Search Results (303)

Substance-induced psychosis is a recognized clinical entity, commonly linked to cannabinoids, stimulants, hallucinogens, alcohol, and polysubstance use. These agents may provoke transient or persistent psychotic symptoms during intoxication or withdrawal. Opioids, however, constitute a noteworthy exception: psychosis is rarely observed during opioid intoxication, and emerging data suggest that opioid agonists might even exert antipsychotic-like effects. This article examines the paradoxical interaction between opioids and psychosis, with attention to clinical reports of psychotic symptoms arising following abrupt discontinuation of methadone or buprenorphine. In numerous cases, symptoms resolved swiftly after reintroduction of the opioid agonist, implying a neuromodulatory role. Opioids, unlike other substances of abuse, seem to lack intrinsic psychotogenic effects and may influence dopaminergic activity via kappa-opioid receptor antagonism and endorphinergic mechanisms. This challenges standard models of substance-induced psychosis and calls for a refined understanding of opioid pharmacodynamics in psychiatric contexts. In psychotic presentations among polysubstance users who also use opioids, restoring opioid agonist therapy should be prioritized, with antipsychotics reserved as second-line options—preferably agents with favorable receptor profiles. Where opioids are not involved, antipsychotics remain first-line, but should be applied judiciously, with efforts to taper when clinically appropriate. Full article

Caffeine is a widely consumed psychoactive compound known to influence drug metabolism and efficacy through interactions with key enzymes such as cytochrome P450 3A4 (CYP3A4). This study investigates the molecular impact of caffeine on the binding behavior of imatinib, a first-line BCR-ABL tyrosine kinase inhibitor, using molecular docking simulations. Structural optimization and lipophilicity analyses were conducted using HyperChem, while docking was performed with HEX software (Version 8.0.0) against the CYP3A4 receptor (PDB ID: 1W0E). Two administration scenarios were evaluated: concurrent caffeine–imatinib complex formation and sequential administration with caffeine pre-bound to CYP3A4. The caffeine–imatinib complex exhibited a predicted increase in lipophilicity (logP = 3.09) compared to imatinib alone (logP = −1.29), which may indicate the potential for enhanced membrane permeability and tissue distribution. Docking simulations revealed stronger binding affinity of the complex to CYP3A4 (−350.53 kcal/mol) compared to individual compounds, and improved imatinib binding when CYP3A4 was pre-complexed with caffeine (−294.14 kcal/mol vs. −288.19 kcal/mol). Frontier molecular orbital analysis indicated increased reactivity of the complex (ΔE = 7.74 eV), supporting the hypothesis of altered pharmacodynamic behavior. These findings suggest that caffeine may modulate imatinib’s metabolic profile and therapeutic efficacy by enhancing receptor binding and altering drug distribution. The study underscores the importance of evaluating dietary components during drug development and therapeutic planning, particularly for agents metabolized by CYP3A4. Full article

High-mobility group box 1 (HMGB1) is a nuclear protein that can interact with a transmembrane cell surface receptor for advanced glycation end products (RAGEs) and mediates the inflammatory pathways that lead to various pathological conditions like cancer, diabetes, cardiovascular diseases, and neurodegenerative disorders. Blocking the HMGB1/RAGE axis using various small synthetic or natural molecules has been proven to be an effective therapeutic approach to treating these inflammatory conditions. However, the low water solubility of these pharmacoactive molecules limits their clinical use. Pharmaceutically active molecules with low solubility and bioavailability in vivo convey a higher risk of failure for drug development and drug innovation. The pharmacokinetic and pharmacodynamics parameters of these compounds are majorly affected by their solubility. Enhancement of the bioavailability and solubility of drugs is a significant challenge in the area of pharmaceutical formulations. This review mainly describes various technologies utilized to improve the bioavailability of synthetic or natural molecules which have been particularly used in various inflammatory conditions acting specifically through the HMGB1/RAGE pathway. Full article

Background: Sodium–glucose cotransporter 2 (SGLT2) inhibitors have transformed type 2 diabetes mellitus (T2DM) management by promoting glucosuria, lowering glycated hemoglobin (HbA1c), blood pressure, and weight; however, their use is limited by genitourinary infections and ketoacidosis. Phytocannabinoids—bioactive compounds from Cannabis sativa—exhibit multi-target pharmacology, including interactions with cannabinoid receptors, Peroxisome Proliferator-Activated Receptors (PPARs), Transient Receptor Potential (TRP) channels, and potentially SGLT2. Objective: To evaluate the potential of phytocannabinoids as novel modulators of renal glucose reabsorption via SGLT2 and to compare their efficacy, safety, and pharmacological profiles with synthetic SGLT2 inhibitors. Methods: We performed a narrative review encompassing the following: (1) the molecular and physiological roles of SGLT2; (2) chemical classification, natural sources, and pharmacokinetics/pharmacodynamics of major phytocannabinoids (Δ⁹-Tetrahydrocannabinol or Δ⁹-THC, Cannabidiol or CBD, Cannabigerol or CBG, Cannabichromene or CBC, Tetrahydrocannabivarin or THCV, and β-caryophyllene); (3) in silico docking and drug-likeness assessments; (4) in vitro assays of receptor binding, TRP channel modulation, and glucose transport; (5) in vivo rodent models evaluating glycemic control, weight change, and organ protection; (6) pilot clinical studies of THCV and case reports of CBD/BCP; (7) comparative analysis with established synthetic inhibitors. Results: In silico studies identify high-affinity binding of several phytocannabinoids within the SGLT2 substrate pocket. In vitro, CBG and THCV modulate SGLT2-related pathways indirectly via TRP channels and CB receptors; direct IC₅₀ values for SGLT2 remain to be determined. In vivo, THCV and CBD demonstrate glucose-lowering, insulin-sensitizing, weight-reducing, anti-inflammatory, and organ-protective effects. Pilot clinical data (n = 62) show that THCV decreases fasting glucose, enhances β-cell function, and lacks psychoactive side effects. Compared to synthetic inhibitors, phytocannabinoids offer pleiotropic benefits but face challenges of low oral bioavailability, polypharmacology, inter-individual variability, and limited large-scale trials. Discussion: While preclinical and early clinical data highlight phytocannabinoids’ potential in SGLT2 modulation and broader metabolic improvement, their translation is impeded by significant challenges. These include low oral bioavailability, inconsistent pharmacokinetic profiles, and the absence of standardized formulations, necessitating advanced delivery system development. Furthermore, the inherent polypharmacology of these compounds, while beneficial, demands comprehensive safety assessments for potential off-target effects and drug interactions. The scarcity of large-scale, well-controlled clinical trials and the need for clear regulatory frameworks remain critical hurdles. Addressing these aspects is paramount to fully realize the therapeutic utility of phytocannabinoids as a comprehensive approach to T2DM management. Conclusion: Phytocannabinoids represent promising multi-target agents for T2DM through potential SGLT2 modulation and complementary metabolic effects. Future work should focus on pharmacokinetic optimization, precise quantification of SGLT2 inhibition, and robust clinical trials to establish efficacy and safety profiles relative to synthetic inhibitors. Full article

The global impact of the COVID-19 crisis has underscored the need for novel therapeutic candidates capable of efficiently targeting essential viral proteins. Existing therapeutic strategies continue to encounter limitations such as reduced efficacy against emerging variants, safety concerns, and suboptimal pharmacodynamics, which emphasize the potential of natural-origin compounds as supportive agents with immunomodulatory, anti-inflammatory, and antioxidant benefits. The present study significantly advances prior molecular docking research through comprehensive virtual screening of structurally related analogs derived from antiviral phytochemicals. These compounds were evaluated specifically against the SARS-CoV-2 main protease (3CLpro) and papain-like protease (PLpro). Utilizing chemical similarity algorithms via the ChEMBL database, over 600 candidate molecules were retrieved and subjected to automated docking, interaction pattern analysis, and comprehensive ADMET profiling. Several analogs showed enhanced binding scores relative to their parent scaffolds, with CHEMBL1720210 (a shogaol-derived analog) demonstrating strong interaction with PLpro (−9.34 kcal/mol), and CHEMBL1495225 (a 6-gingerol derivative) showing high affinity for 3CLpro (−8.04 kcal/mol). Molecular interaction analysis revealed that CHEMBL1720210 forms hydrogen bonds with key PLpro residues including GLY163, LEU162, GLN269, TYR265, and TYR273, complemented by hydrophobic interactions with TYR268 and PRO248. CHEMBL1495225 establishes multiple hydrogen bonds with the 3CLpro residues ASP197, ARG131, TYR239, LEU272, and GLY195, along with hydrophobic contacts with LEU287. Gene expression predictions via DIGEP-Pred indicated that the top-ranked compounds could influence biological pathways linked to inflammation and oxidative stress, processes implicated in COVID-19’s pathology. Notably, CHEMBL4069090 emerged as a lead compound with favorable drug-likeness and predicted binding to PLpro. Overall, the applied in silico framework facilitated the rational prioritization of bioactive analogs with promising pharmacological profiles, supporting their advancement toward experimental validation and therapeutic exploration against SARS-CoV-2. Full article

Background: Sirolimus (SRL, rapamycin) is a clinically important mTOR inhibitor used in immunosuppression, oncology, and cardiovascular drug-eluting devices. Despite its long-standing FDA approval, the human metabolic profile of SRL remains incompletely characterized. SRL is primarily metabolized by CYP3A enzymes in the liver and intestine, but the diversity, pharmacokinetics, and biological activity of its metabolites have been poorly explored due to the lack of structurally identified standards. Methods: To investigate SRL metabolism, we incubated SRL with pooled human liver microsomes (HLM) and isolated the resulting metabolites. Structural characterization was performed using high-resolution mass spectrometry (HRMS) and ion trap MSⁿ. We also applied Density Functional Theory (DFT) calculations to assess the energetic favorability of metabolic transformations and conducted molecular dynamics (MD) simulations to model metabolite interactions within the CYP3A4 active site. Results: We identified 21 unique SRL metabolites, classified into five major structural groups: O-demethylated, hydroxylated, didemethylated, di-hydroxylated, and mixed hydroxylated/demethylated derivatives. DFT analyses indicated that certain demethylation and hydroxylation reactions were energetically preferred, correlating with metabolite abundance. MD simulations further validated these findings by demonstrating the favorable orientation and accessibility of key sites within the CYP3A4 binding pocket. Conclusions: This study provides a comprehensive structural map of SRL metabolism, offering mechanistic insights into the formation of its metabolites. Our integrated approach of experimental and computational analyses lays the groundwork for future investigations into the pharmacodynamic and toxicodynamic effects of SRL metabolites on the mTOR pathway. Full article

Lycopene exhibits a broad spectrum of biological activities with potential therapeutic applications. Despite its established antioxidant and anti-inflammatory properties, the molecular basis for its pharmacological actions remains incompletely defined. Here we investigated the molecular targets, pharmacodynamic feasibility, and tissue-specific expression of lycopene targets using a computational pharmacology approach combined with affinity and protein–protein interaction (PPI) analyses. Lycopene-associated human protein targets were predicted using a Swiss target screening platform. Molecular docking was used to estimate binding affinities, and concentration-affinity (CA) ratios were calculated based on physiologically relevant plasma concentrations (75–210 nM). PPI networks of lycopene targets were constructed to identify highly connected targets, and tissue expression analysis was assessed for high-affinity targets using protein-level data from the Human Protein Atlas database. Of the 94 predicted targets, 37% were nuclear receptors and 18% were Family A G Protein Coupled Receptors (GPCRs). Among the top 15 high-affinity targets, nuclear receptors and GPCRs comprised 40% and 26.7%, respectively. Twenty targets had affinities < 10 μM, with six key targets (MAP2K2, SCN2A, SLC6A5, SCN3A, TOP2A, and TRIM24) showing submicromolar binding. CA ratio analysis identified MAP2K2, SCN2A, and SLC6A5 as pharmacodynamically feasible targets (CA > 1). PPI analysis revealed 32 targets with high interaction and 9 with significant network connectivity. Seven targets (TRIM24, GRIN1, NTRK1, FGFR1, NTRK3, CHRNB4, and PIK3CD) showed both high affinity and centrality in the interaction network. The expression profiling of submicromolar targets revealed widespread tissue distribution for MAP2K2 and SCN3A, while SCN2A, TOP2A, and TRIM24 showed more restricted expression patterns. This integrative analysis identifies a subset of lycopene targets with both high affinity and pharmacological feasibility, particularly MAP2K2, SCN2A, and TRIM24. Lycopene appears to exert its biological effects through modulation of interconnected signalling networks involving nuclear receptors, GPCRs, and ion channels. These findings support the potential of lycopene as a multi-target therapeutic agent and provide a rationale for future experimental and clinical validation. Full article

Background: “CFTR modulators” (also named “caftor”) have been developed and introduced into clinical practice to improve the functionality of defective CFTR protein. Therapeutic drug monitoring (TDM) is not currently used for CFTR modulators in routine clinical practice and there is still much to learn about the pharmacokinetic/pharmacodynamic (PK/PD) and the safety profiles of these drugs in a real-world setting. Moreover, therapeutic ranges are not yet available for both pediatric and adult cystic fibrosis (CF) patients. Methods: A new and sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) method for contemporary quantification of ivacaftor (IVA), tezacaftor (TEZ) and elexacaftor (ELX) in plasma samples has been developed and validated. The clinical performance of our method has been tested on samples collected during the routine clinical practice from n = 25 pediatric patients (aged between 7 and 17 years) affected by cystic fibrosis. This LC-MS/MS method has been validated according to ICH (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use) guidelines for the validation of bioanalytical methods. Results: Our method fulfilled ICH guidelines in terms of accuracy, precision, selectivity, specificity and carry-over. Intra- and inter-day accuracy and precision were ≤15%. The 9-day autosampler stability was 90–100% for TEZ and ELX; meanwhile, it fell to 76% for IVA. An injection volume of 1 µL and a wider quantification range (0.1–20 µg/mL) represent a novelty of our method in terms of sensitivity and fields of application. Finally, the evaluation of PK exposure parameters for IVA revealed strong agreement with previously published reports and with results from the summary of product characteristics (SmPCs). Conclusions: This method could be adopted to contemporarily measure ELX/TEZ/IVA plasma levels for both PK studies and monitor therapy compliance, especially in case of poor or partial responses to treatment, or to evaluate drug–drug interactions when multiple concomitant medications are required. Considering also the high cost burden of these medications to the health system, a TDM-based approach could facilitate more cost-effective patient management. Full article

The SARS-CoV-2 main protease (Mpro) is a validated therapeutic target for inhibiting viral replication. Few compounds have advanced clinically, underscoring the difficulty in optimizing both target affinity and drug-like properties. To address this challenge, we integrated machine learning (ML), molecular docking, and molecular dynamics (MD) simulations to investigate the balance between pharmacodynamic (PD) and pharmacokinetic (PK) properties in Mpro inhibitor design. We developed ML models to classify Mpro inhibitors based on experimental IC₅₀ data, combining molecular descriptors with structural insights from MD simulations. Our Support Vector Machine (SVM) model achieved strong performance (training accuracy = 0.84, ROC AUC = 0.91; test accuracy = 0.79, ROC AUC = 0.86), while our Logistic Regression model (training accuracy = 0.78, ROC AUC = 0.85; test accuracy = 0.76, ROC AUC = 0.83). Notably, PK descriptors often exhibited opposing trends to binding affinity: hydrophilic features enhanced binding affinity but compromised PK properties, whereas hydrogen bonding, hydrophobic, and π–π interactions in Mpro subsites S2 and S3/S4 are fundamental for binding affinity. Our findings highlight the need for a balanced approach in Mpro inhibitor design, strategically targeting these subsites may balance PD and PK properties. For the first time, we demonstrate antagonistic trends between pharmacokinetic (PK) and pharmacodynamic (PD) features through the integrated application of ML/MD. This study provides a computational framework for rational Mpro inhibitors, combining ML and MD to investigate the complex interplay between enzyme inhibition and drug likeness. These insights may guide the hit-to-lead optimization of the novel next-generation Mpro inhibitors of SARS-CoV-2 with preclinical and clinical potential. Full article

Propolis is a natural resinous substance produced by honeybees that has many biological activities. For thousands of years, it has been widely used as a dietary supplement and traditional medicine to treat a variety of ailments due to its antimicrobial, anti-inflammatory, antioxidant, immunomodulatory, and wound-healing properties. Nutritional supplements and foods may interact with drugs both pharmacodynamically and pharmacokinetically, which could raise clinical concerns. Background/Objectives: This study aimed to investigate the effect of propolis on the plasma disposition of enrofloxacin and to assess the potential pharmacokinetic interaction in rabbits. Methods: In this study, enrofloxacin was applied per os (20 mg/kg) and IM (10 mg/kg) and with propolis (100 mg resin/kg) administration in four groups of rabbits (each of six individuals). Heparinized blood samples were collected at 0, 0.1, 0.3, 0.5, 1, 2, 4, 8, 12, and 24 h post-administration. HPLC-FL was used to analyze the plasma concentrations of enrofloxacin and its active metabolite ciprofloxacin following liquid–liquid phase extraction, i.e., protein precipitation with acetonitrile and partitioning with sodium sulfate. Results: The results revealed that propolis coadministration significantly affected the plasma disposition of enrofloxacin and its active metabolite after both per os and intramuscular administration routes. Significantly greater AUC (48.91 ± 11.53 vs. 26.11 ± 12.44 µg.h/mL), as well as longer T_1/2λz (11.75 ± 3.20 vs. 5.93 ± 2.51 h) and MRT (17.26 ± 4.55 vs. 8.96 ± 3.82 h) values of enrofloxacin and its metabolite ciprofloxacin, were observed after the coadministration of propolis compared to enrofloxacin alone following both per os and IM routes in rabbits. Conclusions: The concurrent use of propolis and prescription medications may prolong the half-life (T_1/2λz) and increase the systemic availability of chronically used drugs with narrow therapeutic indices. The repeated use of drugs such as antibiotics, heart medications, and antidepressants, or drugs with a narrow therapeutic index such as antineoplastic and anticoagulant agents, can cause toxic effects by raising blood plasma levels. Considering the varied metabolism of rabbits and humans, further validation of this study may require thorough clinical trials in humans. Full article

This study explores the viral dynamics of SARS-CoV-2 infection within host cells by incorporating the pharmacological effects of andrographolide—a bioactive compound extracted from Andrographis paniculata, renowned for its antiviral, anti-inflammatory, and immunomodulatory properties. Through the application of mathematical modeling, the interactions among the virus, host cells, and immune responses are simulated to provide a comprehensive analysis of viral behavior over time. Two distinct models were employed to assess the impact of varying andrographolide dosages on viral load, target cell populations, and immune responses. One model revealed a clear dose–response relationship, whereas the other indicated that additional biological or pharmacological factors may modulate drug efficacy. Both models demonstrated stability, with basic reproductive numbers (R₀) suggesting the potential for viral propagation in the absence of effective therapeutic interventions. This study emphasizes the significance of understanding the pharmacokinetics (PK) and pharmacodynamics (PD) of andrographolide to optimize its therapeutic potential. The findings also underscore the necessity for further investigation into the compound’s absorption, distribution, metabolism, and excretion (ADME) characteristics, as well as its prospective applications in the treatment of not only COVID-19 but also other viral infections. Overall, the results lay a foundational framework for future experimental research and clinical trials aimed at refining andrographolide dosing regimens and improving patient outcomes. Full article

Emerging evidence highlights the gut microbiota as a pivotal determinant of pharmacological efficacy. While Enterococcus faecalis (E. faecalis)-derived tyrosine decarboxylases (tyrDCs) are known to decarboxylate levodopa (L-dopa), compromising systemic bioavailability, the causal mechanisms underlying microbiota-mediated pharmacodynamic variability remain unresolved. In our study, we employed antibiotic-induced microbiota depletion and fecal microbiota transplantation (FMT) to interrogate microbiota-L-dopa interactions in MPTP-induced Parkinson’s disease (PD) mice. The study demonstrated that antibiotic-mediated microbiota depletion enhances L-dopa bioavailability and striatal dopamine (DA) level, correlating with improved motor function. To dissect clinical heterogeneity in the L-dopa response, PD patients were stratified into moderate responders and good responders following standardized L-dopa challenges. In vitro bioconversion assays revealed greater L-dopa-to-DA conversion in fecal samples from moderate responders versus good responders. FMT experiments confirmed mice receiving good-responder microbiota exhibited enhanced L-dopa bioavailability, higher striatal DA concentrations, and a heightened therapeutic effect of L-dopa relative to moderate-responder recipients. Collectively, our study provided evidence that the gut microbiota directly modulates L-dopa metabolism and microbial composition determines interindividual therapeutic heterogeneity. Targeted microbial modulation—through precision antibiotics or donor-matched FMT—is a viable strategy to optimize PD pharmacotherapy, supporting the potential for microbiota-targeted adjuvant therapies in PD management. Full article

Background/Objectives:Bougainvillea x buttiana is used in traditional Mexican medicine to treat various diseases. Previous studies have demonstrated its anti-inflammatory properties, which are associated with its chemical composition. This study evaluated the effect of ethanol concentration on the yield and anti-inflammatory activity of its extracts. Additionally, an in silico analysis of the plant’s previously identified phytochemicals was conducted. Methods: Four extracts of B. x buttiana (var. Rose) (labeled as BxbREE) were prepared with increasing concentrations of ethanol (0%, 50%, 80%, and 100%). Their anti-inflammatory activity was assessed using different in vitro assays. The in silico prediction, performed with SwissADME, included the physicochemical, pharmacokinetic, and drug-like properties of the compounds. Results: The findings indicated that varying the ethanol concentration in the preparations of BxbREE-0%, BxbREE-50%, BxbREE-80%, and BxbREE-100% significantly impacted the extraction yield, with BxbREE-0% and BxbREE-50% exhibiting the highest recovery. All four extracts demonstrated significant anti-inflammatory activity, with BxbREE-50% and BxbREE-80% showing the most important effects on the denaturation of bovine serum albumin (BSA) and trypsin, inhibition of pro-inflammatory enzymes (cyclooxygenase and phospholipase A2), and increased stability of the erythrocyte membrane. The in silico analysis revealed that most phytochemicals identified in the extracts had good drug-likeness and bioavailability for oral administration and an adequate ADME profile. Conclusions: These findings reaffirm the anti-inflammatory potential of B. x buttiana (var. Rose) ethanolic extracts and the favorable pharmacokinetic and pharmacodynamic properties of its phytochemicals. Further structural exploration of the interactions of these bioactive compounds could contribute to the design of new drugs. Full article

To investigate the therapeutic impact of Forsythia suspensa extract (FS) on RSV-infected mice and explore its antiviral pharmacodynamic foundations. Methods: An integrated analytical approach, combining UPLC-Q-TOF/MS with network pharmacology, was employed to analyze and identify the chemical constituents in FS, particularly those exhibiting antiviral properties against RSV. The study integrated network pharmacology and metabolomics for further analysis, and molecular docking and interaction experiments were conducted to validate the pharmacodynamic mechanisms. Finally, an RSV pneumonia mouse model was employed to evaluate the therapeutic influence of FS, including pathological and immunohistochemistry assessments. Twenty-five components in FS were identified through UPLC-Q-TOF/MS analysis. Integrated network pharmacology data revealed 43 effective components and predicted 113 potential targets of FS for anti-RSV activity. Metabolomics analysis identified 14 metabolite biomarkers closely linked to RSV-induced metabolic disruptions involving pathways. Moreover, molecular docking and Biacore experiments provided additional confirmation that FS primarily exerts its effects through compounds such as rutin, quercetin, and kaempferol. Immunohistochemistry experiments demonstrated a significant reduction in the expression of relevant proteins following FS administration, affirming its capacity to ameliorate lung inflammation induced by RSV infection through the modulation of Toll-like receptor signaling pathways. The data presented in this study illustrate that FS exerts its anti-RSV effects by regulating the Toll-like receptor signaling pathway and the arachidonic acid metabolism pathway via rutin, quercetin, and kaempferol. Furthermore, the approach of combining network pharmacology with metabolomics proves to be an effective research strategy for investigating the bioactive constituents of medicinal plants and elucidating their pharmacological effects. Full article

Background/Objectives: The Self-Nanoemulsifying Drug Delivery System (SNEDDS) has been widely applied in oral drug delivery, particularly for poorly water-soluble compounds. The successful development of SNEDDS largely depends on the precise composition of its components. This narrative review provides an in-depth analysis of Quality by Design (QbD), Design of Experiment (DoE), and in silico approach applications in SNEDDS development. Methods: The review is based on publications from 2020 to 2025, sourced from reputable scientific databases (Pubmed, Science direct, Taylor and francis, and Scopus). Results: Quality by Design (QbD) is a systematic and scientific approach that enhances product quality while ensuring the robustness and reproducibility of SNEDDS, as outlined in the Quality Target Product Profile (QTPP). DoE was integrated into the QbD framework to systematically evaluate the effects of predefined factors, particularly Critical Material Attributes (CMAs) and Critical Process Parameters (CPP_S), on the desired responses (Critical Quality Attributes/CQA), ultimately leading to the identification of the optimal SNEDDS formulation. Various DoEs, including the mixture design, response surface methodology, and factorial design, have been widely applied to SNEDDS formulations. The experimental design facilitates the analysis of the relationship between CQA and CMA/CPP, enabling the identification of optimized formulations with enhanced biopharmaceutical, pharmacokinetic, and pharmacodynamic profiles. As an essential addition to this review, in silico approach emerges as a valuable tool in the development of SNEDDS, offering deep insights into self-assembly dynamics, molecular interactions, and emulsification behaviour. By integrating molecular simulations with machine learning, this approach enables rational and efficient optimization. Conclusions: The integration of QbD, DoE, and in silico approaches holds significant potential in the development of SNEDDS. These strategies enable a more efficient, rational, and predictive formulation process. Full article