AAPS PharmSciTech最新文献

Formulation strategies for colonic delivery offer a unique opportunity for the local delivery of drugs for symptomatic relief in inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and colorectal cancer, as well as for the systemic delivery of peptides and biologics. By releasing active pharmaceutical ingredients (APIs) directly at the site of action within the colon, these systems can achieve higher local exposure with reduced systemic effects. This is achieved by utilizing prodrugs, pH-sensitive polymers, time-dependent systems, pressure, microbiota, and multi-pronged systems. Monolithic delivery systems can deliver drugs to the colon with limitations; however, the multiparticulate drug delivery of pellets has proven to be a superior methodology in meeting targets. This review highlights various techniques to bypass the upper part of the gastrointestinal tract, thereby releasing the active pharmaceutical ingredient specifically in various parts of the intestine and colon, to achieve both local and systemic therapeutic effects.

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Natural polymers such as chitosan, alginate, cellulose, gelatin, and silk fibroin have become central to modern drug delivery research due to their biocompatibility, biodegradability, and environmental sustainability. However, variability in source, molecular weight, and crosslinking chemistry often results in inconsistent formulation performance and limited scalability. To overcome these challenges, artificial intelligence (AI) and machine learning frameworks have been increasingly integrated into formulation science under the quality by design paradigm. This review synthesizes current advances in AI-assisted modeling and optimization of natural polymer drug delivery systems, highlighting how predictive algorithms capture nonlinear relationships among polymer structure, process variables, and release kinetics. Neural-network and Bayesian-optimization models demonstrate accurate prediction of encapsulation efficiency and dissolution profiles, while hybrid mechanistic–AI and physics-informed neural networks enhance interpretability by embedding kinetic and diffusion equations. The review also discusses data-generation workflows, FAIR-compliant standards, and polymer-informatics databases that enable interoperable, reproducible modeling. Collectively, these developments establish a pathway toward data-driven, sustainable pharmaceutics, where predictive and eco-designed formulations replace empirical trial-and-error methods. Remaining challenges include dataset standardization, model transparency, and regulatory validation. Addressing these will accelerate the translation of intelligent polymer design into reproducible, scalable, and environmentally responsible drug delivery innovations.

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Mesalamine (MES) remains a first-line therapy for the treatment of inflammatory bowel disease; however, its clinical use is limited by poor aqueous solubility in the colon, high dose requirements, variable pharmacokinetics, pill burden, and patient non-compliance. This study aimed to develop and optimise MES nanocrystals (MES NCs) using a top-down ball milling approach using a stabiliser Hydroxypropyl methylcellulose acetate succinate (HPMC-AS). Thirteen different batches were formulated to assess the effects of speed and time of milling, and polymer concentration on particle size, polydispersity index (PDI), morphology, crystallinity, thermal properties, and dissolution. The B11 batch was evaluated for its biological activity using PMA-differentiated THP 1 cell line treated with LPS using inflammatory markers: IL-4, IL-6, TNFα, and TGF-β. The first reproducibility batches (0.1/400/40; B9-B15) exhibited an intra-batch average particle size of 537.3 ± 139.2 nm with a PDI of 0.5 ± 0.1. SEM analysis confirmed a uniform plate-like morphology. PXRD analysis revealed partial peak shifts and broadening, suggesting lattice strain in the milled NCs. Dissolution studies demonstrated pH-dependent release of MES-NCs. FTIR confirmed drug-polymer compatibility. Cytotoxicity testing in PMA-differentiated THP-1 macrophage-like cells showed > 64% cell viability at therapeutic MES NC concentrations up to 2.5 µM. Type 2 cytokines (IL-4), typically induced by LPS in the late phase, showed a time-dependent response, further supporting the immunomodulatory effect of MES NCs. The B11 batch significantly increased TGF-β expression compared with the disease group, suggesting activation of regulatory anti-inflammatory pathways with M2 macrophage polarisation.

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Natural lipophilic pigments typically exhibit poor water solubility, low dissolution rates, and photothermal instability, which hinder their pharmaceutical application. To address these challenges, a nanosuspension–microencapsulation delivery system was developed using curcumin (CUR) and lutein (LUT) as model compounds to enhance dissolution and stability. Hydroxypropyl methylcellulose E5 (HPMC-E5) was identified as the optimal stabilizer for CUR and LUT nanosuspensions (NS) prepared by antisolvent precipitation and optimized by wet media milling. The resulting CUR-NS achieved a rapid dissolution of 93.29 ± 3.43% within 5 min compared with 26.71 ± 1.11% for raw CUR, while LUT-NS reached 85.13 ± 2.27% at 120 min versus 13.35 ± 1.32% for raw LUT. To enhance powder properties and stability, nanosuspensions were transformed into microcapsules via spray drying and bottom-spray fluidized bed coating, yielding drug loadings of 10–30%. The spray-dried CUR microcapsules exhibited poor flowability (angle of repose: 47°), which improved to 33° after surface modification with 3% colloidal silica. In contrast, CUR and LUT microcapsules prepared with sucrose-based cores via fluidized bed coating showed larger particle sizes, smoother surfaces, excellent flowability (angle of repose ~ 20°), and direct compression suitability. Accelerated stability tests revealed 1.3- to fourfold improvements in resistance to heat, light, and humidity compared with the raw pigments. Furthermore, compressibility evaluations confirmed good tableting performance for all microcapsules. Overall, this study demonstrates a robust nanosuspension–microencapsulation strategy that markedly enhances the dissolution, stability, and processing performance of poorly soluble natural pigments, highlighting its promise for industrial formulation and application.

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In pharmaceutical manufacturing, equipment is often used for multiple products following a single standard cleaning process regardless of the previously manufactured product. Despite this, residue levels are frequently non-detectable. Regulatory guidelines, such as the EMA Q&A on HBELs, mandate cleaning and visual inspection after each use, with analytical testing required after product changeovers unless otherwise justified. Consequently, cleaning validation (CV) data is typically left-censored, limited in sample size, and subject to multiple upper specification limits (USLs). These realities limit the applicability of traditional parametric capability indices and reduce the robustness of nonparametric methods. Moreover, they hinder the effective use of historical CV data in AI applications, which depend on large, standardized datasets for model training. To address these challenges, we propose a USL-normalization method that standardizes all residue measurements to a unified USL_Pct = 100. This transformation enables the aggregation of USL-heterogeneous datasets and supports robust nonparametric analysis. The cleaning process CQA (critical quality attribute) level upper capability index Ppu is calculated using the KDEDPonUSLND algorithm (kernel density estimation derived percentiles on USL-normalized data), which demonstrates improved robustness compared to traditional approaches. The cleaning process level Ppu is evaluated using either CQAWWC (CQA-wise worst case) or CQAWP (CQA-wise pooling) strategies, both integrated with the KDEDPonUSLND algorithm. The resulting CQAWWC_BAKEDPonUSLND and CQAWP_BAKEDPonUSLND models support an AI-driven CV Stage 3 Continued Cleaning Process Verification/Monitoring system, aligned with regulatory expectations.

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Although FDM is one of the prominent 3D printing technologies, and it has been widely investigated in pharmaceutical sciences, the printability of filaments remains a challenge. Therefore, our primary objective was to evaluate the effect of PEG 400, PEG 4000 and triethyl citrate at different concentrations (10%, 15% and 20% w/w) on the printability behavior of hydrocortisone-loaded Eudragit RS filaments. In this study, physical mixtures and their filaments were produced using a hot melt extruder and the properties of the filaments were examined by DSC, XRD, FESEM, FTIR, MFI and mechanical tests. Release behavior and hardness properties of the 3D-printed tablets were also evaluated. DSC and XRD results showed that the drug converted from crystalline to amorphous during hot melt extrusion and remained so during the 3D printing. FTIR results showed no chemical interactions between the drug and other excipients during hot melt extrusion and 3D printing. FESEM results of filaments showed that triethyl citrate-containing filaments had rougher surfaces, which makes them more suitable for 3D printing, while PEG-contained filaments had smoother surfaces. Mechanical tests showed that filaments containing triethyl citrate were stronger and tougher and had moderate ductility and stiffness. Overall, these filaments showed a good balance between these mechanical characteristics, which makes them a suitable candidate for 3D printing. Release studies showed that regardless of plasticizer type, the concentration of the plasticizer determines the extent of drug release. MFI test showed that formulations containing TEC presented a melt flow closer to 30 g/10 min compared to other formulations. Therefore, it can be deduced that TEC improves printability by enhancing melt flow better than the other two plasticizers (PEG 400 and PEG 4000). Based on the results, it can be concluded that triethyl citrate in 15% concentration is the best plasticizer for the production of hydrocortisone-loaded Eudragit RS tablets.

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High shear wet granulation (HSWG) is a conventional and widely used pharmaceutical drug product manufacturing process. Proper process control of the HSWG is crucial for ensuring the quality of granulation and, consequently, the final drug product. To demonstrate the adequacy of a proposed HSWG commercial process, the control of critical process parameters should be well established based on sufficient development data and scientific rationale. At the U.S. Food and Drug Administration (FDA), during the Chemistry, Manufacturing and Controls (CMC) assessment of original drug applications, deficiencies related to manufacturing process controls have been often found to be one of the causes of extended application review time or cycle numbers. In this paper, we have analyzed deficiencies from the manufacturing assessment of applications from 2017 to 2022 in which HSWG was used to produce oral solid dosage form drug products. The results revealed that the most frequently occurring deficiencies in the control of the HSWG process are related to lack of controls for granulation end point, granulation fluid level, granulation fluid addition rate, wet massing time, and process scale up strategy. This paper discusses the impact of these deficiencies on HSWG and final drug product quality along with recommendations for improvement of process controls.

Psoriasis is a chronic inflammatory skin condition characterized by the hyperproliferation of keratinocytes that results in erythematous and scaly plaques on the epidermal surface. Conventional therapeutic approaches exhibit drawbacks such as inadequate skin penetration, low drug bioavailability, and undesirable side effects. Nanoformulations emerge as a novel strategy to enhance drug delivery for treating psoriatic lesions with modified cyclodextrins (CDs), offering significant potential to improve their efficacy in the field of medicine. Cyclodextrins are well-known as versatile excipients that improve solubility, dissolution rate, chemical stability, and bioavailability through the formation of inclusion complexes. Furthermore, the chemical modifications of cyclodextrins such as sulfation, methylation, and hydroxypropylation have further enhanced their utility in topical formulations. Modified cyclodextrins enhance the delivery of anti-psoriatic agents such as TNF-α or IL-17 inhibitors and target key inflammatory pathways in psoriasis while reducing systemic exposure and minimizing side effects like immunosuppression, infections, and gastrointestinal disturbances. Additionally, modified cyclodextrins help to repair the epidermal barrier by increasing the efficacy of anti-inflammatory and keratinocyte-modulating medications. This article highlights the capabilities of modified cyclodextrins for revolutionizing the transformation of more effective and targeted therapies for psoriasis by identifying the limitations of current therapies and exploring the innovative applications of modified cyclodextrins in nanoformulations.

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The principal of generic product development is to match the critical quality attributes. Most of the time during complex product development, life cycle management; biowaiver, pre- and post-change approvals the significant efforts are made by scientist to match the drug release profile. In order to get the vivo bioequivalence testing waived based on in vitro performance of drug product; the dissolution testing is mostly act as a surrogate or performance indicator. Hence, assessment of similarity or equivalence of release profile is most critical aspect with respect to regulatory decision making. Available guideline defines the methodologies and acceptance criteria for same based on data structure e.g., application of mathematical and statistical model like similarity factor (F2), bootstrapped F2, model independent and model dependent approach etc. However, during regulatory review lot of discrepancies usually raise by regulators with respect to similarity demonstration like selection of proper methodology, define suitable acceptance criteria in case of high variability. Current article emphases on the visions behind regulatory expectations, with respect to dissolution profile comparison and highlights the prerequisites and answer the common question like how to choose the correct methodology, what are the limitations, way forward and regulatory expectations and alternative methodologies in order to evaluate the dissolution data statistically to make wise decision on in vitro equivalence. Overall, various approaches are available for dissolution similarity analysis. However, the intension of statistical comparability should be like; neither force the dissimilar product to pass the criteria, nor fail the product which are similar. This comprehensive review will enhance the overall understanding and help the formulation and biopharmaceutics scientists; how to ensure regulatory compliance during similarity evaluation.

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