Pharmaceutics

Introduction: Many orally administered drugs are either unstable in the acidic environment of the stomach or cause moderate to severe side effects in the upper gastrointestinal tract (GIT). These limitations can reduce therapeutic efficacy, discourage patient compliance, worsen the disease, and even contribute to the risk of cancer development. To overcome these issues, drug release often needs to be modified and targeted to the distal parts of the GIT . This is typically achieved through the use of pH-sensitive polymer coatings or incorporation into polymeric delivery systems. With this in mind, the aim of this project was to design, develop, and characterize gellan gum-based beads for colon-specific prolonged release of mesalazine, with potential application in the chemoprevention and treatment of bowel diseases. Materials and Methods: The dehydrated capsules were characterized using Raman spectroscopy and scanning electron microscopy. The crosslinked gellan gum was additionally evaluated for cytotoxicity. Key parameters such as pH-dependent swelling behavior, drug content, encapsulation efficiency, and drug release in simulated gastrointestinal fluids were also assessed. Furthermore, the behavior of the capsules in the gastrointestinal tract was studied in a rat model to evaluate their in vivo performance. Results: Significant differences in drug release profiles were observed between formulations crosslinked solely with calcium ions and those additionally crosslinked with glutaraldehyde (GA). The incorporation of GA effectively prolonged the release of mesalazine. These findings were further supported by in vivo studies conducted on Wistar rats, where the GA-crosslinked formulation demonstrated a markedly extended release compared to the formulation prepared using only ionotropic gelation. Conclusions: The combination of ionotropic gelation and glutaraldehyde crosslinking in gellan gum-based beads appears to be a promising strategy for achieving colon-specific prolonged release of mesalazine, facilitating targeted delivery to the distal regions of the gastrointestinal tract.

Abstract: The food-induced viscosity of the media can alter tablet disintegration and eventually the release of the drug it contains. The extent of this retardation depends on tablet formulation factors, such as the solubility of its excipients. Objectives: This research aimed to study the effect of filler solubility on the disintegration and dissolution of tablets under different testing conditions. Methods: Tablet formulations containing acetaminophen (as a model compound), mixtures of different ratios of fillers, and other excipients were directly compressed using uniform manufacturing parameters. These formulations were investigated under fasted-and fed-state conditions to determine the influence of viscosity on their disintegration, inspired by the liquid penetration ratio (LPR) theoretical framework. Disintegration and dissolution tests were performed using both compendial and novel testing apparatuses. Results: The soluble fillers in the tablets affected their disintegration and dissolution in the simulated fed-state medium, while fasted-state conditions affected the tablets only marginally. The testing devices showed partially contrasting results, which appeared to be due to the hydrodynamics of the testing media used. The novel CNC (computed numerical control) apparatus offered 3D motion and effectively exposed the tablets to the viscous testing media, unlike the compendial paddle apparatus. Conclusions: This study explored the impact of filler solubility on the disintegration and dissolution of tablets. As the LPR framework revealed, fillers with a higher solubility have positive effects on the disintegration and dissolution of tablets in viscous conditions. Additionally, the proportion of soluble filler used is also inversely correlated with the disintegration time. Further investigation of the formulation parameters, as well as the testing conditions, would provide additional insights into the effects of food on these tablets.

Background/Objectives: Microfluidic mixing has become the gold standard procedure for manufacturing nucleic acid lipid-based delivery systems, offering precise control over critical process parameters. The choice and design of microfluidic mixers are often seen as a key driving force affecting the critical quality attributes of the resulting lipid nanoparticles (LNPs). Methods: This study aimed to evaluate LNPs manufactured using two low-cost microfluidic mixers alongside manual mixing (pipette mixing (PM)), followed by characterization studies using orthogonal analytics as well as expression studies to establish whether low-cost microfluidic manufacturing methods are suitable for bench-scale and high-throughput research. Results: The results show that all manufacturing methods can produce LNPs with sizes ranging between 95 and 215 nm with high encapsulation (70–100%), and enhanced analytics showed variations between the LNPs produced using the different mixers. Despite these differences, pipette mixing production of LNPs demonstrated its application as a high-throughput screening tool for LNPs, effectively distinguishing between different formulations and predicting consistent expression patterns both in vitro and in vivo. Conclusions: Overall, these results validate the use of low-cost microfluidic mixers without compromising the efficiency and integrity of the resulting LNPs. This study supports the increased accessibility of small-scale LNP manufacturing and high-throughput screening.

Objectives: Hot-melt extrusion (HME) offers a solvent-free, scalable approach for manufacturing pharmaceutical co-crystals (CCs), aligning with the industry’s shift to continuous manufacturing (CM). However, challenges like undefined yield optimization, insufficient risk management, and limited process analytical technology (PAT) integration hinder its industrial application. This study aimed to develop a proof-of-concept HME platform for CCs, assess process risks, and evaluate PAT-enabled monitoring to facilitate robust production. Methods: Using carbamazepine (CBZ) and nicotinamide (NIC) as model compounds, an HME platform compatible with PAT tools was established. A systematic risk assessment identified five key risk domains: materials, machinery, measurement, methods, and other factors. A Box–Behnken design of experiments (DoE) evaluated the impact of screw speed, temperature, and mixing sections on CC quality. Near-infrared (NIR) spectroscopy monitored CBZ-NIC co-crystal formation in real time during HME process. Results: DoE revealed temperature and number of mixing sections significantly influenced particle size (D50: 2.0–4.0 μm), while screw speed affected efficiency. NIR spectroscopy detected a unique CC absorption peak at 5008.3 cm⁻¹, enabling real-time structural monitoring with high accuracy (R² = 0.9999). Risk assessment highlighted material attributes, process parameters, and equipment design as critical factors affecting CC formation. All experimental batches yielded ≥ 94% pure CCs with no residual starting materials, demonstrating process reproducibility and robustness. Conclusions: Overall, this work successfully established a continuous hot-melt extrusion (HME) process for manufacturing CBZ-NIC co-crystals, offering critical insights into material, equipment, and process parameters while implementing robust in-line NIR monitoring for real-time quality control. Additionally, this work provides interpretable insights and serves as a basis for future machine learning (ML)-driven studies.

Background/Objectives: A specially designed chamber setup for containment investigations of pharmaceutical dusts was recently developed. The aim of the present study was to optimize the measurement procedure with this chamber setup, focusing on the atomization parameters. The optimization was aimed at a maximization of the amount of detected dust and a minimization of the required sample mass. Methods: For this purpose, the safe surrogate substance acetaminophen was used for dust measurements. In addition to the atomization parameters investigated by a design of experiments, the cleaning of the chamber setup and the selection of two different types of acetaminophen with different physicochemical properties were examined. Results: By altering the cleaning method of the chamber setup, more than a tenfold increase of detected acetaminophen was observed. In addition, by selecting the more appropriate acetaminophen type, the totally detected acetaminophen amount was further increased by more than 25%. By means of the design of experiments two models were developed, one dealing with the atomization parameters with regard to the atomization effectiveness and the other describing their influence on the spatial dust distribution of acetaminophen. Based on the model for atomization effectiveness, the totally detected acetaminophen amount may be increased by more than double at a constant sample mass. Conclusions: In summary, the measurement procedure of the chamber setup was optimized in terms of the cleaning method, surrogate choice, and the adjustment of the atomization parameters, giving valuable insights to deepen our understanding of dustiness and the spatial distribution of dust in the context of containment.

Background/Objectives: In the past, many drug release models have been presented which attempt to describe the interaction of drugs and excipients in a formulation. Nevertheless, modeling the intrinsic dissolution behavior is essential for understanding the fundamental dissolution mechanisms of drugs and for enhancing the quality of computational approaches in the long term. Methods: In this study, the intrinsic dissolution of various pharmaceutical model substances (benzocaine, carbamazepine, griseofulvin, ibuprofen, naproxen, phenytoin, theophylline monohydrate, and trimethoprim) was investigated in dissolution experiments, taking into account the flow conditions in a dissolution channel apparatus. A practicable and generally valid representation was identified to describe the diffusion properties of the drugs in terms of the boundary layer thickness without considering the particle size distribution, physical state, or viscoelastic properties. This representation was supported by numerical simulations using a high-resolution mesh. The influence of the topography on the modeling was also examined. Results: Besides the prediction of the influence of a surface reaction limitation or the solubility of a diffusion controlled drug, the boundary layer thickness at the tablet surface is modellable in terms of a freely selectable length and as a function of the diffusion coefficient, drug solubility, and the flow velocity of the dissolution medium. Conclusions: Using different methods and a large dataset, this study presents a modeling approach that can contribute to a deeper understanding of intrinsic dissolution behavior.

In the original publication [...]

Background/Objective: Antimicrobial resistance (AMR) and therapy-resistant cancer cells represent major clinical challenges, necessitating the development of novel therapeutic strategies. This study explores the use of selenium nanoparticles (SeNPs) and colistin-conjugated selenium nanoparticles (Col-SeNPs) as a dual-function nanotherapeutic against multidrug-resistant Pseudomonas aeruginosa, antifungal-drug-resistant Candida spp., and human breast carcinoma (MCF-7) cells. Methods: SeNPs were synthesized and characterized using UV-Vis spectroscopy, atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and Fourier-transform infrared spectroscopy (FTIR), confirming their nanoscale morphology, purity, and stability. Results: The antimicrobial activity of SeNPs and Col-SeNPs was assessed based on the minimum inhibitory concentration (MIC) and bacterial viability assays. Col-SeNPs exhibited enhanced antibacterial effects against P. aeruginosa, along with significant downregulation of the mexY efflux pump gene, which is associated with colistin resistance. Additionally, Col-SeNPs demonstrated superior antifungal activity against Candida albicans, C. glabrata, and C. krusei compared to SeNPs alone. The anticancer potential of Col-SeNPs was evaluated in MCF-7 cells using the MTT assay, revealing dose-dependent cytotoxicity through apoptosis and oxidative stress pathways. Although MCF-7 is not inherently drug-resistant, this model was used to explore the potential of Col-SeNPs in overcoming resistance mechanisms commonly encountered in cancer therapy. Conclusions: these findings support the promise of Col-SeNPs as a novel approach for addressing both antimicrobial resistance and cancer treatment challenges. Further in vivo studies, including pharmacokinetics and combination therapies, are warranted to advance clinical translation.

Background/Objectives: Acute myeloid leukemia (AML) is an aggressive malignancy marked by high relapse rates and molecular heterogeneity, necessitating the identification of novel therapeutic targets. T-complex protein 1 (TCP1), a chaperonin implicated in protein folding, remains underexplored in AML pathogenesis. This study investigates the functional role of TCP1 in AML progression and evaluates its therapeutic potential. Methods: Using successive generations of xenografted tumor models, we systematically assessed the correlation between TCP1 expression and AML tumorigenicity. Functional consequences of TCP1 silence were evaluated through in vitro proliferation assays and in vivo tumor growth monitoring. Two distinct inhibitory strategies were employed: miR-340-5p-mediated transcriptional silencing and FTY720-induced disruption of TCP1 chaperone activity. Mechanistic insights were derived from ubiquitin–proteasome pathway analysis, cell cycle profiling, and apoptosis assays. Results: High TCP1 expression correlated strongly with enhanced AML tumorigenicity. Knockdown of TCP1 significantly inhibited AML cell growth and induced degradation of AML1-ETO and PLK1 proteins through the ubiquitin–proteasome pathway. miR-340-5p effectively silenced TCP1 expression, exhibiting an inverse correlation with TCP1 levels. FTY720 disrupted TCP1′s chaperone function, leading to cell cycle arrest, apoptosis, and reduced xenograft tumor growth in murine models. Conclusion: Our findings establish TCP1 as a promising therapeutic target for AML. Both miR-340-5p and FTY720 demonstrate potent anti-leukemic effects by suppressing TCP1 activity, highlighting their potential as novel strategies to inhibit AML proliferation and improve therapeutic outcomes.

Background/Objectives: Poly (ADP-ribose) polymerase (PARP) inhibitors have shown significant efficacy in treating BRCA-mutated cancers; however, a significant proportion of patients fail to respond. Emerging evidence highlights the role of PARP in lipid metabolism, suggest-ing its modulation as a novel strategy to regulate tumor progression. Methods: In this study, lipidomics and transcriptomics analyses were conducted to elucidate the mechanisms underlying PARP inhibitor-induced ferroptosis and immune modulation in triple-negative breast cancer (TNBC). Results: We demonstrated that the PARP inhibitor Niraparib significantly reprograms lipid metabolism in TNBC cells, marked by elevated phosphatidylethanolamine (PE) and cholesterol ester (ChE) levels. This metabolic shift was mechanistically linked to upregulation of the cholesterol transporter NPC1L1 via the PARP1-RELA-NPC1L1 signaling axis, which subsequently activated the AKT pathway. Combinatorial treatment with Niraparib and either Ezetimibe (an NPC1L1 inhibitor) or AZD5363 (an AKT inhibitor) synergistically enhanced TNBC cell death by promoting ferroptosis through glutathione depletion and lipid peroxidation. Furthermore, NPC1L1 inhibition amplified PARP inhibitor-induced immune responses, increasing CD8+ T cell infiltration and cytotoxicity in tumors. Conclusions: In conclusion, our findings establish NPC1L1 as a critical mediator of PARP inhibitor efficacy and propose dual targeting of lipid metabolism, providing a new therapeutic approach for the combination treatment of TNBC.

Background/Objectives: The objective of this study was to develop chitosan films plasticized with glycerol for the topical delivery of ascorbic acid and metronidazole. Methods: The films were prepared using a casting technique in which an aqueous ascorbic acid solution served as the solvent, eliminating the need for additional mineral or organic acids. The influence of compositions on film characteristics—specifically mechanical properties and surface pH—was examined, and an optimized formulation was identified using a Box-Behnken design-response surface methodology. Relevant characterization techniques and in vitro evaluations were conducted to assess the properties and performance of the optimized film formulation. Results: Results showed that both glycerol and ascorbic acid contributed to the plasticization of the films. Fourier-transform infrared spectroscopic analysis of the optimized film revealed the formation of chitosan ascorbate and interactions between chitosan and glycerol. In addition, the thermogram and powder X-ray diffractogram demonstrated alterations in the thermal behavior and crystallinity of the embedded bioactive compounds. The developed film possessed the preferred swelling capacity. Moreover, in vitro release studies revealed a co-release pattern, delivering both bioactive compounds simultaneously. Conclusions: These findings suggest that the prepared chitosan-based film could serve as a promising platform for topical delivery.

Background/Objectives: Phosphodiesterase 5 (PDE5) inhibitors, sildenafil, vardenafil, and tadalafil, activate the cyclic guanosine monophosphate pathway resulting in vascular smooth muscle relaxation. They have been tested for a broad variety of conditions from cancer to Alzheimer’s disease with a positive impact. The known mechanism of action of these drugs could not explain such a plethora of effects. We studied the influence of PDE5 inhibitors on lipid bilayers as a possible application point of their action. Methods: To monitor the membrane changes induced by PDE5 inhibitors, the differential scanning microcalorimetry and the molecular dynamics simulation were used. Results: We found that sildenafil, vardenafil, and tadalafil change elastic properties of model membranes: PDE5 inhibitors disorder thin membranes and order thick membranes. Moreover, PDE inhibitors were able to induce lipid interdigitation. To address the biological aspect of the findings, we performed molecular dynamics on smooth muscle cell’s lipid raft treated with PDE5 inhibitors and revealed the increased density of the lipids. Furthermore, we showed that the lipid condensation in the PDE inhibitors presence increases nitric oxide permeability. Conclusions: The obtained results may be of biological relevance as lipid raft thickening might have an impact on membrane protein function. Moreover, improved nitric oxide flow through membrane may partially explain therapeutic action of these drugs. The presented results are useful for finding novel implications for PDE inhibitors.

Background: Advancements in pharmacogenomics, artificial intelligence (AI), and CRISPR gene-editing technology are revolutionizing precision medicine by enabling highly individualized therapeutic strategies. Artificial intelligence-driven computational techniques improve biomarker discovery and drug optimization while pharmacogenomics helps to identify genetic polymorphisms affecting medicine metabolism, efficacy, and toxicity. Genetically editing based on CRISPR presents a precise method for changing gene expression and repairing damaging mutations. This review explores the convergence of these three fields to enhance improved precision medicine. Method: A methodical study of the current literature was performed on the effects of pharmacogenomics on drug response variability, artificial intelligence, and CRISPR in predictive modeling and gene-editing applications. Results: Driven by artificial intelligence, pharmacogenomics allows clinicians to classify patients and select the appropriate medications depending on their DNA profiles. This reduces the side effect risk and increases the therapeutic efficacy. Precision genetic modifications made feasible by CRISPR technology improve therapy outcomes in oncology, metabolic illnesses, neurological diseases, and other fields. The integration of artificial intelligence streamlines genome-editing applications, lowers off-target effects, and increases CRISPR specificity. Notwithstanding these advances, issues including computational biases, moral dilemmas, and legal constraints still arise. Conclusions: The synergy of artificial intelligence, pharmacogenomics, and CRISPR alters precision medicine by letting customized therapeutic interventions. Clinically translating, however, hinges on resolving data privacy concerns, assuring equitable access, and strengthening legal systems. Future research should focus on refining CRISPR gene-editing technologies, enhancing AI-driven pharmacogenomics, and developing moral guidelines for applying these tools in individualized medicine going forward.

Numerous anti-diabetic medications, including metformin, have been explored for their anticancer effects because of the substantial correlation between diabetes and cancer incidence. Metformin has recently gained interest for its anticancer effects against malignancies such as breast cancer, one of the leading causes of death among women worldwide. The cancer-related characteristics of cell proliferation, invasion, migration, and apoptosis are all targeted by metformin. Among breast cancer patients, triple-negative breast cancer (TNBC) is linked to an increased risk of early recurrence and metastases and has poor prognosis. In addition, TNBC has fewer treatment options compared to other breast cancer subtypes because it lacks hormone receptors and human epidermal growth factor receptor 2 (HER2), and it often develops resistance to available treatment options. The current review highlights the recent updates on the mechanistic insights and the efficacy of metformin and metformin-based approaches for the treatment of TNBC. We logically discuss the experimental evidence from the in vitro and in vivo studies exploring metformin’s effects on metabolic pathways, and then its combination with other therapeutic agents, targeting cell signaling pathways, and approaches to enhance metformin’s effects. We also present clinical studies that underscore the beneficial outcomes of metformin or its combination with other agents in TNBC patients.

Background: Hyaluronic acid (HA) – based bioactive hydrogels have emerged as multifunctional platforms for skin bioregeneration. While traditional mesotherapy using multicomponent substances has been widely practiced for improving skin quality, the time-consuming nature of this approach has led to exploration of alternative delivery methods. Aims: This study evaluated the clinical effectiveness of an HA bioactive hydrogel-based bioregeneration system (containing non-stabilized hyaluronic acid and 14 bioactive ingredients) administered via cannula and its impact on facial skin density as assessed by ultrasound imaging. Methods: We conducted a retrospective review of data from 20 female patients aged 30–42 years who received a single cannula-delivered injection of a bioactive hyaluronic acid hydrogel (TEOSYAL® Redensity [I]) in the midface region. The formulation combines the structural benefits of hyaluronic acid with the biochemical stimulation provided by amino acids, antioxidants, minerals, and vitamins. Skin density was measured using high-frequency ultrasound at baseline, immediately post-procedure, and at 3–4 weeks follow-up. A control group of seven individuals received no treatment. Results: Ultrasound assessments revealed a statistically significant increase in skin density (92.7%, p < 0.001) within the treated area compared to no significant changes in the control group. This substantial improvement in dermal architecture demonstrates the efficacy of bioactive hydrogels in stimulating fibroblast function and extracellular matrix regeneration. Patient satisfaction was high, with 85% of patients reporting being satisfied or very satisfied. Side effects were minimal, with minor bruising (10%) and transient swelling (15%). Conclusions: Cannula-delivered bioactive hyaluronic acid hydrogel effectively enhances facial skin density with high patient satisfaction and minimal downtime, demonstrating the potential of advanced hydrogel formulations as multifunctional therapeutic platforms that extend beyond traditional applications into aesthetic and regenerative dermatology.

Background/Objectives: Mebeverine hydrochloride (MBH) is an antispasmodic agent used to regulate bowel movements and relax intestinal smooth muscle, but its application is limited by specific side effects; therefore, this study investigates the effects of previously synthesized MBH-loaded silver nanoparticles (AgNPs) on smooth muscle contractile activity and their anti-inflammatory potential as an alternative delivery system. Methods: The interactions of AgNPs with cholinergic inhibitors, selective antagonists, Ca 2+ blockers, and key neurotransmitters were analyzed. In vitro, albumin denaturation suppression and ex vivo assays evaluated the anti-inflammatory effects of AgNPs-MBH, validated using a DFT in silico approach. To comprehensively assess the systemic impact and IBS treatment potential of AgNPs-MBH, we also examined in vitro their antimicrobial activity and hepatic cell responses, as the liver is a key organ in evaluating the overall safety and efficacy of nanoparticles. Additionally, the drug-release capabilities of Ag NPs were established. Results: Our findings indicate that AgNPs with MBH do not affect blocked cholinergic receptors, but their effects are more pronounced and distinct in amplitude and character than MBH. MBH-loaded AgNPs showed a lower anti-inflammatory effect than MBH but were still better than diclofenac. They also affected hepatic cell morphology and proliferation, suggesting potential for enhanced therapeutic efficacy. Drug-loaded AgNPs are considered not bactericidal. Conclusions: Based on our results, drug-loaded AgNPs might be a promising medication delivery system for MBH and a useful treatment option for IBS. Future in vivo and preclinical experiments will contribute to the establishment of drug-loaded AgNPs in IBS treatment.

Cancer stem cells (CSCs) are essential for the growth of malignancies because they encourage resistance to cancer therapy and make metastasis and relapse easier. To effectively tackle the obstacles presented by CSCs, novel therapeutic approaches are required. Photodynamic therapy (PDT) is a promising treatment option for cancer cells, which uses light-sensitive medications that are activated by light wavelengths. This review investigates the use of PDT to overcome malignancies driven by CSCs that have innate resistance mechanisms. PDT works by causing tumor cells to accumulate photosensitizers (PSs) selectively. The reactive oxygen species (ROS), which kill cells, are released by these PSs when they are stimulated by light. According to recent developments in PDT, its efficacy may go beyond traditional tumor cells, providing a viable remedy for the resistance shown by CSCs. Researchers want to improve the targeted elimination and selective targeting of CSCs by combining PDT with new PSs and customized delivery systems. Studies emphasize how PDT affects CSCs as well as bulk tumor cells. According to studies, PDT not only limits CSC growth but also modifies their microenvironment, which lowers the possibility of recovery. Additionally, studies are being conducted on the utilization of PDT and immunotherapeutic techniques to improve treatment efficacy and overcome inherent resistance of CSCs. In conclusion, PDT is a viable strategy for treating carcinogenesis driven by CSCs. By applying the most recent advancements in PDT technologies and recognizing how it interacts with CSCs, this treatment has the potential to surpass traditional resistance mechanisms and improve the future of cancer patients. Clinical and preclinical studies highlight that combining PDT with CSC-targeted approaches has the potential to overcome current therapy limitations. Future efforts should focus on clinical validation, optimizing light delivery and PS use, and developing effective combination strategies to target CSCs.

Background/Objectives: Physiologically based pharmacokinetic (PBPK) modeling is an important tool in biologic drug development. However, a standardized modeling strategy is currently missing. A cross-industry collaboration developed PBPK models for seven case studies, including monoclonal antibodies, antibody–drug conjugates, and bispecific T-cell engagers, to identify key parameters and establish a workflow to simulate biologic drugs in monkeys and in humans. Methods: PBPK models were developed in the monkey with limited data, including the molecular weight, the binding affinity to FcRn, and the additional systemic clearance of IgG, which is 20% of the total clearance. The binding affinity was only available for human FcRn and corrected for the known species-dependent differences in IgG binding. The strategy of monkey simulations was evaluated with an additional 14 studies published in the literature. Three different scenarios were simulated in humans afterwards: without, with allometrically scaled, and with optimized additional systemic clearance. Results: The plasma peak concentration and the area under the curve were predicted within 50% of the observed data for all studied case examples in the monkey, which demonstrates that sparse input parameters are sufficient for successful predictions in the monkey. Simulations in humans demonstrated the need for additional systemic clearance, because drug exposure was highly overpredicted without an additional systemic clearance term. Allometric scaling improved the predictions, but optimization led to the best fit, which is currently a limitation in the translation from animals to humans. Conclusions: This work highlights the importance of understanding the general mechanisms of drug uptake in different tissue types and cells in both target-dependent and -independent processes.

Background/Objectives: Glioblastoma (GBM) is an aggressive brain tumor with limited treatment options and poor prognosis, largely owing to its heterogeneity and the involvement of multiple intracellular signaling pathways that contribute to drug resistance. While recent advancements in targeted drug combination therapies, such as dabrafenib and trametinib, show promise for certain GBM subgroups, identifying effective drug combinations across the broader GBM population remains a challenge. Integrin-mediated signaling, particularly through Focal Adhesion Kinase (FAK), plays a pivotal role in GBM pathogenesis and invasion, making it a potential therapeutic target and component of future drug combination strategies. Methods: In this study, we utilized a chemogenomic screening approach to identify synergistic drug combinations that target FAK in glioblastoma. We initially employed a CRISPR-engineered GBM model to assess the effects of FAK depletion and subsequently discovered that combining FAK inhibitors such as VS4718 with MEK inhibitors, particularly trametinib, demonstrated synergistic effects. This potent combination was validated using various 2D and 3D assays, including cell viability/apoptosis assessment, synergistic analysis, cellular imaging, and target engagement assays. This combination also effectively inhibited spheroid growth and invasion across a diverse panel of patient-derived GBM stem cells. Molecular mechanisms underlying these effects include suppression of multiple kinase signaling pathways and enhanced apoptosis, elucidated using Reverse-Phase Protein Array (RPPA) profiling and Western blot validation. Result: In vivo, combination therapy significantly reduced the tumor volume in orthotopic transplantation models. Conclusions: These findings suggest that the combination of FAK and MEK inhibitors represents a promising therapeutic strategy to overcome the challenges of GBM treatment.

Advanced biotherapeutic systems such as gene therapy, mRNA lipid nanoparticles, antibody–drug conjugates, fusion proteins, and cell therapy have proven to be promising platforms for delivering targeted biologic therapeutics. Preserving the intrinsic stability of these advanced therapeutics is essential to maintain their innate structure, functionality, and shelf life. Nevertheless, various challenges and obstacles arise during formulation development and throughout the storage period due to their complex nature and sensitivity to various stress factors. Key stability concerns include physical degradation and chemical instability due to various factors such as fluctuations in pH and temperature, which results in conformational and colloidal instabilities of the biologics, adversely affecting their quality and therapeutic efficacy. This review emphasizes key stability issues associated with these advanced biotherapeutic systems and approaches to identify and overcome them. In gene therapy, the brittleness of viral vectors and gene encapsulation limits their stability, requiring the use of stabilizers, excipients, and lyophilization. Keeping cells viable throughout the whole cell therapy process, from culture to final formulation, is still a major difficulty. In mRNA therapeutics, stabilization strategies such as the optimization of mRNA nucleotides and lipid compositions are used to address the instability of both the mRNA and lipid nanoparticles. Monoclonal antibodies are colloidally and conformationally unstable. Hence, buffers and stabilizers are useful to maintain stability. Although fusion proteins and monoclonal antibodies share structural similarities, they show a similar pattern of instability. Antibody–drug conjugates possess issues with conjugation and linker stability. This review outlines the stability issues associated with advanced biotherapeutics and provides insights into the approaches to address these challenges.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by persistent, recurrent, and relapsing inflammation of the mucosal layer. Its pathogenesis is complex and not yet fully understood, with current treatments mainly focused on alleviating symptoms through pharmacological methods. Direct drug administration for UC often leads to poor intestinal bioavailability, suboptimal targeting, and an increased risk of resistance. Therefore, there is an urgent need for effective drug delivery systems. Lipid nanoparticles (LNPs) are promising candidates for UC drug delivery due to their high biocompatibility, stability, and customizable properties. Oral administration, as a preferred treatment approach for UC, offers benefits such as convenience, cost-effectiveness, and better patient compliance. However, oral drug delivery systems must navigate the complex gastrointestinal tract to effectively target colonic lesions, posing significant challenges for LNP-based systems. Researchers are exploring ways to enhance oral delivery efficiency by adjusting LNP composition, surface functionalization, and coating. This article reviews recent advancements in oral LNP research aimed at improving drug delivery efficiency for UC treatment and discusses future prospects.

Objectives: A novel two-step flow-through in vitro lipolysis model was developed for the evaluation of drug release from a self-microemulsifying drug delivery system (SMEDDS). Methods: Firstly, the SMEDDS was dispersed in an acidic medium. Subsequently, the pH was increased, and a lipolytic reaction was immediately initiated, accompanied by medium flow onset. The latter enabled increase of the initial low pH of the medium, improving the physiological relevance of the method by simulating dosage form retainment in the stomach and transfer to the duodenum, which is very important for a weakly basic active pharmaceutical ingredient (API) incorporated in an SMEDDS. Results: Conversely to the traditional pH-stat in vitro lipolysis, the developed method is not established on titration, as the reaction vessel pH is regulated by a medium flow and buffer capacity. Individual parameters, such as pancreatin activity, buffer capacity, and medium shift, were researched using traditional pH-stat in vitro lipolysis prior to their implementation in the flow-through setup. Conclusions: The concentration of the solubilized model API, carvedilol, was increased as pancreatin activity decreased and as buffer capacity increased. The ratios between release profiles obtained under different conditions utilizing the pH-stat and novel two-step flow-through in vitro lipolysis were comparable; however, the differences were more pronounced in the flow-through method.

Objectives: Tumor heterogeneity and acquired resistance to prostate-specific membrane antigen (PSMA) radioligand therapy (PRLT) pose significant challenges to PSMA PET-based diagnosis. This study aimed to develop an Al18F-labeled FAP-targeted tracer and explore the diagnostic value in acquired drug-resistant tumor models. Methods: To identify potential targets for imaging drug-resistant prostate cancer, bioinformatic analysis was employed to correlate FAP expression levels with genes associated with tumor progression and radiotherapy resistance. Molecular docking technology simulations were utilized to screen FAP ligands for optimal binding affinity and target specificity. The most promising ligand, FAP-2286, was radiolabeled with 18F to develop a novel PET imaging agent, Al18F-NOTA-FAP-2286 PET. To evaluate the diagnostic potential of this agent, various tumor models were established. U87 cells were used to optimize the imaging protocol and assess targeting efficiency and 22RV-1-resistant cells co-xenografted with NIH-3T3 cells were used to model acquired drug-resistant prostate cancer. The diagnostic efficacy of Al18F-NOTA-FAP-2286 PET in this acquired drug-resistant model was assessed and validated through immunohistochemical staining of tumor tissue. Results: Bioinformatic analysis confirmed the association between FAP expression and key genes involved in radiotherapy resistance, such as HIF1α, BCL2, ATM, and EGFR. Molecular docking studies demonstrated the strong binding affinity of FAP-2286 to FAPα (−10 kcal/mol). Al18F-NOTA-FAP-2286 PET/CT imaging in U87 tumor-bearing mice revealed accurate targeting of high FAP-expressing xenografts. The imaging characteristics of Al18F-NOTA-FAP-2286 were comparable to 18F-FDG and 68Ga-FAP-2286 but with a prolonged imaging window compared to 68Ga-FAP-2286. In acquired drug-resistant prostate cancer xenograft nude mice, Al18F-NOTA-FAP-2286 could effectively detect tumor lesions, as confirmed by immunohistochemical analysis. Conclusions: Al18F-NOTA-FAP-2286, as a PSMA-independent imaging agent, holds promise as a valuable complementary molecular imaging tool for assessing acquired resistance to PRLT.

Computational intelligence (CI) mimics human intelligence by expanding the capabilities of machines in data analysis, pattern recognition, and making informed decisions. CI has shown promising contributions to advancements in drug discovery, formulation, and manufacturing. Its ability to analyze vast amounts of patient data and optimize drug formulations by predicting pharmacokinetic and pharmacodynamic responses makes it a very useful platform for personalized medicine. The integration of CI with 3D printing further strengthens this potential, as 3D printing enables the fabrication of personalized medicines with precise doses, controlled-release profiles, and complex formulations. Furthermore, the automated and digital capabilities of 3D printing make it suitable for integration with CI. CI has proven useful in predicting material printability, optimizing drug release rates, designing complex structures, ensuring quality control, and improving manufacturing processes in 3D printing. In the context of customizing drug release from 3D-printed products, CI techniques have been applied to predict drug release from input variables and to design geometries that achieve the desired release profile. This review explores the role of CI in customizing drug release from 3D-printed formulations. It provides overview of limitations of 3D printing; how CI can overcome these challenges, and its potential in customizing drug release; a comparison of CI with other methods of optimization; and real-world examples of CI integration in 3D printing.

Objective: This study aimed to develop and characterize the physicochemical properties of a self-emulsion drug delivery system (SNEDDS) incorporating galangal extract (GE) and lemongrass oil (LGO). Then, to develop mouthwash powders containing GE- and LGO-loaded SNEDDS (GL-mouthwash powder) as a promising alternative for preventing and treating denture stomatitis. Methods: The solubility of GE in various vehicles was determined. Subsequently, pseudo-ternary phase diagrams of the different ingredients, oil (LGO), surfactant (Tween® 80), and co-surfactant (Propylene glycol) were selected to develop the SNEDDS. Then, SNEDDS containing GE and LGO (GL-SNEDDS) were prepared and characterized. The optimized liquid GL-SNEDDS was transformed into GL-mouthwash powder by absorbing onto mannitol and blending with a sweetener. Subsequently, various evaluations including drug recovery, moisture content, emulsification time, stability, anti-Candida activity, and in vitro cytotoxicity were performed. Results: The developed SNEDDS formulation improved GE and LGO solubility. The optimized GL-SNEDDS exhibited a small droplet size of 148.2 ± 2.1 nm with a polydispersity index of 0.11 ± 0.03 and a zeta potential of 2.14 ± 0.11 mV. In addition, the GL-mouthwash powder demonstrated a high drug recovery of >80% with a low moisture of <10% and exhibited greater physicochemical stability under accelerated conditions. The developed GL-mouthwash powder rapidly formed a stable nanoemulsion within 2 min after reconstitution. Interestingly, GL-mouthwash powder exhibited strong anti-Candida activity with no toxicity to human fibroblast cells, which demonstrated superior biocompatibility relative to existing commercial products. Conclusions: These findings suggest that GL-mouthwash powder has potential as an alternative prevention and treatment of oral Candida infection.