A Retrospective Biopharmaceutical Analysis of >800 Approved Oral Drug Products: Are Drug Properties of Solid Dispersions and Lipid-Based Formulations Distinctive?

Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute-Lipid Interactions

This study explores the research area of drug solubility in lipid excipients, an area persistently complex despite recent advancements in understanding and predicting solubility based on molecular structure. To this end, this research investigated novel descriptor sets, employing machine learning techniques to understand the determinants governing interactions between solutes and medium-chain triglycerides (MCTs). Quantitative structure-property relationships (QSPR) were constructed on an extended solubility data set comprising 182 experimental values of structurally diverse drug molecules, including both development and marketed drugs to extract meaningful property relationships. Four classes of molecular descriptors, ranging from traditional representations to complex geometrical descriptions, were assessed and compared in terms of their predictive accuracy and interpretability. These include two-dimensional (2D) and three-dimensional (3D) descriptors, Abraham solvation parameters, extended connectivity fingerprints (ECFPs), and the smooth overlap of atomic position (SOAP) descriptor. Through testing three distinct regularized regression algorithms alongside various preprocessing schemes, the SOAP descriptor enabled the construction of a superior performing model in terms of interpretability and accuracy. Its atom-centered characteristics allowed contributions to be estimated at the atomic level, thereby enabling the ranking of prevalent molecular motifs and their influence on drug solubility in MCTs. The performance on a separate test set demonstrated high predictive accuracy (RMSE = 0.50) for 2D and 3D, SOAP, and Abraham Solvation descriptors. The model trained on ECFP4 descriptors resulted in inferior predictive accuracy. Lastly, uncertainty estimations for each model were introduced to assess their applicability domains and provide information on where the models may extrapolate in chemical space and, thus, where more data may be necessary to refine a data-driven approach to predict solubility in MCTs. Overall, the presented approaches further enable computationally informed formulation development by introducing a novel in silico approach for rational drug development and prediction of dose loading in lipids.

Predictions of biorelevant solubility change during dispersion and digestion of lipid-based formulations

Computational approaches are increasingly explored in development of drug products, including the development of lipid-based formulations (LBFs), to assess their feasibility for achieving adequate oral absorption at an early stage. This study investigated the use of computational pharmaceutics approaches to predict solubility changes of poorly soluble drugs during dispersion and digestion in biorelevant media. Concentrations of 30 poorly water-soluble drugs were determined pre- and post-digestion with in-line UV probes using the MicroDISS Profiler™. Generally, cationic drugs displayed higher drug concentrations post-digestion, whereas for non-ionized drugs there was no discernible trend between drug concentration in dispersed and digested phase. In the case of anionic drugs there tended to be a decrease or no change in the drug concentration post-digestion. Partial least squares modelling was used to identify the molecular descriptors and drug properties which predict changes in solubility ratio in long-chain LBF pre-digestion (R2 of calibration = 0.80, Q2 of validation = 0.64) and post-digestion (R2 of calibration = 0.76, Q2 of validation = 0.72). Furthermore, multiple linear regression equations were developed to facilitate prediction of the solubility ratio pre- and post-digestion. Applying three molecular descriptors (melting point, LogD, and number of aromatic rings) these equations showed good predictivity (pre-digestion R2 = 0.70, and post-digestion R2 = 0.68). The model developed will support a computationally guided LBF strategy for emerging poorly water-soluble drugs by predicting biorelevant solubility changes during dispersion and digestion. This facilitates a more data-informed developability decision making and subsequently facilitates a more efficient use of formulation screening resources.

Rationalizing Counterion Selection for the Development of Lipophilic Salts: A Case Study with Venetoclax

The use of lipid-based formulations (LBFs) can be hindered by low dose loading due to solubility limitations of candidate drugs in lipid vehicles. Formation of lipophilic salts through pairing these drugs with a lipophilic counterion has been demonstrated as a potential means to enhance dose loading in LBFs. This study investigated the screening of appropriate counterions to form lipophilic salts of the BCS class IV drug venetoclax. The physical properties, lipid solubility, and in vitro performance of the salts were analyzed. This study illustrated the versatility of alkyl sulfates and sulfonates as suitable counterions in lipophilic salt synthesis with up to ∼9-fold higher solubility in medium- and long-chain LBFs when compared to that of the free base form of venetoclax. All salts formulated as LBFs displayed superior in vitro performance when compared to the free base form of the drug due to the higher initial drug loadings in LBFs and increased affinity for colloidal species. Further, in vitro studies confirmed that venetoclax lipophilic salt forms using alkyl chain counterions demonstrated comparable in vitro performance to venetoclax docusate, thus reducing the potential for laxative effects related to docusate administration. High levels of the initial dose loading of venetoclax lipophilic salts were retained in a molecularly dispersed state during dispersion and digestion of the formulation, while also demonstrating increased levels of saturation in biorelevant media. The findings of this study suggest that alkyl chain sulfates and sulfonates can act as a suitable alternative counterion to docusate, facilitating the selection of counterions that can unlock the potential to formulate venetoclax as an LBF.

In vitro dissolution/permeation tools for amorphous solid dispersions bioavailability forecasting I: Experimental design for PermeaLoop™

Along with the increasing demand for candidate-enabling formulations comes the need for appropriate in vitro bioavailability forecasting. Dissolution/permeation (D/P) systems employing cell-free permeation barriers are increasingly gaining interest, due to their low cost and easy application as passive diffusion bio-predictive profiling in drug product development, as this accounts for nearly 75% of new chemical entities (NCEs) absorption mechanism. To this end, this study comprises theoretical considerations on the design and experimental work towards the establishment and optimization of a PermeaLoop™ based dissolution/permeation assay to simultaneously evaluate the drug release and permeation using Itraconazole (ITZ)-based amorphous solid dispersions (ASD) formulations, with different drug loads, based on a solvent-shift approach. Alternative method conditions were tested such as: donor medium, acceptor medium and permeation barrier were screened using both PermeaPad® and PermeaPlain® 96-well plates. A range of solubilizers, namely Sodium Dodecyl Sulfate, Vitamin E-TPGS and hydroxypropyl-β-cyclodextrin, were screened as possible solubilizing additives to the acceptor medium, while donor medium was varied between blank FaSSIF (phosphate buffer) and FaSSIF. The method optimization also included the ITZ dose selection, being the ITZ single dose (100 mg) considered the most adequate to be used in further experiments to allow the comparison with in vivo studies. In the end, a standardized approach that may be applied to predict the bioavailability of weakly basic poorly soluble drug-based formulations is described, contributing to strengthening the analytical portfolio of in vitro pre-clinical drug product development.

In vitro dissolution/permeation tools for amorphous solid dispersions bioavailability forecasting II: Comparison and mechanistic insights

Along with the increasing demand for complex formulations comes the need for appropriate in vitro methodologies capable of predicting their corresponding in vivo performance and the mechanisms controlling the drug release which can impact on in vivo drug absorption. In vitro dissolution-permeation (D/P) methodologies that can account for the effects of enabling formulations on the permeability of drugs are increasingly being used in performance ranking during early development stages. This work comprised the application of two different cell-free in vitro D/P setups: BioFLUX™ and PermeaLoop™ to evaluate the dissolution-permeation interplay upon drug release from itraconazole (ITZ)- HPMCAS amorphous solid dispersions (ASDs) of different drug loads. A solvent-shift approach was employed, from a simulated gastric environment to a simulated intestinal environment in the donor compartment. PermeaLoop™ was then combined with microdialysis sampling to separate the dissolved (free) drug from other species present in solution, like micelle-bound drug and drug-rich colloids, in real time. This setup was applied to clarify the mechanisms for drug release and permeation from these ASDs. In parallel, a pharmacokinetic study (dog model) was conducted to assess the drug absorption from these ASDs and to compare the in vivo results with the data obtained from each in vitro D/P setup, allowing to infer which would be the most adequate setup for ASD ranking. Even though both D/P systems resulted in the same qualitative ranking, BioFLUX™ overpredicted the difference between the in vivo AUC of two ASDs, whereas PermeaLoop™ permeation flux resulted in a good correlation with the AUC observed in pharmacokinetic studies (dog model) (R2 ≈ 0.98). Also, PermeaLoop™ combined with a microdialysis sampling probe clarified the mechanisms for drug release and permeation from these ASDs. It demonstrated that the free drug was the only driving force for permeation, while the drug-rich colloids kept permeation active for longer periods by acting as drug reservoirs and maintaining constant high levels of free drug in solution, which are then immediately able to permeate. Hence, the data obtained points BioFLUX™ and PermeaLoop™ applications to different momentums in the drug product development pipeline: while BioFLUX™, an automated standardized method, poses as a valuable tool for initial ASD ranking during the early development stages, PermeaLoop™ combined with microdialysis sampling allows to gain mechanistic understanding of the dissolution-permeation interplay, being crucial to fine tune and identify leading ASD candidates prior to in vivo testing.

Strategizing Spray Drying Process Optimization for the Manufacture of Redispersible Indomethacin Nanoparticles Using Quality-by-Design Principles

The present study adopted a Quality by Design (QbD) approach to spray dry indomethacin nanosuspension (IMC-NS) consisting of HPC-SL, poloxamer 407, and lactose monohydrate. The Box-Behnken Design was used to systematically evaluate the effects of inlet temperature, aspiration rate, and feed rate on the critical quality attributes (CQAs) [redispersibility index (RDI; minimize), % yield (maximize), and % release at 15 min (maximize)] of the indomethacin spray dried nanosuspension (IMC-SD-NS). To identify significant main and quadratic effects, two-way interactions, and create a predictive model for the spray drying process, regression analysis and ANOVA were utilized. Following optimization, the IMC-SD-NS was analyzed for its physicochemical properties using X-ray powder diffraction (XRPD), Fourier transform infrared spectroscopy (FTIR), and in vitro dissolution studies. Statistical analysis revealed significant independent variables, including inlet temperature, feed rate, and aspiration rate, that critically impacted the solidified end product's RDI, % yield, and % release at 15 min. The models developed for critical quality attributes (CQAs) were significant at a p-value of 0.05. The crystalline state of IMC was maintained in the solidified product, as confirmed by XRPD, and no interactions were observed between IMC and the excipients as evaluated by FTIR. In vitro dissolution studies showed improved dissolution rate for the IMC-SD-NS (3.82-fold increase in overall drug release), which may be attributed to the readily redispersible nanosized drug particles. The implementation of a well-designed study, utilizing Design of Experiments (DoE) methodology, played a crucial role in the development of a highly effective spray drying process.

Trends in oral small-molecule drug discovery and product development based on product launches before and after the Rule of Five

In 1997, the 'Rule of Five' (Ro5) suggested physicochemical limitations for orally administered drugs, based on the analysis of chemical libraries from the early 1990s. In this review, we report on the trends in oral drug product development by analyzing products launched between 1994 and 1997 and between 2013 and 2019. Our analysis confirmed that most new oral drugs are within the Ro5 descriptors; however, the number of new drug products of drugs with molecular weight (MW) and calculated partition coefficient (clogP) beyond the Ro5 has slightly increased. Analysis revealed that there is no single scientific or technological reason for this trend, but that it likely results from incremental advances are being made in molecular biology, target diversity, drug design, medicinal chemistry, predictive modeling, drug metabolism and pharmacokinetics, and drug delivery.

The Influence of Blonanserin Supersaturation in Liquid and Silica Stabilised Self-Nanoemulsifying Drug Delivery Systems on In Vitro Solubilisation

Reformulating poorly water-soluble drugs as supersaturated lipid-based formulations achieves higher drug loading and potentially improves solubilisation and bioavailability. However, for the weak base blonanserin, silica solidified supersaturated lipid-based formulations have demonstrated reduced in vitro solubilisation compared to their liquid-state counterparts. Therefore, this study aimed to understand the influence of supersaturated drug load on blonanserin solubilisation from liquid and silica solidified supersaturated self-nanoemulsifying drug delivery systems (super-SNEDDS) during in vitro lipolysis. Stable liquid super-SNEDDS with varying drug loads (90-300% of the equilibrium solubility) were solidified by imbibition into porous silica microparticles (1:1 lipid: silica ratio). In vitro lipolysis revealed greater blonanserin solubilisation from liquid super-SNEDDS compared to solid at equivalent drug saturation levels, owing to strong silica-BLON/lipid interactions, evidenced by a significant decrease in blonanserin solubilisation upon addition of silica to a digesting liquid super-SNEDDS. An increase in solid super-SNEDDS drug loading led to increased solubilisation, owing to the increased drug:silica and drug:lipid ratios. Solidifying SNEDDS with silica enables the fabrication of powdered formulations with higher blonanserin loading and greater stability than liquid super-SNEDDS, however at the expense of drug solubilisation. These competing parameters need careful consideration in designing optimal super-SNEDDS for pre-clinical and clinical application.

Trends in small molecule drug properties: A developability molecule assessment perspective

Developability molecule assessment is a key interfacial capability across the biopharmaceutical industry, screening and staging molecules discovered by medicinal chemists for successful chemistry manufacturing controls (CMC) development and launch. The breadth of responsibility and expertise such teams possess puts them in a unique position to understand the impact of the physicochemical properties of a drug during its initial discovery and subsequent development. However, most of the publications describing trends in physicochemical properties are written from a medicinal chemistry perspective with the aim to identify molecules with better ADMET profiles that are either lead-like or drug-like, failing to describe the impact these properties have on CMC development. To systematically uncover knowledge obtained from recent trends in physicochemical properties and the corresponding impact on CMC development, a comprehensive analysis was conducted on molecules in the drug repurposing hub dataset. The only physicochemical property that seems to have been preserved in FDA-approved oral molecules over the decades (1900-2020) is a constant H-bond donor count, highlighting the importance this property has on cell permeability and lattice energy. Pharmaceutical attrition analysis suggests that partition-distribution coefficient, H-bond acceptors, polar surface area and the fraction of sp³ carbons are properties that are associated with compound attrition. Looking at pharmaceutical attrition asynchronously with the temporal analysis of FDA-approved oral molecules highlights the opposing trends, risks and diminishing effects some of these physiochemical properties (cLogP, cLogD and Fsp3) have on describing compound attrition during the past decade. Trellising the dataset by target class suggests that certain formulation and drug delivery strategies can be anticipated or put into place based on target class of a molecule. For example, molecules binding to nuclear hormone receptors are amenable to lipid-based drug delivery systems with proven commercial success. Although the poor solubility of kinase inhibitors is a combination of hydrophobicity (due to aromaticity) required to bind to its target and high lattice energy (melting point), they are a challenging target class to formulate. The influence of drug targets on physicochemical properties and the temporal nature of these properties is highlighted when comparing molecules in the drug repurposing dataset to those developed at Amgen. An improved understanding of the impact of molecular properties on performance attributes can accelerate decisions and facilitate risk assessments during candidate selection and development.

Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series

A webinar series that was organised by the Academy of Pharmaceutical Sciences Biopharmaceutics focus group in 2021 focused on the challenges of developing clinically relevant dissolution specifications (CRDSs) for oral drug products. Industrial scientists, together with regulatory and academic scientists, came together through a series of six webinars, to discuss progress in the field, emerging trends, and areas for continued collaboration and harmonisation. Each webinar also hosted a Q&A session where participants could discuss the shared topic and information. Although it was clear from the presentations and Q&A sessions that we continue to make progress in the field of CRDSs and the utility/success of PBBM, there is also a need to continue the momentum and dialogue between the industry and regulators. Five key areas were identified which require further discussion and harmonisation.

Acetic Acid as Processing Aid Dramatically Improves Organic Solvent Solubility of Weakly Basic Drugs for Spray Dried Dispersion Manufacture

Many active pharmaceutical ingredients (APIs) in the pharmaceutical pipeline require bioavailability enhancing formulations due to very low aqueous solubility. Although spray dried dispersions (SDDs) have demonstrated broad utility in enhancing the bioavailability of such APIs by trapping them in a high-energy amorphous form, many new chemical entities (NCEs) are poorly soluble not just in water, but in preferred organic spray drying solvents, e.g., methanol (MeOH) and acetone. Spraying poorly solvent soluble APIs from dilute solutions leads to low process throughput and small particles that challenge downstream processing. For APIs with basic pKa values, spray solvent solubility can be dramatically increased by using an acid to ionize the API. Specifically, we show that acetic acid can increase API solubility in MeOH:H2O by 10-fold for a weakly basic drug, gefitinib (GEF, pKa 7.2), by ionizing GEF to form the transient acetate salt. The acetic acid is removed during drying, resulting in a SDD of the original GEF free base having performance similar to SDDs sprayed from solvents without acetic acid. The increase in solvent solubility enables large scale manufacturing for these challenging APIs by significantly increasing the throughput and reducing the amount of solvent required.

Insights into the Release Mechanisms of ITZ:HPMCAS Amorphous Solid Dispersions: The Role of Drug-Rich Colloids

Understanding the dissolution mechanisms of amorphous solid dispersions (ASDs) and being able to link enhanced drug exposure with process parameters are key when formulating poorly soluble compounds. Thus, in this study, ASDs composed by itraconazole (ITZ) and hydroxypropylmethylcellulose acetate succinate (HPMCAS) were formulated with different polymer grades and drug loads (DLs) and processed by spray drying with different atomization ratios and outlet temperatures. Their in vitro performance and the ability to form drug-rich colloids were then evaluated by a physiologically relevant dissolution method. In gastric media, drug release followed a diffusion-controlled mechanism and drug-rich colloids were not formed since the solubility of the amorphous API at pH 1.6 was not exceeded. After changing to intestinal media, the API followed a polymer dissolution-controlled release, where the polymer rapidly dissolved, promoting the immediate release of API and thus leading to liquid-liquid phase separation (LLPS) and consequent formation of drug-rich colloids. However, the release of API and polymer was not congruent, so API surface enrichment occurred, which limited the further dissolution of the polymer, leading to a drug-controlled release. ASDs formulated with M-grade showed the highest ability to maintain supersaturation and the lowest tendency for AAPS due to its good balance between acetyl and succinoyl groups, and thus strong interactions with both the hydrophobic drug and the aqueous dissolution medium. The ability to form colloids increased for low DL (15%) and high specific surface area due to the high amount of polymer released until the occurrence of API surface enrichment. Even though congruent release was not observed, all ASDs formed drug-rich colloids that were stable in the solution until the end of the dissolution study (4 h), maintaining the same size distribution (ca. 300 nm). Drug-rich colloids can, in vivo, act as a drug reservoir replenishing the drug while it permeates. Designing ASDs that are prone to form colloids can overcome the solubility constraints of Biopharmaceutics Classification System (BCS) II and IV drugs, posing as a reliable formulation strategy.

Best practices in current models mimicking drug permeability in the gastrointestinal tract - an UNGAP review

The absorption of orally administered drug products is a complex, dynamic process, dependent on a range of biopharmaceutical properties; notably the aqueous solubility of a molecule, stability within the gastrointestinal tract (GIT) and permeability. From a regulatory perspective, the concept of high intestinal permeability is intrinsically linked to the fraction of the oral dose absorbed. The relationship between permeability and the extent of absorption means that experimental models of permeability have regularly been used as a surrogate measure to estimate the fraction absorbed. Accurate assessment of a molecule's intestinal permeability is of critical importance during the pharmaceutical development process of oral drug products, and the current review provides a critique of in vivo, in vitro and ex vivo approaches. The usefulness of in silico models to predict drug permeability is also discussed and an overview of solvent systems used in permeability assessments is provided. Studies of drug absorption in humans are an indirect indicator of intestinal permeability, but in vitro and ex vivo tools provide initial screening approaches are important tools for direct assessment of permeability in drug development. Continued refinement of the accuracy of in silico approaches and their validation with human in vivo data will facilitate more efficient characterisation of permeability earlier in the drug development process and will provide useful inputs for integrated, end-to-end absorption modelling.

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.

Artificial Neural Networks to Predict the Apparent Degree of Supersaturation in Supersaturated Lipid-Based Formulations: A Pilot Study

In response to the increasing application of machine learning (ML) across many facets of pharmaceutical development, this pilot study investigated if ML, using artificial neural networks (ANNs), could predict the apparent degree of supersaturation (aDS) from two supersaturated LBFs (sLBFs). Accuracy was compared to partial least squares (PLS) regression models. Equilibrium solubility in Capmul MCM and Maisine CC was obtained for 21 poorly water-soluble drugs at ambient temperature and 60 °C to calculate the aDS ratio. These aDS ratios and drug descriptors were used to train the ML models. When compared, the ANNs outperformed PLS for both sLBF_Capmul^MC (r² 0.90 vs. 0.56) and sLBF_Maisine^LC (r² 0.83 vs. 0.62), displaying smaller root mean square errors (RMSEs) and residuals upon training and testing. Across all the models, the descriptors involving reactivity and electron density were most important for prediction. This pilot study showed that ML can be employed to predict the propensity for supersaturation in LBFs, but even larger datasets need to be evaluated to draw final conclusions.

Exploring porcine gastric and intestinal fluids using microscopic and solubility estimates: Impact of placebo self-emulsifying drug delivery system administration to inform bio-predictive in vitro tools

Validation and characterisation of in vitro and pre-clinical animal models to support bio-enabling formulation development is of paramount importance. In this work, post-mortem gastric and small intestinal fluids were collected in the fasted, fed state and at five sample-points post administration of a placebo Self-Emulsifying Drug Delivery System (SEDDS) in the fasted state to pigs. Cryo-TEM and Negative Stain-TEM were used for ultrastructure characterisation. Ex vivo solubility of fenofibrate was determined in the fasted-state, fed-state and post-SEDDS administration. Highest observed ex vivo drug solubility in intestinal fluids after SEDDS administration was used for optimising the biorelevant in vitro conditions to determine maximum solubility. Under microscopic evaluation, fasted, fed and SEDDS fluids resulted in different colloidal structures. Drug solubility appeared highest 1 hour post SEDDS administration, corresponding with presence of SEDDS lipid droplets. A 1:200 dispersion of SEDDS in biorelevant media matched the highest observed ex vivo solubility upon SEDDS administration. Overall, impacts of this study include increasing evidence for the pig preclinical model to mimic drug solubility in humans, observations that SEDDS administration may poorly mimic colloidal structures observed under fed state, while microscopic and solubility porcine assessments provided a framework for increasingly bio-predictive in vitro tools.

Self-Nanoemulsifying Drug Delivery System of Genkwanin: A Novel Approach for Anti-Colitis-Associated Colorectal Cancer

PURPOSE

The aim of the present study was to develop an optimized Genkwanin (GKA)-loaded self-nanoemulsifying drug delivery system (SNEDDS) formulation to enhance the solubility, intestinal permeability, oral bioavailability and anti-colitis-associated colorectal cancer (CAC) activity of GKA.

METHODS

We designed a SNEDDS comprised oil phase, surfactants and co-surfactants for oral administration of GKA, the best of which were selected by investigating the saturation solubility, constructing pseudo-ternary phase diagrams, followed by optimizing thermodynamic stability, emulsification efficacy, self-nanoemulsification time, droplet size, transmission electron microscopy (TEM), drug release and intestinal permeability. In addition, the physicochemical properties and pharmacokinetics of GKA-SNEDDS were characterized, and its anti-colitis-associated colorectal cancer (CAC) activity and potential mechanisms were evaluated in AOM/DSS-induced C57BL/6J mice model.

RESULTS

The optimized nanoemulsion formula (OF) consists of Maisine CC, Labrasol ALF and Transcutol HP in a weight ratio of 20:60:20 (w/w/w), in which ratio the OF shows multiple improvements, specifically small mean droplet size, excellent stability, fast release properties as well as enhanced solubility and permeability. Pharmacokinetic studies demonstrated that compared with GKA suspension, the relative bioavailability of GKA-SNEDDS was increased by 353.28%. Moreover, GKA-SNEDDS not only significantly prevents weight loss and improves disease activity index (DAI) but also reduces the histological scores of inflammatory cytokine levels as well as inhibiting the formation of colon tumors via inducing tumor cell apoptosis in the AOM/DSS-induced CAC mice model.

CONCLUSION

Our results show that the developed GKA-SNEDDS exhibited enhanced oral bioavailability and excellent anti-CAC efficacy. In summary, GKA-SNEDDS, using lipid nanoparticles as the drug delivery carrier, can be applied as a potential drug delivery system for improving the clinical application of GKA.

Applying Computational Predictions of Biorelevant Solubility Ratio Upon Self-Emulsifying Lipid-Based Formulations Dispersion to Predict Dose Number

Computational approaches are increasingly utilised in development of bio-enabling formulations, including self-emulsifying drug delivery systems (SEDDS), facilitating early indicators of success. This study investigated if in silico predictions of drug solubility gain i.e. solubility ratios (SR), after dispersion of a SEDDS in biorelevant media could be predicted from drug properties. Apparent solubility upon dispersion of two SEDDS in FaSSIF was measured for 30 structurally diverse poorly water soluble drugs. Increased drug solubility upon SEDDS dispersion was observed in all cases, with higher SRs observed for cationic and neutral versus anionic drugs at pH 6.5. Molecular descriptors and solid-state properties were used as inputs during partial least squares (PLS) modelling resulting in predictive models for SR_MC (r² = 0.81) and SR_LC (r² = 0.77). Multiple linear regression (MLR) facilitated generation of simplified SR equations with high predictivity (SR_MC r² = 0.74; SR_LC r² = 0.69), requiring only three drug properties; partition coefficient at pH 6.5 (logD_6.5), melting point (Tm) and aromatic bonds as fraction of total bonds (F-AromB). Through using the equations to inform developability classification system (DCS) classes for drugs that have already been licensed as lipid-based formulations, merits for development with SEDDS was predicted for 2/3 drugs.