Unveiling the influence of microaeration and sludge recirculation on enhancement of pharmaceutical removal and microbial community change of the novel anaerobic baffled biofilm - membrane bioreactor in treating building wastewater.

This research aims to conduct a comparative investigation of the role played by microaeration and sludge recirculation in the novel anaerobic baffled biofilm-membrane bioreactor (AnBB-MBR) for enhancing pharmaceutical removal from building wastewater. Three AnBB-MBRs - R1: AnBB-MBR, R2: AnBB-MBR with microaeration and R3: AnBB-MBR with microaeration and sludge recirculation - were operated simultaneously to remove Ciprofloxacin (CIP), Caffeine (CAF), Sulfamethoxazole (SMX) and Diclofenac (DCF) from real building wastewater at the hydraulic retention time (HRT) of 30 h for 115 days. From the removal profiles of the targeted pharmaceuticals in the AnBB-MBRs, it was found that the fixed-film compartment (C1) could significantly reduce the targeted pharmaceuticals. The remaining pharmaceuticals were further removed with the microaeration compartment. R2 exhibited the utmost removal efficiency for CIP (78.0 %) and DCF (40.8 %), while SMX was removed most successfully by R3 (microaeration with sludge recirculation) at 91.3 %, followed by microaeration in R2 (88.5 %). For CAF, it was easily removed by all AnBB-MBR systems (>90 %). The removal mechanisms indicate that the microaeration in R2 facilitated the adsorption of CIP onto microaerobic biomass, while the enhanced biodegradation of CAF, SMX and DCF was confirmed by batch biotransformation kinetics and the adsorption isotherms of the targeted pharmaceuticals. The microbial groups involved in biodegradation of the targeted compounds under microaeration were identified as nitrogen removal microbials (Nitrosomonas, Nitrospira, Thiobacillus, and Denitratisoma) and methanotrophs (Methylosarcina, Methylocaldum, and Methylocystis). Overall, explication of the integration of AnBB-MBR with microaeration (R2) confirmed it as a prospective technology for pharmaceutical removal from building wastewater due to its energy-efficient approach characterized by minimal aeration supply.

Parental exposure to antidepressants has lasting effects on offspring? A case study with zebrafish.

Fish have common neurotransmitter pathways with humans, exhibiting a significant degree of conservation and homology. Thus, exposure to fluoxetine makes fish potentially susceptible to biochemical and physiological changes, similarly to what is observed in humans. Over the years, several studies demonstrated the potential effects of fluoxetine on different fish species and at different levels of biological organization. However, the effects of parental exposure to unexposed offspring remain largely unknown. The consequences of 15-day parental exposure to relevant concentrations of fluoxetine (100 and 1000 ng/L) were assessed on offspring using zebrafish as a model organism. Parental exposure resulted in offspring early hatching, non-inflation of the swimming bladder, increased malformation frequency, decreased heart rate and blood flow, and reduced growth. Additionally, a significant behavioral impairment was also found (reduced startle response, basal locomotor activity, and altered non-associative learning during early stages and a negative geotaxis and scototaxis, reduced thigmotaxis, and anti-social behavior at later life stages). These behavior alterations are consistent with decreased anxiety, a significant increase in the expression of the monoaminergic genes slc6a4a (sert), slc6a3 (dat), slc18a2 (vmat2), mao, tph1a, and th2, and altered levels of monoaminergic neurotransmitters. Alterations in behavior, expression of monoaminergic genes, and neurotransmitter levels persisted until offspring adulthood. Given the high conservation of neuronal pathways between fish and humans, data show the possibility of potential transgenerational and multigenerational effects of pharmaceuticals' exposure. These results reinforce the need for transgenerational and multigenerational studies in fish, under realistic scenarios, to provide realistic insights into the impact of these pharmaceuticals.

From molecules to visuals: Empowering drug discovery and development with mass spectrometry imaging.

Over the past three decades, mass spectrometry imaging (MSI) has emerged as a valuable tool for the spatial localization of drugs and metabolites directly from tissue surfaces without the need for labels. MSI offers molecular specificity, making it increasingly popular in the pharmaceutical industry compared to conventional imaging techniques like quantitative whole-body autoradiography (QWBA) and immunohistochemistry, which are unable to distinguish parent drugs from metabolites. Across the industry, there has been a consistent uptake in the utilization of MSI to investigate drug and metabolite distribution patterns, and the integration of MSI with omics technologies in preclinical investigations. To continue the further adoption of MSI in drug discovery and development, we believe there are two key areas that need to be addressed. First, there is a need for accurate quantification of analytes from MSI distribution studies. Second, there is a need for increased interactions with regulatory agencies for guidance on the utility and incorporation of MSI techniques in regulatory filings. Ongoing efforts are being made to address these areas, and it is hoped that MSI will gain broader utilization within the industry, thereby becoming a critical ingredient in driving drug discovery and development.

Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods.

Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one of the key factors for the successful marketing of drug candidates. Therefore, predicting half-life is of great significance in drug design. In this study, we employed eXtreme Gradient Boosting (XGboost), randomForest (RF), gradient boosting machine (GBM), and supporting vector machine (SVM) to build quantitative structure-activity relationship (QSAR) models on 3512 compounds and evaluated model performance by using root-mean-square error (RMSE), R2, and mean absolute error (MAE) metrics and interpreted features by SHapley Additive exPlanation (SHAP). Furthermore, we developed consensus models through integrating four individual models and validated their performance using a Y-randomization test and applicability domain analysis. Finally, matched molecular pair analysis was used to extract the transformation rules. Our results revealed that XGboost outperformed other individual models (RMSE = 0.176, R2 = 0.845, MAE = 0.141). The consensus model integrating all four models continued to enhance prediction performance (RMSE = 0.172, R2 = 0.856, MAE = 0.138). We evaluated the reliability, robustness, and generalization ability via Y-randomization test and applicability domain analysis. Meanwhile, we utilized SHAP to interpret features and employed matched molecular pair analysis to extract chemical transformation rules that provide suggestions for optimizing drug structure. In conclusion, we believe that the consensus model developed in this study serve as a reliable tool to evaluate half-life in drug discovery, and the chemical transformation rules concluded in this study could provide valuable suggestions in drug discovery.

Pharmacokinetics Profiler (PhaKinPro): Model Development, Validation, and Implementation as a Web Tool for Triaging Compounds with Undesired Pharmacokinetics Profiles.

Computational models that predict pharmacokinetic properties are critical to deprioritize drug candidates that emerge as hits in high-throughput screening campaigns. We collected, curated, and integrated a database of compounds tested in 12 major end points comprising over 10,000 unique molecules. We then employed these data to build and validate binary quantitative structure-activity relationship (QSAR) models. All trained models achieved a correct classification rate above 0.60 and a positive predictive value above 0.50. To illustrate their utility in drug discovery, we used these models to predict the pharmacokinetic properties for drugs in the NCATS Inxight Drugs database. In addition, we employed the developed models to predict the pharmacokinetic properties of all compounds in the DrugBank. All models described in this paper have been integrated and made publicly available via the PhaKinPro Web-portal that can be accessed at https://phakinpro.mml.unc.edu/.

Sorting drug conformers in enzyme active sites: the XTB way.

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected. By examining different groups of systems within MEI196 that contain species of a similar nature, we find that chemical similarity leads to cancellation of errors in the calculation of relative binding energies. Importantly, the semi-empirical method GFN1-xTB (XTB1) yields reasonable results for this purpose. We have thus further assessed the performance of XTB1 for calculating relative energies of docking poses of substrates in enzyme active sites represented by cluster models or within the ONIOM protocol. The results support the observations on error cancellation. This paves the way for the use of XTB1 in parts of large-scale virtual screening workflows to accelerate the drug discovery process.

Biotransformation of fluorinated drugs and xenobiotics by the model fungus Cunninghamella elegans.

Some species of the genus Cunninghamella (C. elegans, C. echinulata and C. blaskesleeana) produce the same phase I and phase II metabolites when incubated with xenobiotics as mammals, and thus are considered microbial models of mammalian metabolism. This had made these fungi attractive for metabolism studies with drugs, pesticides and environmental pollutants. As a substantial proportion of pharmaceuticals and agrochemicals are fluorinated, their biotransformation has been studied in Cunninghamella fungi and C. elegans in particular. This article details the methods employed for cultivating the fungi in planktonic and biofilm cultures, and extraction and analysis of fluorinated metabolites. Furthermore, protocols for the heterologous expression of Cunninghamella cytochromes P450 (CYPs), which are the enzymes associated with phase I metabolism, are described.

Antarctic marine sediment as a source of filamentous fungi-derived antimicrobial and antitumor compounds of pharmaceutical interest.

Antarctica harbors a microbial diversity still poorly explored and of inestimable biotechnological value. Cold-adapted microorganisms can produce a diverse range of metabolites stable at low temperatures, making these compounds industrially interesting for biotechnological use. The present work investigated the biotechnological potential for antimicrobial and antitumor activity of filamentous fungi and bacteria isolated from marine sediment samples collected at Deception Island, Antarctica. A total of 89 microbial isolates were recovered from marine sediments and submitted to an initial screening for L-glutaminase with antitumoral activity and for antimicrobial metabolites. The isolates Pseudogymnoascus sp. FDG01, Pseudogymnoascus sp. FDG02, and Penicillium sp. FAD33 showed potential antiproliferative action against human pancreatic carcinoma cells while showing no toxic effect on non-tumor cells. The microbial extracts from unidentified three bacteria and four filamentous fungi showed antibacterial activity against at least one tested pathogenic bacterial strain. The isolate FDG01 inhibited four bacterial species, while the isolate FDG01 was active against Micrococcus luteus in the minimal inhibitory concentration of 0.015625 µg mL -1. The results pave the way for further optimization of enzyme production and characterization of enzymes and metabolites found and reaffirm Antarctic marine environments as a wealthy source of compounds potentially applicable in the healthcare and pharmaceutical industry.

Photo-crosslinkable polyester microneedles as sustained drug release systems toward hypertrophic scar treatment.

Burn injuries can result in a significant inflammatory response, often leading to hypertrophic scarring (HTS). Local drug therapies e.g. corticoid injections are advised to treat HTS, although they are invasive, operator-dependent, extremely painful and do not permit extended drug release. Polymer-based microneedle (MN) arrays can offer a viable alternative to standard care, while allowing for direct, painless dermal drug delivery with tailorable drug release profile. In the current study, we synthesized photo-crosslinkable, acrylate-endcapped urethane-based poly(ε-caprolactone) (AUP-PCL) toward the fabrication of MNs. Physico-chemical characterization (1H-NMR, evaluation of swelling, gel fraction) of the developed polymer was performed and confirmed successful acrylation of PCL-diol. Subsequently, AUP-PCL, and commercially available PCL-based microneedle arrays were fabricated for comparative evaluation of the constructs. Hydrocortisone was chosen as model drug. To enhance the drug release efficiency of the MNs, Brij®35, a nonionic surfactant was exploited. The thermal properties of the MNs were evaluated via differential scanning calorimetry. Compression testing of the arrays confirmed that the MNs stay intact upon applying a load of 7 N, which correlates to the standard dermal insertion force of MNs. The drug release profile of the arrays was evaluated, suggesting that the developed PCL arrays can offer efficient drug delivery for up to two days, while the AUP-PCL arrays can provide a release up to three weeks. Finally, the insertion of MN arrays into skin samples was performed, followed by histological analysis demonstrating the AUP-PCL MNs outperforming the PCL arrays upon providing pyramidical-shaped perforations through the epidermal layer of the skin.

AUP-PCL MN arrays provide long-term transdermal drug delivery of hydrocortisoneAUP-PCL-based MN arrays provide superior drug release profiles compared to PCL MNsEffective skin penetration AUP-PCL-based MNs on skin was achieved.

BMP2-ERK-ATF4 Axis-Based 6-methoxybenzofuran Compound I-9 Acts as Candidate Drug for Bone Formation and Anti-Osteoporosis.

As the global population ages, the number of patients with osteoporosis is rapidly rising. The existing first-line clinical drugs are bone resorption inhibitors that have difficulty restoring the bone mass of elderly patients to the safe range. The range and period of use of existing peptides and monoclonal antibodies are limited, and small-molecule bone formation-promoting drugs are urgently required. We established an I-9 synthesis route with high yield, simple operation, and low cost that was suitable for future large-scale production. I-9 administration promoted bone formation and increased bone mass in mice with low bone mass in an aged C57 mouse model. Our findings revealed a hitherto undescribed pathway involving the BMP2-ERK-ATF4 axis that promotes osteoblast differentiation; I-9 has favorable biosafety in mice. This study systematically investigated the efficacy, safety, and mechanism of I-9 for treating osteoporosis and positions this drug for preclinical research in the future. Thus, this study has promoted the development of small-molecule bone-promoting drugs.

Preclinical pharmacokinetic investigation of the bioavailability and skin distribution of HY-072808 ointment, a novel drug candidate for the treatment of atopic dermatitis, in minipigs by a newly LC-MS/MS method.

HY-072808 is a novel phosphodiesterase 4 inhibitor clinically used for topical atopic dermatitis treatment. Cytochrome P450 enzymes are involved in transforming it into major metabolite ZZ-24. An efficient UPLC-MS/MS method was established to detect HY-072808 and ZZ-24 in plasma and skin tissues of minipigs.One-step protein precipitation was performed with acetonitrile. Subsequently, elution was served with a methanol and water gradient containing 0.1% formic acid for 3.5 min. The plasma and skin tissue concentrations of HY-072808 and ZZ-24 showed good linearity from 0.200 to 200 ng/mL.The experimental minipigs exhibited low systemic exposure and bioavailability of 3.1-7.6% after transdermal application of 1-4% HY-072808 ointment. Multiple topical administrations over seven consecutive days showed a minor accumulation in systemic exposure, with accumulation factors of 2.3 and 4.0 for HY-072808 and ZZ-24, respectively.The distribution of HY-072808 ointment among different cortical layers in minipigs was studied for the first time. Following transdermal application of 2% HY-072808 ointment, the concentration in plasma and skin tissues in the order of epidermis > dermis > subcutaneous tissue ≈ subcutaneous muscle ≈ plasma; at 48 h after the administration, the epidermis and dermis still had a high concentration of the drug.

Parafilm® M and Strat-M® as skin simulants in in vitro permeation of dissolving microarray patches loaded with proteins.

In vitro permeation studies play a crucial role in early formulation optimisation before extensive animal model investigations. Biological membranes are typically used in these studies to mimic human skin conditions accurately. However, when focusing on protein and peptide transdermal delivery, utilising biological membranes can complicate analysis and quantification processes. This study aims to explore Parafilm®M and Strat-M® as alternatives to dermatomed porcine skin for evaluating protein delivery from dissolving microarray patch (MAP) platforms. Initially, various MAPs loaded with different model proteins (ovalbumin, bovine serum albumin and amniotic mesenchymal stem cell metabolite products) were prepared. These dissolving MAPs underwent evaluation for insertion properties and in vitro permeation profiles when combined with different membranes, dermatomed porcine skin, Parafilm®M, and Strat-M®. Insertion profiles indicated that both Parafilm®M and Strat-M® showed comparable insertion depths to dermatomed porcine skin (in range of 360-430 µm), suggesting promise as membrane substitutes for insertion studies. In in vitro permeation studies, synthetic membranes such as Parafilm®M and Strat-M® demonstrated the ability to bypass protein-derived skin interference, providing more reliable results compared to dermatomed neonatal porcine skin. Consequently, these findings present valuable tools for preliminary screening across various MAP formulations, especially in the transdermal delivery of proteins and peptides.

Intranasal Nose-to-Brain Drug Delivery via the Olfactory Region in Mice: Two In-Depth Protocols for Region-Specific Intranasal Application of Antibodies and for Expression Analysis of Fc Receptors via In Situ Hybridization in the Nasal Mucosa.

A region-specific catheter-based intranasal administration method was successfully developed, established, and validated as reported previously. By using this method, drugs can be applicated specifically to the olfactory region. Thereby, intranasally administered drugs could be delivered via neuronal connections to the central nervous system. Here, we present a detailed protocol with a step-by-step procedure for nose-to-brain delivery via the olfactory mucosa.Fc receptors such as the neonatal Fc receptor (FcRn) and potentially Fcγ receptor IIb (FcγRIIb) are involved in the uptake and transport of antibodies via the olfactory nasal mucosa. To better characterize their expression levels and their role in CNS drug delivery via the nose, an in situ hybridization (ISH) protocol was adapted for nasal mucosa samples and described in abundant details.

Enhancing Multi-species Liver Microsomal Stability Prediction through Artificial Intelligence.

Liver microsomal stability, a crucial aspect of metabolic stability, significantly impacts practical drug discovery. However, current models for predicting liver microsomal stability are based on limited molecular information from a single species. To address this limitation, we constructed the largest public database of compounds from three common species: human, rat, and mouse. Subsequently, we developed a series of classification models using both traditional descriptor-based and classic graph-based machine learning (ML) algorithms. Remarkably, the best-performing models for the three species achieved Matthews correlation coefficients (MCCs) of 0.616, 0.603, and 0.574, respectively, on the test set. Furthermore, through the construction of consensus models based on these individual models, we have demonstrated their superior predictive performance in comparison with the existing models of the same type. To explore the similarities and differences in the properties of liver microsomal stability among multispecies molecules, we conducted preliminary interpretative explorations using the Shapley additive explanations (SHAP) and atom heatmap approaches for the models and misclassified molecules. Additionally, we further investigated representative structural modifications and substructures that decrease the liver microsomal stability in different species using the matched molecule pair analysis (MMPA) method and substructure extraction techniques. The established prediction models, along with insightful interpretation information regarding liver microsomal stability, will significantly contribute to enhancing the efficiency of exploring practical drugs for development.

Uptake/depuration kinetics, bioaccumulation potential and metabolic transformation of a complex pharmaceutical mixture in zebrafish (Danio rerio).

Uptake and elimination kinetics, bioconcentration factors (BCFs), and metabolic transformation of 20 different pharmaceutically active compounds (PhACs), covering a wide range of therapeutic categories and physico-chemical properties, were studied using zebrafish (Danio rerio). The fish were exposed to the mixture of the selected PhACs at environmentally relevant concentrations similar to 10 µg L-1. The experiments were performed in semi-static conditions and comprised a 7-day uptake period followed by a 7-day depuration period. Most of the PhACs reached a concentration plateau within the 7-day uptake-phase which was followed by an efficient depuration, with the observed uptake (ku) and depuration rate constants (kd,) ranging between 0.002 and 3.752 L kg-1 h-1, and 0.010 to 0.217 h-1, respectively. The investigated PhACs showed low to moderate BCFs. The highest BCFs of 47.8, 28.6 and 47.6 L kg-1 were determined for sertraline, diazepam and desloratadine, respectively. A high contribution of metabolic products to the total internal concentration was observed for some PhACs such as codeine (69%), sulfamethoxazole (51%) and verapamil (87%), which has to be taken into account when assessing the bioconcentration potential. Moreover, most of the metabolites exhibited significantly longer half-lives in zebrafish than their parent compounds and affected the overall depuration kinetics.

Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine.

INTRODUCTION: Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hampers accurate prediction of drug candidates' pharmacokinetic properties. AREAS COVERED: The study highlights current developments in human pharmacokinetic prediction, talks about attempts to apply synthetic approaches for molecular design, and searches several databases, including Scopus, PubMed, Web of Science, and Google Scholar. The article stresses importance of rigorous analysis of machine learning model performance in assessing progress and explores molecular modeling (MM) techniques, descriptors, and mathematical approaches. Transitioning to clinical drug development, article highlights AI (Artificial Intelligence) based computer models optimizing trial design, patient selection, dosing strategies, and biomarker identification. In-silico models, including molecular interactomes and virtual patients, predict drug performance across diverse profiles, underlining the need to align model results with clinical studies for reliability. Specialized training for human specialists in navigating predictive models is deemed critical. Pharmacogenomics, integral to personalized medicine, utilizes predictive modeling to anticipate patient responses, contributing to more efficient healthcare system. Challenges in realizing potential of predictive modeling, including ethical considerations and data privacy concerns, are acknowledged. EXPERT OPINION: AI models are crucial in drug development, optimizing trials, patient selection, dosing, and biomarker identification and hold promise for streamlining clinical investigations.

Use of sawdust for production of ligninolytic enzymes by white-rot fungi and pharmaceutical removal.

Use of white-rot fungi for enzyme-based bioremediation of wastewater is of high interest. These fungi produce considerable amounts of extracellular ligninolytic enzymes during solid-state fermentation on lignocellulosic materials such as straw and sawdust. We used pure sawdust colonized by Pleurotus ostreatus, Trametes versicolor, and Ganoderma lucidum for extraction of ligninolytic enzymes in aqueous suspension. Crude enzyme suspensions of the three fungi, with laccase activity range 12-43 U/L and manganese peroxidase activity range 5-55 U/L, were evaluated for degradation of 11 selected pharmaceuticals spiked at environmentally relevant concentrations. Sulfamethoxazole was removed significantly in all treatments. The crude enzyme suspension from P. ostreatus achieved degradation of wider range of pharmaceuticals when the enzyme activity was increased. Brief homogenization of the colonized sawdust was also observed to be favorable, resulting in significant reductions after a short exposure of 5 min. The highest reduction was observed for sulfamethoxazole which was reduced by 84% compared to an autoclaved control without enzyme activity and for trimethoprim which was reduced by 60%. The compounds metoprolol, lidocaine, and venlafaxine were reduced by approximately 30% compared to the control. Overall, this study confirmed the potential of low-cost lignocellulosic material as a substrate for production of enzymes from white-rot fungi. However, monitoring over time in bioreactors revealed a rapid decrease in enzymatic ligninolytic activity.

Deciphering the core bacterial community structure and function and their response to environmental factors in activated sludge from pharmaceutical wastewater treatment plants.

Pharmaceutical wastewater is recognized for its heightened concentrations of organic pollutants, and biological treatment stands out as an effective technology to remove these organic pollution. Therefore, a comprehensive exploration of core bacterial community compositions, functions, and their responses to environmental factors in pharmaceutical wastewater treatment plants (PWWTPs) is important for understanding the removal mechanism of these organic pollutants. This study comprehensively investigated 36 activated sludge (AS) samples from 15 PWWTPs in China. The results revealed that Proteobacteria (45.41%) was the dominant phylum in AS samples, followed by Bacteroidetes (19.54%) and Chloroflexi (4.13%). While the dominant genera were similar in both aerobic and anaerobic treatment processes, their relative abundances exhibited significant variations. Genera like HA73, Kosmotoga, and Desulfovibrio were more abundant during anaerobic treatment, while Rhodoplanes, Bdellovibrio, and Hyphomicrobium dominated during aerobic treatment. 13 and 10 core operational taxonomic units (OTUs) were identified in aerobic and anaerobic sludge, respectively. Further analysis revealed that core OTUs belonging to genera Kosmotoga, Desulfovibrio, Thauera, Hyphomicrobium, and Chelativorans, were associated with key functions, including sulfur metabolism, methane metabolism, amino acid metabolism, carbohydrate metabolism, toluene degradation, and nitrogen metabolism. Furthermore, this study highlighted the crucial roles of environmental factors, such as COD, NH4+-N, SO42-, and TP, in shaping both the structure and core functions of bacterial communities within AS of PWWTPs. Notably, these factors indirectly affect functional attributes by modulating the bacterial community composition and structure in pharmaceutical wastewater. These findings provide valuable insights for optimizing the efficiency of biochemical treatment processes in PWWTPs.

Nanovesicular ultraflexible invasomes and invasomal gel for transdermal delivery of phytopharmaceuticals.

Tweetable abstract Invasomes and invasomal gel are ultraflexible, soft vesicular, phospholipid based nanocarriers with deeper skin penetration ability for transdermal applications of drugs and phytopharmaceuticals.

Intranasal drug delivery: The interaction between nanoparticles and the nose-to-brain pathway.

Intranasal delivery provides a direct and non-invasive method for drugs to reach the central nervous system. Nanoparticles play a crucial role as carriers in augmenting the efficacy of brain delivery. However, the interaction between nanoparticles and the nose-to-brain pathway and how the various biopharmaceutical factors affect brain delivery efficacy remains unclear. In this review, we comprehensively summarized the anatomical and physiological characteristics of the nose-to-brain pathway and the obstacles that hinder brain delivery. We then outlined the interaction between nanoparticles and this pathway and reviewed the biomedical applications of various nanoparticulate drug delivery systems for nose-to-brain drug delivery. This review aims at inspiring innovative approaches for enhancing the effectiveness of nose-to-brain drug delivery in the treatment of different brain disorders.