver. A separate in vivo study addressed the liver cell distribution after administration. Dissolved compound accumulated in hepatocytes only, while particles were distributed between liver sinusoidal endothelial cells and Kupffer cells. More DSPE-PEG2000/PVP/AOT stabilized particles accumulated in the liver, preferably in Kupffer cells, compared to Pluronic F127/PVP/AOT stabilized particles. The present study extends the understanding of PEG-ylation and “stealth” behaviour to also include nanocrystals. [ABSTRACT FROM AUTHOR]

Background: Recent experimental data support the view that signaling activity at the membrane depends on its geometric parameters such as surface area and curvature. However, a mathematical, biophysical concept linking shape to receptor signaling is missing. The membranes of cardiomyocytes are constantly reshaped due to cycles of contraction and relaxation. According to constant-volume behavior of cardiomyocyte contraction, the length shortening is compensated by Z-disc myofilament lattice expansion and dynamic deformation of membrane between two adjacent Z-discs. Both morphological changes are strongly dependent on the frequency of contraction. Here, we developed the hypothesis that dynamic geometry of cardiomyocytes could be important for their plasticity and signaling. This effect may depend on the frequency of the beating heart and may represent a novel concept to explain how changes in frequency affect cardiac signaling. Methods: This hypothesis is almost impossible to answer with experiments, as the in-vitro cardiomyocytes are almost two-dimensional and flattened rather than being in their real in-vivo shape. Therefore, we designed a COMSOL multiphysics program to mathematically model the dynamic geometry of a human cardiomyocyte and explore whether the beating frequency can modulate membrane signal transduction. Src kinase is an important component of cardiac mechanotransduction. We first presented that Src mainly localizes at costameres. Then, the frequency-dependent signaling effect was studied mathematically by numerical simulation of Src-mediated PDGFR signaling pathway. The reaction-convection-diffusion partial differential equation was formulated to simulate PDGFR pathway in a contracting sarcomeric disc for a range of frequencies from 1 to 4 Hz. Results: Simulations exhibits higher concentration of phospho-Src when a cardiomyocyte beats with higher rates. The calculated phospho-Src concentration at 4, 2, and 1 Hz beat rates, comparing to 0 Hz, was 21.5%, 9.4%, and 4.7% higher, respectively. Conclusion: Here we provide mathematical evidence for a novel concept in biology. Cell shape directly translates into signaling, an effect of importance particularly for the myocardium, where cells continuously reshape their membranes. The concept of locality of surface-to-volume ratios is demonstrated to lead to changes in membrane-mediated signaling and may help to explain the remarkable plasticity of the myocardium in response to biomechanical stress., Competing Interests: Author JW was employed by the company Wendelsbergs beräkningskemi AB. Authors LL and RK were employed by the company AstraZeneca. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Haftbaradaran Esfahani, Westergren, Lindfors and Knöll.)

Detection of nucleic acids within subcellular compartments is key to understanding their function. Determining the intracellular distribution of nucleic acids requires quantitative retention and estimation of their association with different organelles by immunofluorescence microscopy. This is particularly important for the delivery of nucleic acid therapeutics, which depends on endocytic uptake and endosomal escape. However, the current protocols fail to preserve the majority of exogenously delivered nucleic acids in the cytoplasm. To solve this problem, by monitoring Cy5-labeled mRNA delivered to primary human adipocytes via lipid nanoparticles (LNP), we optimized cell fixation, permeabilization, and immunostaining of a number of organelle markers, achieving quantitative retention of mRNA and allowing visualization of levels that escape detection using conventional procedures. The optimized protocol proved effective on exogenously delivered siRNA, miRNA, as well as endogenous miRNA. Our protocol is compatible with RNA probes of single molecule fluorescence in situ hybridization (smFISH) and molecular beacon, thus demonstrating that it is broadly applicable to study a variety of nucleic acids in cultured cells., (© 2022 Paramasivam et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.)

Delivery of exogenous mRNA using lipid nanoparticles (LNPs) is a promising strategy for therapeutics. However, a bottleneck remains in the poor understanding of the parameters that correlate with endosomal escape versus cytotoxicity. To address this problem, we compared the endosomal distribution of six LNP-mRNA formulations of diverse chemical composition and efficacy, similar to those used in mRNA-based vaccines, in primary human adipocytes, fibroblasts, and HeLa cells. Surprisingly, we found that total uptake is not a sufficient predictor of delivery, and different LNPs vary considerably in endosomal distributions. Prolonged uptake impaired endosomal acidification, a sign of cytotoxicity, and caused mRNA to accumulate in compartments defective in cargo transport and unproductive for delivery. In contrast, early endocytic/recycling compartments have the highest probability for mRNA escape. By using super-resolution microscopy, we could resolve a single LNP-mRNA within subendosomal compartments and capture events of mRNA escape from endosomal recycling tubules. Our results change the view of the mechanisms of endosomal escape and define quantitative parameters to guide the development of mRNA formulations toward higher efficacy and lower cytotoxicity., (© 2021 Paramasivam et al.)

The development of safe and efficacious gene vectors has limited greatly the potential for therapeutic treatments based on messenger RNA (mRNA). Lipid nanoparticles (LNPs) formed by an ionizable cationic lipid (here DLin-MC3-DMA), helper lipids (distearoylphosphatidylcholine, DSPC, and cholesterol), and a poly(ethylene glycol) (PEG) lipid have been identified as very promising delivery vectors of short interfering RNA (siRNA) in different clinical phases; however, delivery of high-molecular weight RNA has been proven much more demanding. Herein we elucidate the structure of hEPO modified mRNA-containing LNPs of different sizes and show how structural differences affect transfection of human adipocytes and hepatocytes, two clinically relevant cell types. Employing small-angle scattering, we demonstrate that LNPs have a disordered inverse hexagonal internal structure with a characteristic distance around 6 nm in presence of mRNA, whereas LNPs containing no mRNA do not display this structure. Furthermore, using contrast variation small-angle neutron scattering, we show that one of the lipid components, DSPC, is localized mainly at the surface of mRNA-containing LNPs. By varying LNP size and surface composition we demonstrate that both size and structure have significant influence on intracellular protein production. As an example, in both human adipocytes and hepatocytes, protein expression levels for 130 nm LNPs can differ as much as 50-fold depending on their surface characteristics, likely due to a difference in the ability of LNP fusion with the early endosome membrane. We consider these discoveries to be fundamental and opening up new possibilities for rational design of synthetic nanoscopic vehicles for mRNA delivery., Competing Interests: Conflict of interest statement: M.Y.A., T.K., S.B., S.W., X.W., A.J.K, A.D., and L.L. are employed by AstraZeneca R&D Gothenburg., (Copyright © 2018 the Author(s). Published by PNAS.)

The purpose of this study was to investigate in vivo intestinal precipitation of a model drug mebendazole, a basic BCS class II drug, using dogs with intestinal stomas for administration or sampling. After oral administration of a solution with an expected intestinal supersaturation of approximately 20 times the solubility, the measured supersaturation in dog intestinal fluid (DIF) was up to 10 times and, on average, only 11% of the given dose was retrieved as solid drug in the collected fluid from the stoma. The drug was rapidly absorbed with >90% of the total systemic exposure reached within three hours after duodenal administration of a solution. In silico absorption modeling showed that in vivo data were reasonably well described by a nonprecipitating solution. An in vitro model of precipitation in DIF predicted that the intestinal concentration of dissolved mebendazole would be less than 1/5 of the initial concentration within 10 min at concentrations comparable to in vivo. It was concluded that intestinal precipitation did not have any major influence on mebendazole absorption. The extent of precipitation was overpredicted in vitro given the in vivo absorption rate, and further work is needed to identify in vitro factors that could enable more accurate in vivo predictions of intestinal precipitation from solutions.

Dissolution models require, at their core, an accurate diffusion model. The accuracy of the model for diffusion-dominated dissolution is particularly important with the trend toward micro- and nanoscale drug particles. Often such models are based on the concept of a "diffusion layer." Here a framework is developed for diffusion-dominated dissolution models, and we discuss the inadequacy of classical models that are based on an unphysical constant diffusion layer thickness assumption, or do not correctly modify dissolution rate due to "confinement effects": (1) the increase in bulk concentration from confinement of the dissolution process, (2) the modification of the flux model (the Sherwood number) by confinement. We derive the exact mathematical solution for a spherical particle in a confined fluid with impermeable boundaries. Using this solution, we analyze the accuracy of a time-dependent "infinite domain model" (IDM) and "quasi steady-state model" (QSM), both formally derived for infinite domains but which can be applied in approximate fashion to confined dissolution with proper adjustment of a concentration parameter. We show that dissolution rate is sensitive to the degree of confinement or, equivalently, to the total concentration C(tot). The most practical model, the QSM, is shown to be very accurate for most applications and, consequently, can be used with confidence in design-level dissolution models so long as confinement is accurately treated. The QSM predicts the ratio of diffusion layer thickness to particle radius (the Sherwood number) as a constant plus a correction that depends on the degree of confinement. The QSM also predicts that the time required for complete saturation or dissolution in diffusion-controlled dissolution experiments is singular (i.e., infinite) when total concentration equals the solubility. Using the QSM, we show that measured differences in dissolution rate in a diffusion-controlled dissolution experiment are a result of differences in the degree of confinement on the increase in bulk concentration independent of container geometry and polydisperse vs single particle dissolution. We conclude that the constant diffusion-layer thickness assumption is incorrect in principle and should be replaced by the QSM with accurate treatment of confinement in models of diffusion-controlled dissolution.

A computational method of predicting the effects of the metastability of drug solutions is sought. A simple extension of our in silicio approach to thermodynamic drug solubility is tested on the drug bicalutamide for which we performed vapor pressure measurements complementing earlier measurements of aqueous solubility and crystal-water interfacial tension. The free energy of formation of an N-cluster of the drug molecule is estimated semiempirically by use of an Einstein model of the crystal in which experiment supplies the crystal structure, enthalpy of sublimation, and Einstein frequency of vibration. The rigid drug clusters with N from 2 to 14 are extracted from the bulk crystal by minimization of either cluster energy or radius of gyration. The free energy of hydration is estimated by Monte Carlo simulation combined with simplified response theory based on the OPLS-AA/COMPASS force field for the drug-water interaction and the TIP4P water model. The results have been interpreted in terms of an apparent crystal-water interfacial tension according to classical nucleation theory. The energy-minimal and radius of gyration-minimal clusters seem to give very similar crystal-water interfacial tensions for both the monoclinic and the triclinic polymorph. The interfacial tension of the monoclinic polymorph is significantly higher (by around 20%) than that of the triclinic polymorph in accordance with experiment. For the triclinic polymorph a substantial overestimation of the interfacial tension compared to estimates from crystal nucleation experiments is found, mitigated somewhat by an empirical scaling of the simulated binding energies and free energies of hydration.

In the present paper, we have studied particle dissolution and crystal growth of the poorly water soluble drug felodipine, using fluorescence as a probe for the amount of crystalline material. Dissolution kinetics is essentially diffusion-controlled, while the rate of crystal growth is significantly slower compared to the diffusion-controlled limit. The deviation from diffusion control was characterized by the effective length, lambda, related to the kinetics of a surface integration process. Amorphous nanoparticles may be highly unstable in the presence of small amounts of crystalline particles. This is due to the fact that the molecular solubility from the amorphous nanoparticles often is at least an order of magnitude higher than the corresponding crystalline solubility. In a mixed system where crystalline nanoparticles have been added to an amorphous nanosuspension, the bulk will have a monomer concentration intermediate between the amorphous and crystalline solubilities, and is thus supersaturated with respect to the crystalline particles while being undersaturated with respect to the amorphous particles. As a consequence, the amorphous particles spontaneously dissolve, while crystalline particles grow, in a combined process which is similar to Ostwald ripening. By knowing the parameters describing dissolution and crystal growth, respectively, it was possible to simulate the outcome of controlled seeding experiments, where a small amount of crystalline nanoparticles was added to a dispersion of amorphous nanoparticles. A good agreement between model calculations and experiments was obtained including how the crystal growth rate varied with the amounts of added crystalline seeds.

The solubility of drugs in water is investigated in a series of papers. In this work, we address the process of bringing a drug molecule from the vapor into a pure drug amorphous phase. This step enables us to actually calculate the solubility of amorphous drugs in water. In our general approach, we, on one hand, perform rigorous free energy simulations using a combination of the free energy perturbation and thermodynamic integration methods. On the other hand, we develop an approximate theory containing parameters that are easily accessible from conventional Monte Carlo simulations, thereby reducing the computation time significantly. In the theory for solvation, we assume that DeltaG* = DeltaGcav + ELJ + EC/2, where the free energy of cavity formation, DeltaGcav, in pure drug systems is obtained using a theory for hard-oblate spheroids, and ELJ and EC are the Lennard-Jones and Coulomb interaction energies between the chosen molecule and the others in the fluid. The theoretical predictions for the free energy of solvation in pure amorphous matter are in good agreement with free energy simulation data for 46 different drug molecules. These results together with our previous studies support our theoretical approach. By using our previous data for the free energy of hydration, we compute the total free energy change of bringing a molecule from the amorphous phase into water. We obtain good agreement between the theory and simulations. It should be noted that to obtain accurate results for the total process, high precision data are needed for the individual subprocesses. Finally, for eight different substances, we compare the experimental amorphous and crystalline solubility in water with the results obtained by the proposed theory with reasonable success.

As a first step in the computational prediction of drug solubility the free energy of hydration, DeltaG*(vw) in TIP4P water has been computed for a data set of 48 drug molecules using the free energy of perturbation method and the optimized potential for liquid simulations all-atom force field. The simulations were performed in two steps, where first the Coulomb and then the Lennard-Jones interactions between the solute and the water molecules were scaled down from full to zero strength to provide physical understanding and simpler predictive models. The results have been interpreted using a theory assuming DeltaG*(vw) = A(MS)gamma + E(LJ) + E(C)/2 where A(MS) is the molecular surface area, gamma is the water-vapor surface tension, and E(LJ) and E(C) are the solute-water Lennard-Jones and Coulomb interaction energies, respectively. It was found that by a proper definition of the molecular surface area our results as well as several results from the literature were found to be in quantitative agreement using the macroscopic surface tension of TIP4P water. This is in contrast to the surface tension for water around a spherical cavity that previously has been shown to be dependent on the size of the cavity up to a radius of approximately 1 nm. The step of scaling down the electrostatic interaction can be represented by linear response theory.

Amorphous drug nanosuspensions are prone to particle growth due to Ostwald ripening. By incorporating a second component of extremely low aqueous solubility, Ostwald ripening can be inhibited. These studies indicate that to inhibit ripening, the drug/inhibitor mixture (in the particles) must form a single phase. The drug/inhibitor mixture can be characterized by the interaction parameter chi using the Bragg-Williams theory, in which single phase mixtures are obtained for chi < 2. The chi parameter can be calculated from the (crystalline) solubility of the drug in the inhibitor, provided the inhibitor is a liquid, and the melting entropy and temperature of the drug.

A simple turbidimetric method was developed to measure the bulk concentration of drug in nanosuspensions. The bulk concentrations measured were in the range from 1 microM to 1 mM. The accuracy of the method was checked by determination of the bulk concentration of crystalline nanosuspensions, i.e., the crystalline solubility, which compared favorably to solubilities measured by a conventional method. Results obtained for amorphous nanosuspensions agreed with predictions using a theory describing the relative solubility between a supercooled liquid and a crystal. Further, it was found that the bulk concentration in Ostwald ripening inhibited amorphous nanosuspensions and could be lowered by incorporation of higher amounts of the inhibitor, in agreement with predictions using the Bragg-Williams theory of nonideal solutions.