Search Results (520)

Background/Objectives: Lansoprazole (LNS) is widely used to treat and prevent stomach and intestinal ulcers and as a proton pump inhibitor with low solubility and high permeability. Soluble soybean polysaccharides (SSPS) are well-known disintegrants in food processing but are rarely used in the pharmaceutical field. In this study, we included SSPS as a disintegrant in LNS formulation for pharmaceutical use to investigate the effect of SSPS on the characteristics, dissolution curve, and stability of LNS enteric coated pellets. Methods: The screening of multiple excipients in formulation optimized the release and stability profile of enteric LNS pellets. The final enteric coated LNS pellet containing SSPS were evaluated by LNS crystal form, release profile, and stability. Results: X-ray powder diffraction revealed that this new LNS pellet and commercial reference LNS pellet had similar crystal form by X-ray powder diffraction. Under both long-term and accelerated conditions, these new SSPS-containing LNS pellets had higher release rate and better acid resistance than reference marketed LNS pellets. Conclusions: Inclusion of SSPS in LNS formulation could increase the physicochemical stability of the enteric coated capsules after storage, providing the basis of SSPS for further development and utilization in pharmaceutical formulation as a promising excipient. Full article

Background: Three-dimensional (3D) printing has been established in pharmaceutical sciences for preparing customized dosage forms with intricate release profiles. However, realizing this potential requires complex design strategies and the careful use of various excipients. This study was designed to evaluate the utility of hypromellose acetate succinate (HPMC-AS) as a singular release-modifying excipient for manufacturing oral solid dosage forms via fused deposition modeling (FDM) 3D printing. Methods: The scope of work encompassed comprehensive material characterization, formulation and production of drug-loaded filaments using hot-melt extrusion (HME), subsequent FDM 3D printing of tablet geometries, and in vitro dissolution studies using mebeverine hydrochloride (MebH) as the model drug. Results: Initial HME processing indicated that the HPMC-AS-based filaments were brittle, presenting technical challenges for direct 3D printing. This issue was successfully overcome by incorporating an additional preheating stage into the FDM printing process, which enabled production of the tablets. Dissolution analysis demonstrated that the 3D-printed mebeverine hydrochloride tablets exhibited delayed and sustained-release characteristics. Conclusions: These results confirm the viability of HPMC-AS as a standalone functional excipient in FDM 3D printing to produce tailored, complex drug delivery systems. Full article

Cyclodextrins and chitosan are biomaterials largely used as pharmaceutical excipients due to their biocompatibility, biodegradability, and low/absent toxicity, associated with a number of favorable properties. In particular, cyclodextrins complexation is mainly utilized to improve the physicochemical and biological properties of drugs, including solubility, stability, and bioavailability, and to reduce their irritating effect. Nevertheless, some disadvantages related to the fast removal of the complex from blood circulation after in vivo administration, and possible competition effects for interaction with cyclodextrin between the complexed drug and other molecules present in the biological environment, can reduce their efficacy as drug carriers. On the other hand, chitosan is widely employed to take advantage of its mucoadhesive, controlled/targeted release, and permeation-enhancing properties. However, its almost complete insolubility in water and poor affinity towards hydrophobic molecules (as most drugs are) are considered its main drawbacks, which could strongly limit its applicability. Due to the several beneficial properties of both cyclodextrins and chitosan, their joint use could provide additional favorable effects in drug delivery and help overcome their disadvantages, in particular by combining the complexing/solubilizing ability of the former towards hydrophobic molecules with the mucoadhesive and controlled/targeted release properties of the latter. The present review is intended to provide a critical and comprehensive summary of the main relevant investigations performed in the last twenty-five years regarding the applications and possible advantages that can be obtained by the combined use of cyclodextrins and chitosan in the development of more effective drug delivery systems. Full article

Powder flow is a constant concern in the production of solid dosage forms. Its concise and reliable determination and improvement are challenges for the pharmaceutical industry. Lactose (Lac) and microcrystalline cellulose (MCC) are both widely used pharmaceutical fillers either alone or mixed. In this study, flow determination was performed through methods described on the European Pharmacopoeia. The results obtained showed poor flow and cohesive behavior for Lac and MCC powders and their mixtures (co-processed excipients). The 50% Lac_MCC mixture, with colloidal silicon dioxide (CSD) as the glidant in different proportions, showed relevant improvements in flow. In addition, the effective angle of wall friction (φx), the effective angle of internal friction (φe), arching, and ratholing were also determined, demonstrating the flow behavior in the discharge equipment. Outlet diameters that prevent blockages or insufficient powder flow were also determined. With this study, it was concluded that it was possible to prepare a co-processed excipient with optimal flow behavior composed of Lac_MCC and CSD as a glidant. Full article

Background/Objectives: The high volatility of volatile drugs significantly restricts their clinical applicability. Although excipients capable of strong interactions can reduce volatilization, conventional screening methods rely on empirical trial-and-error, resulting in low efficiency and high resource consumption. To address this limitation, this study introduces an artificial intelligence (AI)-driven strategy for screening drug–excipient interactions. Using d-borneol as a model drug, this approach aims to efficiently identify strongly interacting excipients and develop stable nano-formulations. Methods: High-throughput simulations were performed using the Protenix structure prediction model to evaluate interactions between d-borneol and 472 FDA-approved excipients. The top 50 candidate excipients were selected based on these simu-lations. Molecular docking and stability experiments were conducted to validate the predictions. Results: Molecular docking and stability experiments confirmed the consistency between predicted and experimental results, validating the model’s reliability. Among the candidates, soybean phospholipid (PC) was identified as the optimal excipient. A lyophilized liposomal formulation prepared with PC significantly suppressed the volatilization of d-borneol and improved both thermal and storage stability. Mechanistic investigations indicated that d-borneol stably incorporates into the hydro-phobic region of phospholipids, enhancing membrane ordering via hydrophobic interactions without disturbing the polar headgroups. Conclusions: This study represents the first application of a structure prediction model to excipient screening for volatile drugs. It successfully addresses the stability challenges associated with d-borneol and offers a new paradigm for developing nano-formulations for volatile pharmaceuticals. Full article

Peptide-based biomaterials have emerged as versatile tools for pharmaceutical drug delivery due to their biocompatibility and tunable sequences, yet a comprehensive overview of their categories, mechanisms, and optimization strategies remains lacking to guide clinical translation. This review systematically collates advances in peptide-based biomaterials, covering peptide excipients (cell penetrating peptides, tight junction modulating peptides, and peptide surfactants/stabilizers), self-assembling peptides (peptide-based nanospheres, cyclic peptide nanotubes, nanovesicles and micelles, peptide-based hydrogels and depots), and peptide linkers (for antibody drug-conjugates, peptide drug-conjugates, and prodrugs). We also dissect sequence-based optimization strategies, including rational design and biophysical optimization (cyclization, stapling, D-amino acid incorporation), functional motif integration, and combinatorial discovery with AI assistance, with examples spanning marketed drugs and research-stage candidates. The review reveals that cell-penetrating peptides enable efficient intracellular payload delivery via direct penetration or endocytosis; self-assembling peptides form diverse nanostructures for controlled release; and peptide linkers achieve site-specific drug release by responding to tumor-associated enzymes or pH cues, while sequence optimization enhances stability and targeting. Peptide-based biomaterials offer precise, biocompatible and tunable solutions for drug delivery, future advancements relying on AI-driven design and multi-functional modification will accelerate their transition from basic research to clinical application. Full article

This study evaluates the feasibility of Near-Infrared (NIR) spectroscopy combined with chemometric modeling for monitoring twin-screw melt granulation. Lactose monohydrate was used as a model excipient and polyethylene glycol (PEG 6000) (Sistemas Analíticos S.A, Buenos Aires, Argentina) as a meltable binder. Granules were produced under different processing conditions by varying binder content, screw configuration (kneading or conveying elements), and measurement temperature. NIR spectra were acquired on-line on a conveyor belt and analyzed using Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression. The regression models showed excellent predictive performance for PEG 6000 content in lactose-based granules, with coefficients of determination higher than 0.998 for both raw and preprocessed spectral data. PCA successfully discriminated between granulated and non-granulated materials, as well as between granules produced with different screw configurations, demonstrating the sensitivity of the technique to processing conditions and granule formation mechanisms. In addition, spectral differences associated with measurement temperature were detected, with derivative-based preprocessing improving the discrimination between warm and cooled granules. Overall, the results demonstrate that NIR spectroscopy, coupled with multivariate analysis, is a robust and non-invasive tool for real-time monitoring of twin-screw melt granulation, with strong potential to enhance process understanding, control, and product consistency in continuous pharmaceutical manufacturing. Full article

Background: Powdered mucilages are increasingly being used as natural excipients in pharmaceutical formulations, functioning as binders, disintegrants, thickeners, suspending agents, and film formers. Their swelling, viscosity-enhancing, and biocompatible properties also make them useful in controlled-release systems and tablet production. This study aimed to produce spray-dried Cydonia oblonga (CO) mucilage, examine how drying parameters influence yield, and determine its physicochemical and rheological characteristics to evaluate its suitability for pharmaceutical applications. Methods: Powdered CO mucilage was obtained by spray drying. The obtained powders were characterized on yield, particle size and morphology, moisture content, loss on drying, flow properties and swelling index. Results: The obtained powders show yields of 10.6–16.4%, particle sizes of 4.5–5.39 μm, and moisture contents of 2–3%. Their flowability is limited despite satisfactory angle of repose, Hausner ratio, and Carr index values, yet all powders exhibit excellent swelling properties. Conclusions: Model CM6 of the obtained powdered CO seeds hydrocolloid stands out as the best spray-dried hydrocolloid, combining high drying efficiency, low residual moisture, uniform particle formation, and excellent swelling capacity despite its limited flowability. These properties make it a strong candidate for use as a biopolymer or excipient in pharmaceuticals. Full article

Background: Three-dimensional printing (3DP) is a promising technology for advancing pharmaceutical research by enabling the production of personalized drug products. However, its progress has been hindered by the conventional trial-and-error approach to excipient selection and optimization. Methods: In this study, the blend module was employed to determine the miscibility parameters—mixing energy (E_mix) and Flory–Huggins interaction parameter (χ) to find the right excipients and drug–excipient ratio and examine the incorporation of plasticizers and lipids to enhance printability. Furthermore, molecular dynamics (MD) simulations were employed to calculate the cohesive energy density (CED) for predicting the dissolution behavior of 3DP formulations. Results: Data from 51 formulations were analyzed, enabling correlation and experimental validation of the in silico predictions. The predicted miscibility values demonstrated a strong correlation with experimental printability results. Furthermore, using a miscibility parameter, it was possible to accurately forecast minor changes in the drug-to-excipient ratio, plasticizer/lipid concentration, and hot-melt extrusion (HME) temperature that affect printability. Hydrophilic carriers exhibited lower CED values corresponding to faster drug release. In contrast, more hydrophobic carriers revealed high CED values, indicating stronger drug entrapment and sustained release. Conclusions: The miscibility parameters and MD-simulated CED values provide a practical framework for early-stage, high-throughput excipient screening. Overall, in silico prediction offers a viable strategy for modeling the entire 3DP workflow, minimizing the need for trial-and-error experimentation, and thereby accelerating the clinical translation of 3DP drug delivery systems. Full article

Background/Objectives: This study explores the integration of Design of Experiments (DoE) with Physiologically Based Biopharmaceutics Modeling (PBBM) to streamline the development of extended-release (XR) formulations. Using donepezil (DPZ) as a model drug, we developed an optimized XR formulation exhibiting a dissolution profile comparable to the reference product, Aricept^® (Eisai GmbH, Frankfurt, Germany). Methods: A Box–Behnken experimental design was applied to systematically evaluate how formulation variables—HPMC 100, HPMC 4000, and NaCMC—affect drug release kinetics, tablet hydration, and erosion. This strategy enabled the identification of optimal excipient concentrations with minimal experimental effort. Results: The in vitro dissolution data were then integrated into a PBBM framework to simulate drug release and pharmacokinetics, enabling virtual bioequivalence (VBE) assessments. The combined approach provided robust predictive insights into formulation performance, substantially reducing reliance on resource-intensive in vivo studies. Beyond its successful application with DPZ, this integrated methodology offers a scalable and generalizable strategy for efficiently developing bioequivalent XR formulations for various clinically relevant drugs. Conclusions: Our findings highlight the importance of leveraging advanced statistical methods and in silico modeling to overcome contemporary pharmaceutical development challenges, paving the way for innovative, cost-effective solutions that significantly accelerate time-to-market. Full article

Background: The compaction of formulation blends is a critical stage in pharmaceutical tablet manufacturing, particularly when drug substances or functional excipients exhibit limited flowability and tabletability. Objectives: This study systematically examined the mechanical behaviour of viscoelastic microcrystalline cellulose (MCC) and brittle anhydrous dibasic calcium phosphate (DCPA), as well as their mixtures, to check how deformation mechanisms influence powder handling and tablet performance. Methods: A compaction simulator, mimicking a small rotary tablet press, was used to evaluate tablet weight variability, densification profiles, die-filling height, force–displacement behaviour, and in-die Heckel analysis. Additional assessments included compression times, breaking force, tensile strength, elastic recovery, as well as in-die and out-of-die tablet thickness across various compositions and compaction pressures. Results/Conclusions: Bulk density values from the simulator showed strong correlation with pharmacopeial measurements (R² ≥ 0.997). Measurable differences in true density and cohesiveness led to poor flowability for MCC and good flow for DCPA, with mixtures containing higher DCPA concentration displaying markedly improved flow characteristic. Compaction analyses confirmed extensive plastic deformation for MCC and fragmentation for DCPA. Increasing MCC content elevated die-fill height, compaction energy, and tablet weight variability, whereas higher DCPA fractions decreased apparent density of tablets and reduced energy demand. Tabletability and compressibility profiles reflected that MCC generated hard tablets but exhibited higher elastic recovery, while DCPA formed softer tablets with closer to linear strength–pressure relationships. Energy profiling demonstrated that MCC stored more elastic energy and required higher overall compression work, whereas DCPA reduced elastic accumulation. Overall, blending viscoelastic and brittle excipients offers a robust strategy for optimizing manufacturability, mechanical strength, and energy efficiency in tablet production. Full article

Background/Objectives: Polysorbate 80 (PS80), a complex surfactant mixture, is widely recognized for its ability to enhance drug permeation across the blood–brain barrier (BBB). While this effect is generally attributed to the combined actions of its components, the specific contribution and potential selectivity of individual minor components remain poorly understood. This study therefore aimed to isolate and compare the primary minor components of PS80 to determine whether they uniformly enhance BBB permeation or exhibit drug-specific functions. Methods: In this research, four primary minor components of PS80—polyoxyethylene sorbitan monooleate (PSM), polyoxyethylene isosorbide monooleate (PIM), polyoxyethylene sorbitan dioleate (PSD), and a polyethylene glycol/polyoxyethylene sorbitan/polyoxyethylene isosorbide mixture (PEG/PS/PI mixture)—were isolated using preparative liquid-phase chromatography. Drug-loaded formulations were then prepared using the solvent evaporation method incorporating five model drugs: 1,1′-dioctadecyl-3,3,3′,3′-tetramethylindotricarbocyanine iodide (DiR, MW = 1013.39 Da), donepezil (MW = 379.49 Da), nimodipine (MW = 418.44 Da), chlorogenic acid (MW = 354.31 Da), and paclitaxel (MW = 853.92 Da). The permeability of these formulations across the BBB was evaluated in BALB/c mice after intravenous administration. Brain distribution of the lipophilic dye DiR was assessed using fluorescence imaging, whereas brain homogenate concentrations of therapeutic drugs were quantified by UPLC-MS/MS. Results: Results revealed that the enhancement of brain delivery was dependent on both the specific minor component and the drug. The PEG/PS/PI mixture specially enhanced the brain homogenate concentration of donepezil to 11.8 ± 1.2 ng/mL, representing a 6.9-fold enhancement, while PIM micelles increased the delivery of DiR, donepezil, and nimodipine. In contrast, PSM and PSD micelles improved transport of only DiR and donepezil. The broad performance of PIM suggests a more flexible formulation—a hypothesis that warrants further validation. Conversely, none of the different minor components enhanced the delivery of chlorogenic acid or paclitaxel, underscoring the critical role of specific drug–component interactions. Conclusions: This component-resolved insight challenges the conventional perception of PS80 and provides a rational framework for engineering precision brain-targeted delivery systems by selecting functional minor components. Full article

Artificial intelligence (AI) is transforming pharmaceutical science by shifting drug delivery research from empirical experimentation toward predictive, data-driven innovation. This review critically examines the integration of AI across formulation design, smart drug delivery systems (DDSs), and sustainable pharmaceutics, emphasizing its role in accelerating development, enhancing personalization, and promoting environmental responsibility. AI techniques—including machine learning, deep learning, Bayesian optimization, reinforcement learning, and digital twins—enable precise prediction of critical quality attributes, generative discovery of excipients, and closed-loop optimization with minimal experimental input. These tools have demonstrated particular value in polymeric and nano-based systems through their ability to model complex behaviors and to design stimuli-responsive DDS capable of real-time therapeutic adaptation. Furthermore, AI facilitates the transition toward green pharmaceutics by supporting biodegradable material selection, energy-efficient process design, and life-cycle optimization, thereby aligning drug delivery strategies with global sustainability goals. However, challenges persist, including limited data availability, lack of model interpretability, regulatory uncertainty, and the high computational cost of AI systems. Addressing these limitations requires the implementation of FAIR data principles, physics-informed modeling, and ethically grounded regulatory frameworks. Overall, AI serves not as a replacement for human expertise but as a transformative enabler, redefining DDS as intelligent, adaptive, and sustainable platforms for future pharmaceutical development. Compared with previous reviews that have considered AI-based formulation design, smart DDS, and green pharmaceutics separately, this article integrates these strands and proposes a dual-framework roadmap that situates current AI-enabled DDS within a structured life-cycle perspective and highlights key translational gaps. Full article

Background/Objectives: Silodosin (SLD) is a selective α1A-adrenoceptor antagonist used in the treatment of benign prostatic hyperplasia. Bioequivalence failures have been reported for hard capsule formulations, largely due to the effect of disintegrant excipients, making soft capsules a promising alternative dosage form. This study investigated the stability of SLD soft capsules stored in two different packaging materials, PVC/PVDC and AquaBa^®. Methods: Storage temperatures at 25 °C/60%, 30 °C/65% RH, 30 °C/75% RH, and 40 °C/75% RH, and sampling were performed according to the International Council for Harmonisation (ICH) stability conditions. Assays were performed by HPLC and UV, and mass detection. Results: Degradation analysis revealed that temperature played a critical role in SLD degradation and the formation of its primary degradation products, dehydrosilodosin and impurity 1. Conclusions: AquaBa^® demonstrated superior protective properties compared to PVC/PVDC, preserving SLD content above 95% for over 12 months under 25 °C and 30 °C conditions while limiting the formation of degradation products. Nevertheless, impurity 1 exceeded its ICH Q3B (R2) specification limit (0.3%) after six months under all conditions tested, suggesting a critical interaction between SLD and excipients such as Capryol^® 90. Kinetic modeling confirmed first-order degradation kinetics for both dehydrosilodosin and impurity 1, with a faster degradation rate observed in PVC/PVDC blisters. These findings highlight the critical role of packaging in pharmaceutical stability. While AquaBa^® emerges as the preferred option for SLD soft capsules, formulation optimization remains necessary to limit impurity formation, extend shelf life, and ensure regulatory compliance. Full article