Accuracy of calculated pH-dependent aqueous drug solubility

HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions

Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and chemical systems, owing to water's remarkable versatility as a solvent. However, accurately predicting the feasibility of hydrolysis through computational techniques is a difficult task, as subtle changes in reactant structure like heteroatom substitutions or neighboring functional groups can influence the reaction outcome. Furthermore, hydrolysis is sensitive to the pH of the aqueous medium, and the same reaction can have different reaction properties at different pH conditions. In this work, we have combined reaction templates and high-throughput ab initio calculations to construct a diverse data set of hydrolysis free energies. The developed framework automatically identifies reaction centers, generates hydrolysis products, and utilizes a trained graph neural network (GNN) model to predict ΔG values for all potential hydrolysis reactions in a given molecule. The long-term goal of the work is to develop a data-driven, computational tool for high-throughput screening of pH-specific hydrolytic stability and the rapid prediction of reaction products, which can then be applied in a wide array of applications including chemical recycling of polymers and ion-conducting membranes for clean energy generation and storage.

Small molecule drug absorption in inflammatory bowel disease and current implementation in physiologically- based pharmacokinetic models

Inflammatory bowel disease (IBD) is characterized by a chronic inflammation of the intestinal mucosa, with predominant localization in the colon in ulcerative colitis (UC) or affecting the entire length of the gastrointestinal tract in Crohn's disease (CD). Recent advances in the drug development space have been marked by a return to orally administered small molecules with novel mechanisms of action such as Janus kinase inhibitors. Additionally, the prevalence of certain chronic conditions is higher in IBD patients, many of which are treated with orally administered drugs. Given the pathophysiology and localization of IBD, altered drug absorption from the gastrointestinal tract can be expected. This review discusses several physiological differences between the small and large intestine with the potential to influence drug absorption including pathophysiology related alterations associated with IBD. The main physiological parameters which are identified include luminal fluid volume, luminal pH, transit time, bile salt concentration, microbiome, absorptive surface area, permeability and metabolizing enzymes and transporters. Literature regarding these factors in IBD patients is marked with high heterogeneity in reporting of disease severity and location leading to difficulties in interpreting data across different studies. While the influence of most of these factors has been directly assessed in healthy volunteers, this is rarely the case for IBD patients. Furthermore, studies which used PBPK modelling to describe the PK of an orally administered drug in an IBD population and were able to verify their findings using clinical data are critically examined. These models were able to incorporate the pathophysiological changes associated with IBD and partly succeeded in adequately predicting drug absorption in this population. Given the limited amount of PBPK studies performed on a limited number of drugs, the developed models are most likely not suitable to be used as a general PBPK model for the IBD population.

Biopharmaceutical profiling of anti-infective sanggenons from Morus alba root bark for inhalation administration

Mulberry Diels-Alder-type adducts (MDAAs), isolated from Morus alba root bark, exhibit dual activity against viral and bacterial pathogens but show sobering efficacy following oral administration. Inhalation administration may overcome issues with oral bioavailability and improve efficacy for the treatment of respiratory infections. To assess the suitability of MDAAs for inhalation administration, physicochemical (e.g. pH, pKa, logP, pH-dependent solubility) and biopharmaceutical (epithelial cytotoxicity, permeability, and uptake) properties of two bioactive MDAA stereoisomers sanggenon C (SGC) and sanggenon D (SGD) were evaluated as isolated natural compounds and within parent extracts (MA21, MA60). Despite their structural similarity, SGD exhibited a 10-fold higher solubility than SGC across pH 1.2-7.4, with slight increases at neutral pH. Both compounds were more soluble in isolated form than in the parent extracts. The more lipophilic SGC was found to be more cytotoxic when compared to SGD, indicating a better cellular penetration, which was confirmed by uptake studies. Nonetheless, SGC and SGD exhibited no measurable permeability across intact Calu-3 monolayers, highlighting their potential for increased lung retention and improved local anti-infective activity following inhalation administration. Results suggest that SGC and SGD in isolated form, rather than as extracts, are promising candidates for pulmonary drug delivery to treat lung infections.

Comparative assessment of physics-based in silico methods to calculate relative solubilities

Relative solubilities, i.e. whether a given molecule is more soluble in one solvent compared to others, is a critical parameter for pharmaceutical and agricultural formulation development and chemical synthesis, material science, and environmental chemistry. In silico predictions of this crucial variable can help reducing experiments, waste of solvents and synthesis optimization. In this study, we evaluate the performance of different physics-based methods for predicting relative solubilities. Our assessment involves quantum mechanics-based COSMO-RS and molecular dynamics-based free energy methods using OPLS4, the open-source OpenFF Sage, and GAFF force fields, spanning over 200 solvent-solute combinations. Our investigation highlights the important role of compound multimerization, an effect which must be accounted for to obtain accurate relative solubility predictions. The performance landscape of these methods is varied, with significant differences in precision depending on both the method used and the solute considered, thereby offering an improved understanding of the predictive power of physics-based methods in chemical research.

Intrinsic Solubility of Ionizable Compounds from pKa Shift

Aqueous solubility of pharmaceutical substances plays an important role in small molecule drug discovery and development, with ionizable groups often employed to enhance solubility. Drug candidate compounds often contain ionizable groups to increase their solubility. Recognizing that the electrostatically charged form of the compound is much more soluble than the uncharged form, this work proposes a model to explore the relationship between the pKa shift of the ionizable group and dissolution equilibria. The model considers three forms of a compound: dissolved-charged, dissolved-uncharged, and aggregated-uncharged. It analyzes two linked equilibria: the protonation of the ionizable group and the dissolution-aggregation of the uncharged form, with the observed pKa shift depending on the total concentration of the compound. The active concentration of the aggregates determines this shift. The model was explored through the determination of the pKa shift and intrinsic solubility of specific compounds, such as ICPD47, a high-affinity inhibitor of the Hsp90 chaperone protein and anticancer target, as well as benzoic acid and benzydamine. The model holds the potential for a more nuanced understanding of intrinsic solubility and may lead to advancements in drug discovery and development.

β-Lactoglobulin variants as potential carriers of pramoxine: Comprehensive structural and biophysical studies

β-Lactoglobulin (BLG) is a member of the lipocalin family. As other proteins from this group, BLG can be modified to bind specifically compounds of medical interests. The aim of this study was to evaluate the role of two mutations, L39Y and L58F, in the binding of topical anesthetic pramoxine (PRM) to β-lactoglobulin. Circular dichroism spectroscopy, isothermal titration calorimetry (ITC), and X-ray crystallography were used to understand the mechanisms of BLG-PRM interactions. Studies were performed for three new BLG mutants: L39Y, L58F, and L39Y/L58F. ITC measurements indicated a significant increase in the affinity to the PRM of variants L58F and L39Y. Measurements taken for the double mutant L39Y/L58F showed the additivity of two mutations leading to about 80-fold increase in the affinity to PRM in comparison to natural protein BLG from bovine milk. The determined crystal structures revealed that pramoxine is accommodated in the β-barrel interior of BLG mutants and stabilized by hydrophobic interactions. The observed additive effect of two mutations on drug binding opens the possibility for further designing of new BLG variants with high affinity to selected drugs.

Amorphous solid dispersions of lidocaine and lidocaine HCl produced by ball milling with well-defined RAFT-synthesised methacrylic acid polymers

This study focuses on the use of methacrylic acid polymers synthesised via the Reversible Addition Fragmentation chain Transfer (RAFT) polymerisation method for the production of amorphous solid dispersions (ASDs) by ball milling, to kinetically solubilize a poorly water-soluble model drug. The solid-state characteristics and the physical stability of the formulations were investigated using X-ray diffraction, differential scanning calorimetry, and infrared spectroscopy. This was followed by dissolution studies in different media. It was discovered that the acidic polymers of methacrylic acid were capable of interacting with the weakly basic drug lidocaine and its hydrochloride salt form to produce ASDs when a polymer to drug ratio of 70:30 w/w was used. The ASDs remained amorphous following storage under accelerated aging conditions (40 °C and 75% relative humidity) over 8 months. Fast dissolution and increased lidocaine solubility in different media were obtained from the ASDs owing to the reduced microenvironment pH and enhanced solubilization of the drug caused by the presence of the acidic polymer in the formulation. Production of ASDs using well-defined RAFT-synthesised acidic polymers is a promising formulation strategy to enhance the pharmaceutical properties of basic poorly water-soluble drugs.

pH-dependent solubility prediction for optimized drug absorption and compound uptake by plants

Aqueous solubility is the most important physicochemical property for agrochemical and drug candidates and a prerequisite for uptake, distribution, transport, and finally the bioavailability in living species. We here present the first-ever direct machine learning models for pH-dependent solubility in water. For this, we combined almost 300000 data points from 11 solubility assays performed over 24 years and over one million data points from lipophilicity and melting point experiments. Data were split into three pH-classes - acidic, neutral and basic - , representing the conditions of stomach and intestinal tract for animals and humans, and phloem and xylem for plants. We find that multi-task neural networks using ECFP-6 fingerprints outperform baseline random forests and single-task neural networks on the individual tasks. Our final model with three solubility tasks using the pH-class combined data from different assays and five helper tasks results in root mean square errors of 0.56 log units overall (acidic 0.61; neutral 0.52; basic 0.54) and Spearman rank correlations of 0.83 (acidic 0.78; neutral 0.86; basic 0.86), making it a valuable tool for profiling of compounds in pharmaceutical and agrochemical research. The model allows for the prediction of compound pH profiles with mean and median RMSE per molecule of 0.62 and 0.56 log units.

Intrinsic Aqueous Solubility: Mechanistically Transparent Data-Driven Modeling of Drug Substances

Intrinsic aqueous solubility is a foundational property for understanding the chemical, technological, pharmaceutical, and environmental behavior of drug substances. Despite years of solubility research, molecular structure-based prediction of the intrinsic aqueous solubility of drug substances is still under active investigation. This paper describes the authors’ systematic data-driven modelling in which two fit-for-purpose training data sets for intrinsic aqueous solubility were collected and curated, and three quantitative structure–property relationships were derived to make predictions for the most recent solubility challenge. All three models perform well individually, while being mechanistically transparent and easy to understand. Molecular descriptors involved in the models are related to the following key steps in the solubility process: dissociation of the molecule from the crystal, formation of a cavity in the solvent, and insertion of the molecule into the solvent. A consensus modeling approach with these models remarkably improved prediction capability and reduced the number of strong outliers by more than two times. The performance and outliers of the second solubility challenge predictions were analyzed retrospectively. All developed models have been published in the QsarDB.org repository according to FAIR principles and can be used without restrictions for exploring, downloading, and making predictions.

Factors Influencing the Bioavailability of Organic Molecules to Bacterial Cells-A Mini-Review

The bioavailability of organic compounds to bacterial cells is crucial for their vital activities. This includes both compounds that are desirable to the cells (e.g., sources of energy, carbon, nitrogen, and other nutrients) and undesirable compounds that are toxic to the cells. For this reason, bioavailability is an issue of great importance in many areas of human activity that are related to bacteria, e.g., biotechnological production, bioremediation of organic pollutants, and the use of antibiotics. This article proposes a classification of factors determining bioavailability, dividing them into factors at the physicochemical level (i.e., those related to the solubility of a chemical compound and its transport in aqueous solution) and factors at the microbiological level (i.e., those related to adsorption on the cell surface and those related to transport into the cell). Awareness of the importance of and the mechanisms governing each of the factors described allows their use to change bioavailability in the desired direction.

Molecular design of a pathogen activated, self-assembling mechanopharmaceutical device

Weakly basic small molecule drugs like clofazimine can be used as building blocks for endowing cells with unnatural structural and functional elements. Here, we describe how clofazimine represents a first-in-class mechanopharmaceutical device, serving to construct inert, inactive and stimulus responsive drug depots within the endophagolysosomal compartment of cells of living organisms. Upon oral administration, clofazimine molecules self-assemble into stable, membrane-bound, crystal-like drug inclusions (CLDI) that accumulate within macrophages to form a "smart" biocompatible, pathogen activatable mechanopharmaceutical device. Upon perturbation of the mechanism maintaining pH and ion homeostasis of these CLDIs, the inert encapsulated drug precipitates are destabilized, releasing bioactive drug molecules into the cell and its surrounding. The resulting increase in clofazimine solubility activates this broad-spectrum antimicrobial, antiparasitic, antiviral or cytotoxic agent within the infected macrophage. We present a general, molecular design strategy for using clofazimine and other small molecule building blocks for the cytoplasmic construction of mechanopharmaceutical devices, aimed at rapid deployment during infectious disease outbreaks, for the purpose of pandemic prevention.

Phase Behavior and Crystallization Kinetics of a Poorly Water-Soluble Weakly Basic Drug as a Function of Supersaturation and Media Composition

Understanding the supersaturation and precipitation behavior of poorly water-soluble compounds in vivo and the impact on oral absorption is critical to design consistently performing products with optimized bioavailability. Weakly basic compounds are of particular importance in this context since they have an inherent tendency to undergo supersaturation in vivo upon exit from the stomach and entry into the small intestine because of their pH-dependent solubility. To understand and probe potential in vivo variability of supersaturating systems, rigorous understanding of compound physical properties and phase behavior landscape is essential. Herein, we extensively characterize the solution phase behavior of a model, poorly soluble and weakly basic compound, posaconazole. Phase boundaries for crystal-solution and amorphous-solution were established as a function of pH, allowing possible phase transformations, namely, crystallization or liquid-liquid phase separation, to be mapped for different initial doses and fluid volumes. Endogenous surfactants including sodium taurocholate, lecithin, glycerol monooleate, and sodium oleate in biorelevant media significantly extended the phase boundaries due to solubilization, to an extent that was dependent on the concentration of the surface-active agents. The nucleation induction time of posaconazole was much shorter in biorelevant media in comparison to the corresponding buffer solution, with two distinct regions observed in all media that could be attributed to a change in the nucleation mechanism at high and low supersaturation. The presence of undissolved nanocrystals accelerated the desupersaturation. This work enhances our understanding of biorelevant factors impacting precipitation kinetics, which might affect absorption in vivo. It is expected that findings from this study with posaconazole could be broadly applicable to other weakly basic compounds, after taking into consideration differences in pK_a, solubility, and molecular structure.

Discovery solubility measurement and assessment of small molecules with drug development in mind

Solubility is a key physicochemical property for the success of any drug candidate. Although the methods used and their rationales for determining solubility are subject to project needs and stages along the drug discovery-drug development pipeline, an artificial boundary can exist at the discovery-development interface. This boundary results in less effective solubility knowledge sharing and data integration among scientists in both drug discovery and drug development. Herein, we present a refreshed perspective on solubility. Solubility experimentation is not a one-size-fits-all measurement; instead, we stress the importance of constructing a seamless solubility understanding of a molecule as it progresses from a new chemical entity into a drug product.

Going green: Development of a sustainable lipid-based enteric coating formulation for low-dose aspirin multiparticulate systems

There is a rising awareness of pharmaceutical industry of both patient-centric and sustainable product development. Manufacturing of multiparticulate systems (MPS) with functional coating via solvent-free hot melt coating (HMC) can fulfill both requirements. An innovative lipid-based formulation was developed with the composition of palmitic acid and Grindsted® citrem BC-FS (BC-FS) for enteric coating of acetylsalicylic acid (ASA). The ASA crystals were directly hot melt coated to produce user-friendly low-dose ASA MPS for thromboembolism prophylaxis. Prior to HMC, rational boundaries for the process temperature were defined based on the melting and crystallization behavior of coating blend. Stability of coating in terms of resistance to heat stress and solidstate stability were screened via Fourier-transform infrared spectroscopy and x-ray diffraction. Exposure of coating blend to 100 °C for two hours did not cause any chemical degradation. Crystal growth of palmitic acid and polymorphic transformation in BC-FS were observed after storage under accelerated conditions, however did not significantly affect the ASA release from coating. The developed formulation is a unique solvent-free, lipid-based enteric composition and paves the way for sustainable green pharmaceutical manufacturing.

Multi-material 3D printing of programmable and stretchable oromucosal patches for delivery of saquinavir

Oromucosal patches for drug delivery allow fast onset of action and ability to circumvent hepatic first pass metabolism of drugs. While conventional fabrication methods such as solvent casting or hot melt extrusion are ideal for scalable production of low-cost delivery patches, these methods chiefly allow for simple, homogenous patch designs. As alternative, a multi-material direct-ink-write 3D printing for rapid fabrication of complex oromucosal patches with unique design features was demonstrated in the present study. Specifically, three print-materials: an acidic saquinavir-loaded hydroxypropyl methylcellulose ink, an alkaline effervescent sodium carbonate-loaded ink, and a methyl cellulose backing material were combined in various designs. The CO₂ content and pH of the microenvironment were controlled by adjusting the number of alkaline layers in the patch. Additionally, the rigid and brittle patches were converted to compliant and stretchable patches by implementing mesh-like designs. Our results illustrate how 3D printing can be used for rapid design and fabrication of multifunctional or customized oromucosal patches with tailored dosages and changed drug permeation.

UNGAP best practice for improving solubility data quality of orally administered drugs

An important goal of the European Cooperation in Science and Technology (COST) Action UNGAP (UNderstanding Gastrointestinal Absorption-related Processes, www.ungap.eu) is to improve standardization of methods relating to the study of oral drug absorption. Solubility is a general term that refers to the maximum achievable concentration of a compound dissolved in a liquid medium. For orally administered drugs, relevant information on drug properties is crucial during drug (product) development and at the regulatory level. Collection of reliable and reproducible solubility data requires careful application and understanding of the limitations of the selected experimental method. In addition, the purity of a compound and its solid state form, as well as experimental parameters such as temperature of experimentation, media related factors, and sample handling procedures can affect data quality. In this paper, an international consensus developed by the COST UNGAP network on recommendations for collecting high quality solubility data for the development of orally administered drugs is proposed.

Lipid-based emulsion drug delivery systems - a comprehensive review

Lipid-based emulsion system - a subcategory of emulsion technology, has emerged as an enticing option to improve the solubility of the steadily rising water-insoluble candidates. Along with enhancing solubility, additional advantages such as improvement in permeability, protection against pre-systemic metabolism, ease of manufacturing, and easy to scale-up have made lipid-based emulsion technology very popular among academicians and manufacturers. The present article provides a comprehensive review regarding various critical properties of lipid-based emulsion systems, such as microemulsion, nanoemulsion, SMEDDS (self microemulsifying drug delivery system), and SNEDDS (self nanoemulsifying drug delivery system). The present article also explains in detail the similarities and differences between them, the stabilization mechanism, methods of preparation, excipients used to prepare them, and evaluation techniques. Subtle differences between nearly related terminologies such as microemulsion and nanoemulsion, SMEDDS, and SNEDDS are also explained in detail to clarify the basic differences. The present article also gives in-depth information regarding the chemical structure of various lipidic excipients, various possible chemical modifications to modify their inherent properties, and their regulatory status for rational selection.

Application of Artificial Neural Networks to Predict the Intrinsic Solubility of Drug-Like Molecules

Machine learning (ML) approaches are receiving increasing attention from pharmaceutical companies and regulatory agencies, given their ability to mine knowledge from available data. In drug discovery, for example, they are employed in quantitative structure-property relationship (QSPR) models to predict biological properties from the chemical structure of a drug molecule. In this paper, following the Second Solubility Challenge (SC-2), a QSPR model based on artificial neural networks (ANNs) was built to predict the intrinsic solubility (logS0) of the 100-compound low-variance tight set and the 32-compound high-variance loose set provided by SC-2 as test datasets. First, a training dataset of 270 drug-like molecules with logS0 value experimentally determined was gathered from the literature. Then, a standard three-layer feed-forward neural network was defined by using 10 ChemGPS physico-chemical descriptors as input features. The developed ANN showed adequate predictive performances on both of the SC-2 test datasets. Benefits and limitations of ML approaches have been highlighted and discussed, starting from this case-study. The main findings confirmed that ML approaches are an attractive and promising tool to predict logS0; however, many aspects, such as data quality, molecular descriptor computation and selection, and assessment of applicability domain, are crucial but often neglected, and should be carefully considered to improve predictions based on ML.

Influence of Lactobacillus Biosurfactants on Skin Permeation of Hydrocortisone

One of the most widely used strategies to improve drug diffusion through the skin is the use of permeation enhancers. The aim of this work was to investigate the effect of two biosurfactants (BS), produced by Lactobacillus crispatus BC1 and Lactobacillus gasseri BC9, on the skin permeation profile of hydrocortisone (HC, model drug). HC aqueous solubility and in vitro diffusion studies through porcine skin were performed in the presence of BC1-BS and BC9-BS at concentrations below and above critical micellar concentrations (CMC). Moreover, skin hydration tests and differential scanning calorimetry (DSC) analysis were performed to further investigate BS interaction with the outermost layer of the skin. Both BS increased HC solubility, especially at concentrations above their CMC. At concentrations below the CMC, drug permeation through the skin was improved, as the result of a dual effect: a) the formation of a superficial lipophilic environment, as confirmed by the reduction in skin hydration and b) the interaction between BS and the stratum corneum (SC), as demonstrated by the DSC curves. From the obtained data, it appears that BC1-BS and BC9-BS could represent new promising green excipients for drug permeation enhancement through the skin.

Ionizable Drug Self-Associations and the Solubility Dependence on pH: Detection of Aggregates in Saturated Solutions Using Mass Spectrometry (ESI-Q-TOF-MS/MS)

It is widely accepted that solubility-pH profiles of ionizable compounds follow the Henderson-Hasselbalch equation. However, several studies point out that compounds often undergo additional processes in saturated solutions, such as sub-micellar oligomerization, micellar aggregation, or drug-buffer complexation among others, which make the experimental profiles deviate from the behavior predicted by the Henderson-Hasselbalch equation. Often, the presence of additional processes is supported by the analysis of experimental data through solubility computer programs. However, the purpose of this work is to experimentally prove the aggregation phenomena for a series of bases for which deviations from the theoretical profile have been observed. To this end, five monoprotic bases (lidocaine, maprotiline, cyproheptadine, bupivacaine, and mifepristone) susceptible to form ionic aggregates in solution have been selected, and mass spectrometry has been the technique of choice to prove the presence of aggregation. High declustering potentials have been applied to prevent aggregates from forming in the ionization source of the mass spectrometer. In addition, haloperidol has been used as a negative control since according to its profile, it is not suspected to form ionic aggregates. In all instances, except for haloperidol, the analysis of the saturated solutions revealed the presence of mixed-charged dimers (aggregates formed by a neutral molecule and a charged one) and even trimers in the case of mifepristone and bupivacaine. For lidocaine, the most soluble of the compounds, the presence of neutral aggregates was also detected. These experiments support the hypothesis that the simple Henderson-Hasselbalch equation may explain the solubility-pH behavior of certain compounds, but it can be somewhat inaccurate in describing the behavior of many other substances.

Hyperthermia Improves Solubility of Intravesical Chemotherapeutic Agents

BACKGROUND: Nearly 70% of all new cases of bladder cancer are non-muscle invasive disease, the treatment for which includes transurethral resection followed by intravesical therapy. Unfortunately, recurrence rates approach 50% in part due to poor intravesical drug delivery. Hyperthermia is frequently used as an adjunct to intravesical chemotherapy to improve drug delivery and response to treatment. OBJECTIVE: To assess the solubility profile of intravesical chemotherapies under varying conditions of pH and temperature. METHODS: Using microplate laser nephelometry we measured the solubility of three intravesical chemotherapy agents (mitomycin C, gemcitabine, and cisplatin) at varying physical conditions. Drugs were assessed at room temperature (23°C), body temperature (37°C), and 43°C, the temperature used for hyperthermic intravesical treatments. To account for variations in urine pH, solubility was also investigated at pH 4.00, 6.00, and 8.00. RESULTS: Heat incrementally increased the solubility of all three drugs studied. Conversely, pH largely did not impact solubility aside for gemcitabine which showed slightly reduced solubility at pH 8.00 versus 6.00 or 4.00. Mitomycin C at the commonly used 2.0 mg/mL was insoluble at room temperature, but soluble at both 37 and 43°C. CONCLUSIONS: Hyperthermia as an adjunct to intravesical treatment would improve drug solubility, and likely drug delivery as some current regimens are insoluble without heat. Improvements in solubility also allow for testing of alternative administration regimens to improve drug delivery or tolerability. Further studies are needed to confirm that improvements in solubility result in increased drug delivery.

Stable solid dispersion of lurasidone hydrochloride with augmented physicochemical properties for the treatment of schizophrenia and bipolar disorder

Crystalline solid dispersion of lurasidone hydrochloride (LH) was made with various polar and non-polar small molecules to overcome the poor aqueous solubility issue. LH-Glutathione (GSH) solid dispersion in 1:1 ratio was prepared by co-grinding method and characterized by using differential scanning calorimetry (DSC), powder X-ray diffraction, Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. GSH acts as antioxidant and reported for anti-schizophrenic activity may provide synergistic action with LH or reduce the side effects. LH in LH-GSH solid dispersion (SD) has shown improvement in solubility by 7.9 folds than plain drug which translated in terms of improved dissolution rate by two-folds. The in vitro dissolution results showed maximum dissolution rate with LH-GSH SD (97.85 ± 2.40%) compared to plain drug (50.5 ± 3.02%) at 15 min (t₁₅ min, %) and thus, satisfying criteria of immediate release dosage form. DSC and FTIR data confirmed the stability of LH-GSH SD for 3 months at accelerated stability condition (40 ± 2°C and 75 ± 5% RH). The prepared LH-GSH SD can be used as a tool to target dual problems that is, enhanced physicochemical properties along with possible management of disorder which could be due to synergism with co-administered GSH. This approach is thought to be efficiently providing the relief to the psychological patients.

The Significance of Utilizing In Vitro Transfer Model and Media Selection to Study the Dissolution Performance of Weak Ionizable Bases: Investigation Using Saquinavir as a Model Drug

This study investigated the dissolution behavior of BCS class II ionizable weak base Saquinavir and its mesylate salt in the multi-compartment transfer setup employing different composition of dissolution media. The dissolution behavior of Saquinavir was studied by using a two-compartment transfer model representing the transfer of drug from the stomach (donor compartment) to the upper intestine (acceptor compartment). Various buffers like phosphate, bicarbonate, FaSSIF, and FeSSIF were employed. The dissolution was also studied in the concomitant presence of the additional solute, i.e., Quercetin. Further, the dissolution profiles of Saquinavir and its mesylate salt were simulated by GastroPlus^TM, and the simulated dissolution profiles were compared against the experimental ones. The formation of in situ HCl salt and water-soluble amorphous phosphate aggregates was confirmed in the donor and acceptor compartments of the transfer setup, respectively. As the consequence of the lower solubility product of HCl salt of Saquinavir, the solubility advantage of mesylate salt was vanished leading to the lower than the predicted dissolution in the acceptor compartment. However, the formation of water-soluble aggregates in the presence of the phosphate salts was observed leading to the higher than the predicted dissolution of the free base in the transfer setup. Interestingly, the formation of such water-soluble aggregates was found to be hindered in the concomitant presence of an ionic solute resulting in the lower dissolution rates. The in situ generation of salts and aggregates in the transfer model lead to the inconsistent prediction of dissolution profiles by GastroPlus^TM.

Physicochemical Properties of Pinic, Pinonic, Norpinic, and Norpinonic Acids as Relevant α-Pinene Oxidation Products

Here, the study is focused on the synthesis and determination of physicochemical properties of four α-pinene secondary organic aerosol (SOA) products: cis-pinic acid, cis-pinonic acid, cis-norpinic acid, and cis-norpinonic acid. These encompass their thermal properties, solid-liquid phase equilibria, and dissociation constant (pK_a). Thermal properties, including the melting temperature, enthalpy of fusion, temperature, and enthalpy of the phase transitions, were measured with the differential scanning calorimetry technique. These SOA components exhibit relatively high melting temperatures from 364.32 K for cis-pinic acid to 440.68 K for cis-norpinic acid. The enthalpies of fusion vary from 14.75 kJ·mol^-1 for cis-norpinic acid to 30.35 kJ·mol^-1 for cis-pinonic acid. The solubility in water was determined with the dynamic method (solid-liquid phase equilibria method), and then experimental results were interpreted and correlated using three different mathematical models: Wilson, non-random two-liquid model, and universal quasichemical equations. The results of the correlation indicate that the Wilson equation appears to work the best for all investigated compounds, giving rise to the lowest value of a standard deviation. cis-Norpinic acid and cis-pinic acid (dicarboxylic acids) show better solubility in the aqueous solution than cis-norpinonic acid and cis-pinonic acid (monocarboxylic acids), which affect the multiphase chemistry of α-pinene SOA processes. For cis-pinonic acid and cis-norpinonic acid, also pH-profile solubility was determined. The intrinsic solubility (S₀) for cis-norpinonic acid was measured to be 0.05 mmol·dm^-3, while for cis-pinonic acid, it was found to be 0.043 mmol·dm^-3. The acidity constants (pK_a) at 298 and 310 K using the Bates-Schwarzenbach spectrophotometric method were determined. The pK_a values at 298.15 K for cis-norpinonic acid and cis-pinonic acid were found to be 4.56 and 5.19, respectively, whereas at 310.15 K, pK_a values were found to be -4.76 and 5.25, respectively.

A review of methods for solubility determination in biopharmaceutical drug characterization

The significance of thermodynamic solubility in biopharmaceutical compound or drug characterization as well as the importance of having methods that accurately establish it have been extensively addressed. Nonetheless, its precise determination continues to remain a challenging task to accomplish. Even more so when the number of compounds to evaluate is high and the available amount of each compound is low, both of which are inevitable for the compound characterization during the drug development process. Except for the shake-flask method which is still considered as the 'gold standard' in obtaining thermodynamic data, it is currently difficult to say that another satisfactory model which is routinely used to determine thermodynamic solubility is being applied. Therefore, this review summarizes the various experimental approaches which are based on the classical shake flask method but have yet attempted to speed up the experimental process of obtaining such data more conveniently. The most important experimental features of these approaches are provided to the reader. Some advantages and disadvantages associated with each approach are also highlighted, consequently offering a resource to those looking for the most appropriate of the approaches that have already fared well at determining the biopharmaceutically relevant drug solubility.

Cyclodextrin Reduces Intravenous Toxicity of a Model Compound

Solubilization of new chemical entities for toxicity assessment must use excipients that do not negatively impact drug pharmacokinetics and toxicology. In this study, we investigated the tolerability of a model freebase compound, GDC-0152, solubilized by pH adjustment with succinic acid and complexation with hydroxypropyl-β-cyclodextrin (HP-β-CD) to enable intravenous use. Solubility, critical micelle concentration, and association constant with HP-β-CD were determined. Blood compatibility and potential for hemolysis were assessed in vitro. Local tolerability was assessed after intravenous and subcutaneous injections in rats. A pharmacokinetic study was conducted in rats after intravenous bolus administration. GDC-0152 exhibited pH-dependent solubility that was influenced by self-association. The presence of succinic acid increased solubility in a concentration-dependent manner. HP-β-CD alone also increased solubility, but the extent of solubility enhancement was significantly lower than succinic acid alone. Inclusion of HP-β-CD in the solution of GDC-0152 improved blood compatibility, reduced hemolytic potential by ∼20-fold in vitro, and increased the maximum tolerated dose to 80 mg/kg.

Can human experts predict solubility better than computers?

In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R² of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R² of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

Aqueous Solubility Enhancement for Bioassays of Insoluble Inhibitors and QSPR Analysis: A TNF-α Study

The aim of this study is to improve the aqueous solubility of a group of compounds without interfering with their bioassay as well as to create a relevant prediction model. A series of 55 potential small-molecule inhibitors of tumor necrosis factor-alpha (TNF-α; SPD304 and 54 analogues), many of which cannot be bioassayed because of their poor solubility, was used for this purpose. The solubility of many of the compounds was sufficiently improved to allow measurement of their respective dissociation constants (K_d). Parameters such as dissolution time, initial state of the solute (solid/liquid), co-solvent addition (DMSO and PEG3350), and sample filtration were evaluated. Except for filtration, the remaining parameters affected aqueous solubility, and a solubilization protocol was established according to these. The aqueous solubility of the 55 compounds in 5% DMSO was measured with this protocol, and a predictive quantitative structure property relationship model was developed and fully validated based on these data. This classification model separates the insoluble from the soluble compounds and predicts the solubility of potential small-molecule inhibitors of TNF-α in aqueous solution (containing 5% DMSO as co-solvent) with an accuracy of 81.2%. The domain of applicability of the model indicates the type of compounds for which estimation of aqueous solubility can be confidently predicted.

Equilibrium solubility measurement of compounds with low dissolution rate by Higuchi's Facilitated Dissolution Method. A validation study

Incubation time plays a critical role in the accurate measurement of equilibrium solubility of compounds. Substances which dissolve very slowly generally need long incubation times (days or weeks) to reach equilibrium. However, long times may pose several problems, such as decomposition of solute, molding of buffer, and drifting of pH. Higuchi in 1979 proposed the Facilitated Dissolution Method (FDM) to dramatically reduce incubation time. It employs a small volume of water-immiscible organic solvent to partly solubilize the sample and thereby increase the surface area available for dissolution. The method has been used only rarely. In this study we performed a systematic validation of FDM using progesterone as model compound. The reference solubility value, 7.95±0.21μg/mL (p<0.05, n=5), was determined in Britton-Robinson buffer solution (pH7.4) at 25.0°C by the standardized protocol of Saturation Shake-Flask (SSF) method. Also, the solubility was measured by the FDM approach under varied experimental conditions (e.g., type and volume of organic solvent, time of agitation, and amount of solid excess), and compared to the reference value. It was demonstrated that the small amount of organic solvent used in the FDM does not impact the measured solubility, compared to the reference value. Additionally, four compounds of low dissolution rate (dexamethasone, digoxin, haloperidol and cosalane) were used to demonstrate that FDM can reduce the long equilibration time to the standardized 24h (6h stirring and 18h sedimentation). The time dependence of solubility equilibrium was measured by SSF, and the results were compared with those obtained by FDM. Our study, based on >200 solubility experiments, supports the validity of Higuchi's method. In this study we propose a standardized protocol for the FDM, where 1% v/v of organic solvent is used. Octane (or isooctane) was found to be suitable for highly hydrophobic compounds. Alternatively, octanol or 1,2-dichloroethane can be used for less lipophilic compounds.

Measurement and Accurate Interpretation of the Solubility of Pharmaceutical Salts

Salt formation is one of the primary approaches to improve the developability of ionizable poorly water-soluble compounds. Solubility determination of the salt candidates in aqueous media or biorelevant fluids is a critical step in salt screening. Salt solubility measurements can be complicated due to dynamic changes in both solution and solid phases. Because of the early implementation of salt screening in research, solubility measurements often are performed using minimal amount of material. Some salts have transient high solubility on dissolution. Recognition of these transients can be critical in developing these salts into drug products. This minireview focuses on challenges in salt solubility measurements due to the changes in solution caused by self-buffering effects of dissolved species and the changes in solid phase due to solid-state phase transformations. Solubility measurements and their accurate interpretation are assessed in the context of dissolution monitoring and solid-phase analysis technologies. A harmonized method for reporting salt solubility measurements is recommended to reduce errors and to align with the U.S. Pharmacopeial policy and Food and Drug Administration recommendations for drug products containing pharmaceutical salts.

The Prediction of the Relative Importance of CYP3A/P-glycoprotein to the Nonlinear Intestinal Absorption of Drugs by Advanced Compartmental Absorption and Transit Model

Intestinal CYP3A and P-glycoprotein (P-gp) decrease the intestinal absorption of substrate drugs. Since substrate specificity of CYP3A often overlaps that of P-gp, and estimation of their saturability in the intestine is difficult, dose-dependent FaFg (fraction of the administered drugs that reach the portal blood) of substrate drugs and the relative importance of CYP3A and P-gp have not been clarified in many cases. Thus, we tried to establish the universal methodology for predicting the in vivo absorption of several CYP3A and/or P-gp substrates from in vitro assays. One of the key points is to set up the scaling factor (SF), correcting the difference between the observed in vivo clearance and the predicted clearance from in vitro data. The SFs of Vmax for CYP3A (SFCYP3A) and P-gp (SFP-gp) were simultaneously optimized to explain the FaFg of CYP3A and/or P-gp substrate drugs. The best predictability of FaFg was achieved when considering both SFCYP3A and SFP-gp The simulation also clarified the relative importance of CYP3A and P-gp in determining FaFg In particular, the nonlinear intestinal absorption of verapamil was caused by the saturation of intestinal CYP3A, whereas that of quinidine was governed by the saturation of both CYP3A and P-gp. In addition, the dose-dependent FaFg of selective and dual CYP3A and/or P-gp substrates was well predicted. We therefore propose a methodology for predicting the FaFg of drugs using a mathematical model with optimized SFCYP3A and SFP-gp Our methodology is applicable to in vitro-in vivo extrapolation of intestinal absorption, even if absolute in vivo functions of enzymes/transporters are unclear.

Physiologically Based Absorption Modeling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Alectinib

Alectinib, a lipophilic, basic, anaplastic lymphoma kinase (ALK) inhibitor with very low aqueous solubility, has received Food and Drug Administration-accelerated approval for the treatment of patients with ALK+ non-small-cell lung cancer. This paper describes the application of physiologically based absorption modeling during clinical development to predict and understand the impact of food and gastric pH changes on alectinib absorption. The GastroPlus^™ software was used to develop an absorption model integrating in vitro and in silico data on drug substance properties. Oral pharmacokinetics was simulated by linking the absorption model to a disposition model fit to pharmacokinetic data obtained after an intravenous infusion. Simulations were compared to clinical data from a food effect study and a drug-drug interaction study with esomeprazole, a gastric acid-reducing agent. Prospective predictions of a positive food effect and negligible impact of gastric pH elevation were confirmed with clinical data, although the exact magnitude of the food effect could not be predicted with confidence. After optimization of the absorption model with clinical food effect data, a refined model was further applied to derive recommendations on the timing of dose administration with respect to a meal. The application of biopharmaceutical absorption modeling is an area with great potential to further streamline late stage drug development and with impact on regulatory questions.

Development and validation of a FIA/UV-vis method for pK(a) determination of oxime based acetylcholinesterase reactivators

Acetylcholinesterase reactivators (oximes) are compounds used for antidotal treatment in case of organophosphorus poisoning. The dissociation constants (pK(a1)) of ten standard or promising acetylcholinesterase reactivators were determined by ultraviolet absorption spectrometry. Two methods of spectra measurement (UV-vis spectrometry, FIA/UV-vis) were applied and compared. The soft and hard models for calculation of pK(a1) values were performed. The pK(a1) values were recommended in the range 7.00-8.35, where at least 10% of oximate anion is available for organophosphate reactivation. All tested oximes were found to have pK(a1) in this range. The FIA/UV-vis method provided rapid sample throughput, low sample consumption, high sensitivity and precision compared to standard UV-vis method. The hard calculation model was proposed as more accurate for pK(a1) calculation.