Logo: to the web site of Uppsala University

Treating complex medical conditions often requires the concurrent administration of multiple drugs, either taken simultaneously as separate dosage forms, or as a combination product. This study investigates the impact on the achievable supersaturation of the amorphous formulation when co-administered with a crystalline drug, and the consequences for membrane transport. Non-sink dissolution studies were conducted for a physical mixture of amorphous atazanavir and crystalline darunavir. Flux of atazanavir across a monolayer of Caco-2 cells and across an artificial membrane, was determined in the absence and presence of a pre-equilibrated suspension of darunavir crystals. Miscibility between the drugs was investigated using nano thermal analysis and differential scanning calorimetry. The maximum achievable concentration of atazanavir decreased with increasing darunavir concentration, even when the latter drug was not saturated in the solution. Furthermore, the membrane flux of atazanavir was reduced significantly in the presence of darunavir, indicating that liquid-liquid phase separation occurs at lower supersaturation for atazanavir when darunavir is present. Interestingly, the formation of this colloidal phase of atazanavir also reduced darunavir concentration. The drugs were found to remain phase separated in the dry state, whereas darunavir partitioned into the atazanavir drug-rich phase in aqueous media. This suggests that water facilitated mixing of the drugs in the colloidal phase, which affected the release and membrane transport properties of atazanavir. These findings further illustrate the complexity of formulating or co-administrating multicomponent drugs, even when present in different solid forms, and provide new insights into how amorphous drugs behave when co-administered with crystalline drugs.

Intestinal motility, including peristalsis and segmentation, drives complex fluid movements critical for the oral delivery of biologics and other macromolecules. Despite advances, oral delivery remains commercially limited by low bioavailability, often attributed to poor epithelial permeability. However, variability in motility patterns may also play a critical role, influencing intraluminal distribution and thus absorption, yet this aspect remains underexplored. Here, we combine computational fluid dynamics and machine learning to evaluate how motility type, intensity, pocket size, contractility, and fluid composition affect the delivery of a model macromolecule (insulin) and a permeation enhancer (sodium caprate, C10). We find that segmentation, especially at light intensity, consistently enhances epithelial colocalisation over peristalsis. Under segmentation, smaller pocket sizes (2 mL versus 10 mL) and stronger contractility (occlusion ratio 0.3) yielded optimal performance. Our extreme gradient boosting regression model identified pocket volume, contractility, and motility type as dominant predictors of colocalisation. In a comparative analysis, segmentation led to 128% and 137% higher maximum normalised concentrations of insulin and C10, respectively, than moderate peristalsis with a nutritional drink. Overall, segmentation achieved 6.7-fold and 8.0-fold higher average maximum normalised concentrations for insulin and C10, respectively. These results emphasise segmentation, characteristic of the fed state, as a superior motility pattern for macromolecular absorption compared to peristalsis during the migrating motor complex (MMC). By elucidating the interplay between motility and transport, our findings may guide the design of more effective oral formulations and support personalised strategies for drug delivery based on individual motility profiles.

Liquid crystal nanoparticles (LCNPs), such as hexosomes based on an internal hexagonal phase (H_II), enhance lipid nanoparticle-mediated drug delivery by improving drug solubility, stability and absorption. LCNPs can also be tailored for specific biological environments by incorporating non-ester-linker lipids into the H_II nanostructure. In this study, we developed an H_II model system with a 90:10 phytantriol:farnesol ratio based on experimental data and conducted all-atom molecular dynamics simulations. The model remained stable across various water-to-lipid ratios, and the structural effects observed were consistent with prior experimental data. We used this model to examine the localization and interactions of antibiotics vancomycin and clarithromycin. Clarithromycin, being highly lipophilic, associated mainly with the lipid phase, while vancomycin localized at the water-lipid interface due to its amphiphilic nature. An extended H_II system with repeating units enclosed in Pluronic F127 polymers was also constructed. Simulations showed that hydrogen bonding between Pluronic F127 and water facilitated water influx into the H_II phase, causing interfacial reorganization. To investigate drug release, we performed umbrella sampling simulations. The resulting energy profiles indicated that polymer-water-lipid interactions lowered the energy barrier for vancomycin release compared to clarithromycin. This was confirmed by in vitro release studies, where vancomycin exhibited a higher release rate. Overall, this model provides molecular-level insights into drug loading, partitioning, and release from H_II systems, supporting the design of more effective drug delivery formulations.

Oral delivery of therapeutic peptides is limited by degradation by digestive proteases and poor gastrointestinal permeability. We have investigated how physicochemical properties, including degree of lipidation and degree of amino acid sequence modification, along with formulation with a permeation enhancer (PE), influence the enzymatic stability and intestinal absorption of glucagon-like peptide-1(GLP-1) receptor agonists. We compared four peptides: J211 (non-lipidated; modified), J229 (mono-lipidated; modified), MEDI7219 (bis-lipidated; modified), and semaglutide (mono-lipidated control; least modified). J211, J229 and MEDI7219 have similar amino acid modifications in the peptide sequence to reduce the number of labile proteolytic sites. An in vitro head-to-head comparison between MEDI7219 and semaglutide showed that MEDI7219 was more proteolytically stable (% remaining after 90 min) than semaglutide, which was degraded completely within 10 min. Notably, co-formulation with sodium caprate (C10) improved semaglutide stability, and at least doubled its half-life. Results from in vivo studies in rats following intraduodenal bolus administration, showed that in the absence of C10, the absorption of all the peptides was minimal, with cumulative fractions absorbed below 1 % for all four compounds. Co-formulation with C10 increased the bioavailability of the modified peptides by 35-40-fold, with J211, J229, and MEDI7219 reaching 7.5 %, 4 %, and 17.3 % respectively. Semaglutide's bioavailability improved by similar to 200-fold, however bioavailability did not exceed 2 %. These results demonstrate that C10 enhances peptide absorption primarily by increasing intestinal permeability but also likely by improving enzymatic stability of a labile peptide like semaglutide. Furthermore, when comparing the three modified peptides, the degree of lipidation positively correlated with increased intestinal absorption in both the presence and absence of C10.

The purpose of the study was to develop an amorphous solid dispersion (ASD) of a poorly soluble compound (AK100) and investigate the impact of different surfactants on its dissolution, supersaturation and membrane transport. The solubility of the AK100 was determined in crystalline and amorphous form in the absence and presence of three surfactants at different concentrations: sodium dodecyl sulphate (SDS), polysorbate 80 (PS80) and D-α-tocopherol polyethylene glycol succinate (TPGS). The relation between solubility and surfactant solubilization was evaluated using a computational model. The ASD powder was prepared by solvent evaporation for non-sink dissolution experiments with and without the pre-dissolved surfactants. A transport study with Caco-2 cells was conducted to evaluate the impact of surfactants-based formulation on membrane transport. Both the corresponding crystalline and amorphous solubility of AK100 increased linearly as a function of the surfactant concentrations. The supersaturation was maintained for at least three hours in absence of surfactant and in presence of TPGS, whereas supersaturation declined with SDS and PS80. As expected, the membrane flux of the AK100 was higher for the ASD than for the crystalline powder, and further increased with increased concentration of TPGS. The supersaturation ratio based on the activity-based calculation from Caco-2 cells study was always higher than that of the concentration-based one for the amorphous and crystalline forms of AK100. This study shows how additional solubilizing excipients during formulation development can improve the resulting dissolution and phase behavior of supersaturated drug solution.

Aqueous solubility of a compound plays a crucial role throughout various stages of drug discovery and development. Despite numerous efforts using various machine learning models, accurately estimating aqueous solubility remains a challenge. One primary limitation is the absence of a single source, large dataset of druglike compounds for model training. Additionally, studies have highlighted the need for improvements in prediction algorithms and molecular representations. To address these challenges, the Johnson and Johnson (J&J) in-house solubility data was leveraged. Theoretical pH-solubility equations and in-house pKa prediction tools were utilized to calculate intrinsic solubility from J&J data. A multi-task graph transformer model was developed and trained on the calculated intrinsic solubility data of 13,306 compounds along with seven relevant physicochemical properties including solubility at pH 2/7, logP, and logD at three different pHs. When evaluated making use of high-quality test data, the developed model achieved a root mean square error (RMSE) of 0.61 and coefficient of determination (R2) of 0.60, demonstrating state-of-the-art performance in estimating intrinsic solubility for drug-like compounds.

Antibiotics are essential for treating infections and reducing risks during medical interventions. However, many commonly used antibiotics lack the physiochemical properties for an efficient oral administration when treating systemic infection. Instead, we are reliant on intravenous delivery, which presents complications outside of clinical settings. Developing novel formulations for oral administration is a potential solution to this problem. We engineered hexosome and cubosome liquid crystal nanoparticles (LCNPs) characterized by small-angle X-ray scattering and cryogenic transmission electron microscopy, and could encapsulate the antibiotics vancomycin (VAN) and clarithromycin (CLA) with high loading efficiencies. By rationally choosing stable lipid building blocks, the loaded LCNPs demonstrated excellent resilience against enzymatic degradation in an in vitro gut model LCNP stability is crucial as premature antibiotic leakage can negatively impact the gut microbiota. In screens against the representative gut bacteria Enterococcus faecalis and Escherichia coli, our LCNPs provided a protective effect. Furthermore, we explored co-administration and dual loading strategies of VAN and CLA, and demonstrated effective loading, stability and protection for E. faecalis and E. coli. This work represents a proof of concept for the early-stage development of antibiotic-loaded LCNPs to treat systemic infection via oral administration, opening opportunities for combination antibiotic therapies.

Biosimilar artificial mucus models that mimic native mucus facilitate efficient, lab-based drug diffusion studies, addressing the costly and challenging preclinical phase of drug development, especially for nano- and micro-scale particle-based colonic drug delivery. This study presents a machine-learning-driven framework that integrates microrheological features into diffusional fingerprinting to characterize nano- and micro-scale particle diffusion patterns in mucus and assess the effect of mucus microrheology on such movements. We investigated the diffusion of fluorescent-labeled polystyrene particles in native pig mucus and two artificial mucus models. Particles (100, 200, and 1000 nm in diameter) with carboxylate- or amine-modified surfaces were tracked during passive diffusion. From each particle trajectory, 20 features -including microrheology-based parameters- were extracted. Based on these features, seven supervised machine learning models were applied to classify or identify similarities among mucus hydrogels. Of these, gradient boosting achieved the highest accuracy. SHapley Additive exPlanations analysis identified creep compliance as the most influential feature in distinguishing the mucus models. In native mucus, smaller negatively charged nanoparticles exhibited the highest mobility, with fewer particles being in the immobile and subdiffusive states. Microrheology data further indicated that larger particles experienced greater restriction owing to the elastic properties of native mucus. In contrast, smaller particles interacted more with the viscous liquid phase. A comprehensive feature-wide analysis revealed that hydroxyethyl cellulose (HEC)-based artificial mucus more closely resembled native pig mucus than the polyacrylic acid-based model. In conclusion, the machine-learning-driven fingerprinting approach, incorporating microrheological features, successfully differentiated the microstructural characteristics and rheological properties of the three mucus models. It also supported the selection of HEC-based artificial mucus as a viable substitute for native colonic mucus.

Development of oral drug delivery systems that penetrate the colonic mucus remains challenging. Artificial models of porcine colonic mucus have been developed that mimic the rheology and viscosity of the native mucus and its contents of mucins, protein, and lipids. However, they are less representative with regard to the zeta potential, a factor of importance for charged molecules and particles. This study therefore aimed to improve the existing porcine artificial colonic mucus model by exchanging the polymer backbone (used for viscosity) to more closely mimic the charge of porcine native colonic mucus. Polymers studied were poly(acrylic acid), hydroxyethylcellulose, sodium hyaluronate, sodium alginate, and pectin. The resulting porcine artificial colonic mucus was assayed for apparent viscosity, storage modulus, pH, water content, zeta potential, and pore size. The two best-performing polymers (poly(acrylic acid) and hydroxyethylcellulose) were then assayed with diffusion of FITC-dextran, particle tracking of nanoparticles, and binding of FITC-dextran and contrasted to data generated in porcine native colonic mucus (PNCM). Of the two polymers, PACM based on HEC generated zeta potential and binding kinetics similar to those of PNCM. We conclude that the choice of polymer in PACMs is critical for improving their use in drug development. The extensive characterization of the PACMs further points toward the importance of complementary techniques to determine rheological characteristics, mesh, and pore size.

Despite advances in the field of multidrug formulations, developing and manufacturing them still poses substantial challenges, particularly for drugs with low aqueous solubility. Here, this critical issue was addressed by engineering amorphous multidrug formulations with optimized performance at the site of absorption using the spray drying technique. Formulations containing atazanavir and ritonavir, alone or in combination, were produced by spray drying. Excipient content in aqueous solution was optimized to generate a stable feed suspension of amorphous particles with controlled particle size. The powder formulations were characterized by powder X-ray diffraction (PXRD), thermal analysis, laser diffraction, and scanning electron microscopy (SEM). The drug content was assayed, and a dissolution study was performed. Dynamic light scattering was used to measure particle size of the colloidal phase in the feed suspension and after dissolution of powder. A stability study was conducted at 25 °C/60 % RH and 40 °C/75 % RH condition for 4 weeks. DSC and PXRD confirmed the formulations to be amorphous. Drug content in the spray-dried formulations ranged from 98 to 108 %. Laser diffraction measured the particles to be from 5–10 µm and SEM showed they had wrinkled and irregularly shaped surfaces. The particle size of the colloidal phase formed upon dissolution of combination formulation was stable at 900 nm over 120 min. The formulations remained amorphous under both studied conditions throughout the stability study period. These findings highlight the potential of particle engineering, where a mechanistically informed selection of excipients is combined with an appropriate spray-drying process, to achieve highly stable and robust amorphous multidrug formulations —critical for ensuring effective drug performance and patient treatment.