Search Results (421)

Introduction/aim: N-acetylgalactoseamine-conjugated small interfering RNAs (GalNAc-siRNAs) are an emerging class of drugs possessing an extensive clinical potential because of their high target specificity to the asialoglycoprotein receptor (ASGPR) in hepatocytes. Overall, GalNAc-sRNAs are well-tolerated across species but differences in pharmacokinetic (PK) and pharmacodynamic (PD) properties have been observed. Furthermore, despite GalNAc-siRNA’s high liver specificity, distribution into off-target organs does occur. Through whole-body physiologically based pharmacokinetic (PBPK) modeling, this study seeks to mechanistically address species differences, establish clinical PK-PD relationships, and characterize off-target organ accumulation, ultimately expediting the preclinical-to-clinical translation of GalNAc-sRNAs in drug development. Materials/Methods: For model development, validation, and establishment of species’ translations, three in-house GalNAc-siRNAs with PK data from different biospecimens, as well as downstream effects on mRNA and target proteins in mouse, monkey, and human, were leveraged. A WB-PBPK-PD legacy model, developed as an extension to the generic model for large molecules in the platform Open Systems Pharmacology Suite, was further validated and applied to address the specific aims of this study. Results: The model successfully quantified the PK-PD relationships across species and characterized accumulation in off-target organs. The model further sheds light on species-specific differences, such as liver permeability, subcutaneous absorption rate, as well as PD-related mechanisms. Moreover, the model confirmed previously established compound-specific pharmacokinetic differences and similarities. Conclusions: This PBPK-PD can serve as a framework for future investigations of novel GalNAc-siRNAs across species. Full article

Pharmacotherapy in the geriatric population is one of the greatest challenges in modern medicine. Elderly patients, characterized by multimorbidity and the resulting polypharmacy, are significantly more exposed to adverse drug reactions (ADRs), which often lead to hospitalization and a decline in quality of life. Understanding the reasons for this difference requires an analysis of the physiological changes that occur during the aging process at the molecular level. This article presents a perspective on the molecular aspects of geriatric pharmacotherapy, focusing on the fundamental mechanisms that are modified with age. The analysis covers changes in pharmacokinetics, including the role and regulation of cytochrome P450 (CYP) enzymes, whose activity, especially in phase I reactions, is significantly reduced. The age-dependent dysfunction of drug transporters from the ABC (ATP-binding cassette) and SLC (solute carrier) families in key organs such as the intestines, liver and kidneys is discussed, which affects the absorption, distribution and elimination of xenobiotic compounds, including drugs. The article also provides a comprehensive analysis of the blood–brain barrier (BBB), describing changes in neurovascular integrity, including the dysfunction of tight junctions and a decrease in the activity of P-glycoprotein, sometimes referred to as multidrug resistance protein (MDR). This increases the susceptibility of the central nervous system to the penetration and action of drugs. In the realm of pharmacodynamics, changes in the density and sensitivity of key receptors (serotonergic, dopaminergic, adrenergic) are described based on neuroimaging data, explaining the molecular basis for increased sensitivity to certain drug classes, such as anticholinergics. The paper also explores new research perspectives, such as the role of the gut microbiome in modulating pharmacokinetics by influencing gene expression and the importance of pharmacoepigenetics, which dynamically regulates drug response throughout life via changes in DNA methylation and histone modifications. The clinical implications of these molecular changes are also discussed, emphasizing the potential of personalized medicine, including pharmacogenomics, in optimizing therapy and minimizing the risk of adverse reactions. Such an integrated approach, incorporating data from multiple fields (genomics, epigenomics, microbiomics) combined with a comprehensive geriatric assessment, appears to be the future of safe and effective pharmacotherapy in the aging population. Full article

Background/Objectives: Adapalene is a synthetic retinoid used as a treatment for acne vulgaris. In this study, we attempted to evaluate the dermal pharmacokinetics of adapalene utilizing experimental and in silico tools. Methods: We utilized three over the counter (OTC) adapalene gels to evaluate local dermal pharmacokinetics. A data-driven, robust, mechanistic dermal physiologically based pharmacokinetic (PBPK) model was developed by integrating the physicochemical properties of adapalene, the formulation attributes of the gels, and the biophysical aspects of dermal absorption. The dermal PBPK model was validated against experimental data using in vitro release studies and in vitro permeation studies with human cadaver skin. A clinical study was performed to evaluate the effects of adapalene from the three gel formulations. The impact of adapalene delivery from three gels on the stratum corneum (SC) thickness, pilosebaceous unit area, keratinocyte number, and epidermal thickness was captured using a non-invasive technique, line-field confocal optical coherence tomography (LC–OCT). These responses were evaluated using an Emax model. Results: The dermal PBPK model has successfully predicted adapalene penetration profiles across different gel formulations. The model accuracy, in predicting drug release and permeation characteristics, was confirmed using the experimental data. Clinical evaluation revealed formulation-dependent differences in adapalene’s effects on measured skin parameters, with distinct pharmacodynamic profiles observed for each gel formulation. Conclusions: The overall study gave us a detailed insight into potential effects of formulation on the dermal pharmacokinetics and pharmacodynamics of adapalene using three marketed gels. Full article

Background/Objectives: Diabetes mellitus (DM) is an increasingly prevalent endocrine disorder affecting humans and companion animals. Type 1 DM (T1DM) and type 2 DM (T2DM) are well characterized in humans, and canine DM most often resembles T1DM, marked by insulin dependence and β-cell destruction. Conversely, feline DM shares key features with human T2DM, including insulin resistance, obesity-related inflammation, and islet amyloidosis. This review provides a comprehensive comparative analysis of antidiabetic therapies in humans, dogs, and cats, focusing on three core areas: disease pathophysiology, pharmacological and delivery strategies, and translational implications. In human medicine, a wide array of insulin analogs, oral hypoglycemic agents, and incretin-based therapies, including glucagon-like peptide-1 receptor agonists (liraglutide) and sodium-glucose cotransporter-2 inhibitors (empagliflozin), are available. Veterinary treatments remain limited to species-adapted insulin formulations and off-label use of human drugs. Interspecies differences in gastrointestinal physiology, drug metabolism, and behavioral compliance influence therapeutic efficacy and pharmacokinetics. Recent innovations, such as microneedle patches for insulin delivery and continuous glucose monitoring systems, show promise in humans and animals. Companion animals with naturally occurring diabetes serve as valuable models for preclinical testing of novel delivery platforms and long-acting formulations under real-world settings. While these technologies show potential, challenges remain in regulatory approval and behavioral adaptation in animals. Conclusions: Future research should prioritize pharmacokinetic bridging studies, veterinary-specific formulation trials, and device validation in animal models. By highlighting shared and species-specific characteristics of DM pathogenesis and treatment, this review advocates a One Health approach toward optimized antidiabetic therapies that benefit human and veterinary medicine. Full article

Background: Accurate assessment of CYP2C induction-mediated drug–drug interactions (DDIs) remains a challenge, despite the importance of CYP2C enzymes in drug metabolism. Limitations in available models and scarce clinical induction data have hampered quantitative preclinical DDI risk evaluation. Methods: In this study, the authors utilized an all-human hepatocyte triculture system to capture CYP2C induction using the perpetrators rifampicin, efavirenz, carbamazepine, and apalutamide. In vitro induction parameters were quantified by measuring changes in both mRNA and enzyme activities for CYP2C8, CYP2C9, and CYP2C19. These induction parameters, along with CYP-specific intrinsic clearance (CL_int) for the victim compounds, were incorporated into a physiologically based pharmacokinetic (PBPK) model, and pharmacokinetics (PK) of known CYP2C substrates were predicted with and without co-administration of perpetrator compounds using clinical dosing regimens. The results were quantitatively compared with the currently utilized mechanistic static modeling (MSM) approach and the reported clinical DDI outcomes. Results: By incorporating the measured f_m of CYP2C substrates into PBPK modeling, we observed a lower propensity to over- or underpredict the exposure of these substrates as victims of CYP2C induction-based DDIs when co-administered with known perpetrators, which resulted in an excellent correlation to observed clinical outcomes. The MSM approach predicted the CYP3A4 induction-based DDI risk accurately but could not capture CYP2C induction with similar precision. Conclusions: Overall, this is the first study that demonstrates the utility of PBPK modeling as a complementary approach to MSM for CYP2C induction-based DDI risk assessment. Full article

Background/Objective: Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool for predicting pharmacokinetics (PK) to support drug development and precision medicine. However, it has not been established for non-renal clearance pathways in patients with end-stage renal disease (ESRD), a population that bears heavy medication burden and is thereby at high risk for drug–drug–disease interactions (DDDIs). Furthermore, the pronounced inter-individual variability in PK observed in ESRD patients highlights the urgent need for individualized PBPK models. Methods: In this study, we developed a PBPK population model for ESRD patients, incorporating functional changes in key drug-metabolizing enzymes and transporters (DMETs), including CYP3A4, OATP1B1/3, P-gp, and BCRP. The model was initially constructed using the recalibrated demographic and physiological parameters of ESRD patients. Then, we used five well-validated substrates (midazolam, dabigatran etexilate, pitavastatin, rosuvastatin, and atorvastatin) and their corresponding PK profiles from ESRD patients taking a microdose cocktail regimen to simultaneously estimate the abundance of all these DMETs. Lastly, machine learning was employed to identify potential factors influencing individual clearance. Results: Our study suggested a significant reduction in hepatic OATP1B1/3 (75%) and intestinal P-gp abundance (34%) in ESRD patients. Ileum BCRP abundance was estimated to increase by 100%, while change in hepatic CYP3A4 abundance is minimal. Notably, simulations of drug combinations revealed potential DDDI risks that were not observed in healthy volunteers. Machine learning further identified Clostridium XVIII and Escherichia genus abundances as significant factors influencing dabigatran clearance. For rosuvastatin, aspartate aminotransferase, total bilirubin, Bacteroides, and Megamonas genus abundances were key influencers. No significant factors were identified for midazolam, pitavastatin, or atorvastatin. Conclusions: Our study proposes a feasible strategy for individualized PK prediction by integrating PBPK modeling with machine learning to support the development and precise use of the aforementioned DMET substrates in ESRD patients. Full article

Background/Objectives: Our work was designed to study the physicochemical properties, safety profile, pharmacokinetics, and prophylactic efficacy of an original iodine–dextrin-based pharmaceutical formulation (PA), both alone and in combination with azithromycin (AZ), in a murine model of LPS-induced sepsis. Methods/Results: UV–vis and ¹H-NMR spectroscopy confirmed the formation of a stable iodine–dextrin complex, with triiodide anions stabilized by hydrogen bonding and donor–acceptor interactions. No clinical signs of acute toxicity were observed at doses up to 5000 mg/kg, and subacute administration (62.5 and 125 mg/kg) showed no adverse effects on hematological or biochemical parameters. A mild, non-pathological enlargement of thyrocytes and parallel increases in TSH, T3, and T4 levels were observed at 125 mg/kg, consistent with physiological adaptation to iodine. Pharmacokinetic analysis revealed high oral bioavailability (~92%), prolonged half-life (~21 h), and wide tissue distribution with low clearance. In the sepsis model, pretreatment with AZ+PA alleviated clinical symptoms, maintained body weight, and significantly improved hematological parameters, reducing WBCs and CRP levels. The combination also decreased plasma IL-6 and TNF-α concentrations more effectively than either agent alone, indicating a synergistic anti-inflammatory effect. Histological analysis confirmed that PA, particularly in combination with AZ, mitigated LPS-induced tissue injury in the liver, kidney, and lungs. Conclusions: These findings suggest that PA is a safe, bioavailable compound with immunomodulatory properties that enhance azithromycin’s protective effects during systemic inflammation. This supports its potential use as a prophylactic agent in clinical settings, such as preoperative immune modulation to prevent sepsis-related complications. Full article

Melittin, a cytolytic peptide derived from honeybee venom, has demonstrated potent anticancer activity through mechanisms such as membrane disruption, apoptosis induction, and modulation of key signaling pathways. Melittin exerts its anticancer activity by interacting with key molecular targets, including downregulation of the PI3K/Akt and NF-κB signaling pathways, and by inducing mitochondrial apoptosis through reactive oxygen species generation and cytochrome c release. However, its clinical application is hindered by its systemic and hemolytic toxicity, rapid degradation in plasma, poor pharmacokinetics, and immunogenicity, necessitating the development of targeted delivery strategies to enable safe and effective treatment. Nanoparticle-based delivery systems have emerged as a promising strategy for overcoming these challenges, offering improved tumor targeting, reduced off-target effects, and enhanced stability. This review provides a comprehensive overview of the mechanisms through which melittin exerts its anticancer effects and evaluates the development of various melittin-loaded nanocarriers, including liposomes, polymeric nanoparticles, dendrimers, micelles, and inorganic systems. It also summarizes the preclinical evidence for melittin nanotherapy across a wide range of cancer types, highlighting both its cytotoxic and immunomodulatory effects. The potential of melittin nanoparticles to overcome multidrug resistance and synergize with chemotherapy, immunotherapy, photothermal therapy, and radiotherapy is discussed. Despite promising in vitro and in vivo findings, its clinical translation remains limited. Key barriers include toxicity, manufacturing scalability, regulatory approval, and the need for more extensive in vivo validation. A key future direction is the application of computational tools, such as physiologically based pharmacokinetic modeling and artificial-intelligence-based modeling, to streamline development and guide its clinical translation. Addressing these challenges through focused research and interdisciplinary collaboration will be essential to realizing the full therapeutic potential of melittin-based nanomedicines in oncology. Overall, this review synthesizes the findings from over 100 peer-reviewed studies published between 2008 and 2025, providing an up-to-date assessment of melittin-based nanomedicine strategies across diverse cancer types. Full article

Topical drug administration is a common method of delivering medications to the eye to treat various ocular conditions, including glaucoma, dry eye, and inflammation. Drug efficacy following topical administration, including the drug’s distribution within the eye, absorption and elimination rates, and physiological responses can be predicted using physiologically based pharmacokinetic (PBPK) modeling. High-resolution computational models of the eye are desirable to improve simulations of drug delivery; however, these approaches can have long run times. In this study, a fast-running computational quasi-3D (Q3D) model of the human tear film was developed to account for absorption, blinking, drainage, and evaporation. Visualization of blinking mechanics and flow distributions throughout the tear film were enabled using this Q3D approach. Average drug absorption throughout the tear film subregions was quantified using a high-resolution compartment model based on a system of ordinary differential equations (ODEs). Simulations were validated by comparing them with experimental data from topical administration of 0.1% dexamethasone suspension in the tear film (R² = 0.76, RMSE = 8.7, AARD = 28.8%). Overall, the Q3D tear film model accounts for critical mechanistic factors (e.g., blinking and drainage) not previously included in fast-running models. Further, this work demonstrated methods toward improved computational efficiency, where central processing unit (CPU) time was decreased while maintaining accuracy. Building upon this work, this Q3D approach applied to the tear film will allow for more seamless integration into full-body models, which will be an extremely valuable tool in the development of treatments for ocular conditions. Full article

Background/Objectives: Magnetic resonance imaging (MRI) is a powerful, non-invasive diagnostic tool capable of capturing detailed anatomical and physiological information. MRI contrast agents enhance image contrast but, especially linear gadolinium-based compounds, have been associated with safety concerns. This has prompted interest in alternative contrast agents. Manganese-based contrast agents offer a promising substitute, owing to manganese’s favorable magnetic properties, natural biological role, and strong T1 relaxivity. This review aims to critically assess the structure, mechanisms, applications, and challenges of manganese-based contrast agents in MRI. Methods: This review synthesizes findings from preclinical and clinical studies involving various types of manganese-based contrast agents, including small-molecule chelates, nanoparticles, theranostic platforms, responsive agents, and controlled-release systems. Special attention is given to pharmacokinetics, biodistribution, and safety evaluations. Results: Mn-based agents demonstrate promising imaging capabilities, with some achieving relaxivity values comparable to gadolinium compounds. Targeted uptake mechanisms, such as hepatocyte-specific transport via organic anion-transporting polypeptides, allow for enhanced tissue contrast. However, concerns remain regarding the in vivo release of free Mn²⁺ ions, which could lead to toxicity. Preliminary toxicity assessments report low cytotoxicity, but further comprehensive long-term safety studies should be carried out. Conclusions: Manganese-based contrast agents present a potential alternative to gadolinium-based MRI agents pending further validation. Despite promising imaging performance and biocompatibility, further investigation into stability and safety is essential. Additional research is needed to facilitate the clinical translation of these agents. Full article

Background/Objectives: Tofacitinib is a Janus kinase 1 and 3 inhibitor that was developed to treat rheumatoid arthritis. Accordingly, this study aimed to predict plasma tofacitinib concentrations and pharmacokinetic parameters in patients with renal failure through physiologically based pharmacokinetic (PBPK) simulations. Methods: PK-Sim and Simcyp simulators were used, as well as conventional Dedrick plot analysis, employing a single animal extrapolation method. The predictions were compared with previously published data. Results: PBPK simulations of tofacitinib in patients with renal failure closely matched the observed plasma concentration profiles and pharmacokinetic results, including the area under the plasma concentration–time curve (AUC), maximum plasma concentration (C_max), and time to reach C_max (T_max). The ratios of the simulated to observed plasma concentrations and pharmacokinetic parameters for tofacitinib were within a 0.5–2.0-fold error range. Although the results from the Dedrick plot were reasonably good, they were less accurate than those of the PBPK simulations. This was because the Dedrick plot relied solely on preclinical plasma concentration data without incorporating drug physicochemical properties, in vitro data, or physiological and pathophysiological variables. Conclusions: The findings suggest that PBPK simulations using single-species extrapolation effectively provide preliminary estimates of plasma tofacitinib concentration profiles and pharmacokinetic parameters in humans under specific conditions, including renal failure. Furthermore, the results provide a foundation for adjusting tofacitinib dosage and dosing schedules to maintain effective plasma concentrations by considering the pathophysiological characteristics of patients according to their specific diseases. Full article

Pregnancy introduces significant physiological changes that alter the pharmacokinetics (PK) of antiretroviral therapy (ART), impacting its safety and efficacy in HIV-positive women. Optimizing ART during pregnancy is critical to maintaining maternal virological suppression and preventing mother-to-child transmission (MTCT) of HIV. This review evaluates the impact of pregnancy-induced PK changes on ART and proposes strategies for tailored regimens to improve outcomes. A comprehensive review of published literature was conducted, focusing on PK adaptations during pregnancy and their implications for different ART classes, including protease inhibitors (PIs), integrase strand transfer inhibitors (INSTIs), and nucleoside reverse transcriptase inhibitors (NRTIs). Key studies were analyzed to assess drug exposure, efficacy, and safety. Pregnancy significantly alters the PK of antiretrovirals, with increased hepatic metabolism, renal clearance, and changes in plasma protein binding leading to reduced drug exposure. For example, drugs like lopinavir and atazanavir require dose adjustments, while dolutegravir maintains efficacy despite reduced plasma levels. Integrase inhibitors demonstrate favorable virological suppression, although cobicistat-boosted regimens show subtherapeutic levels. Tailored approaches, such as therapeutic drug monitoring (TDM), optimize ART efficacy while minimizing toxicity. Pregnancy-specific PK changes necessitate evidence-based ART adjustments to ensure virological suppression and reduce MTCT risk. Incorporating TDM, leveraging pharmacogenomic insights, and prioritizing maternal and neonatal safety are critical for personalized ART management. Further research into long-acting formulations and global guideline harmonization is needed to address disparities in care and improve outcomes for HIV-positive pregnant women. Full article

Background: Understanding interactions between cytokine antagonists and drugs is essential for effective medication management in inflammatory conditions. Recent regulatory authority guidelines emphasise a systematic, risk-based approach to evaluating these interactions, underscoring the need for mechanistic insight. Proinflammatory cytokines, such as interleukin-6 (IL-6), modulate cytochrome P450 (CYP) enzymes, reducing the metabolism of CYP substrates. Cytokine antagonists (such as IL-6 receptor antagonists) can counteract this effect, restoring CYP activity and increasing drug clearance. However, quantitative prediction of cytokine-mediated drug interactions remains challenging, as existing models often lack the mechanistic detail needed to capture the dynamic relationship between cytokine signalling, receptor engagement, and downstream modulation of drug metabolism. Methods: A physiologically based pharmacokinetic (PBPK) framework incorporating cytokine–receptor binding, subsequent downregulation of CYP expression, and blockade of the cytokine signalling by a therapeutic protein antagonist was developed to simulate and investigate cytokine antagonist-drug interactions. Tocilizumab, a humanised IL-6 receptor antagonist used to treat several inflammatory conditions associated with elevated IL-6 levels, was selected as a model drug to demonstrate the utility of the framework. Results: The developed PBPK model accurately predicted the pharmacokinetics profiles of tocilizumab and captured clinically observed dynamic changes in simvastatin exposure before and after tocilizumab treatment in rheumatoid arthritis (RA) patients. Simulated IL-6 dynamics aligned with observed clinical profiles, showing transient elevation following receptor blockade and associated restoration of CYP3A4 activity. Prospective simulations with commonly co-administered CYP substrates (celecoxib, chloroquine, cyclosporine, ibuprofen, prednisone, simvastatin, and theophylline) in RA patients revealed dose regimen- and drug-dependent differences in interaction magnitude. Conclusions: This study demonstrated the utility of PBPK models in providing a mechanistic understanding of cytokine antagonist-drug interactions, supporting enhanced therapeutic decision-making and optimising patient care in inflammatory conditions. Full article

Bariatric surgery involves major changes in the anatomy and physiology of the gastrointestinal tract, which may alter oral drug bioavailability and efficacy. Phosphodiesterase-5 inhibitor (PDE5i) drugs are the first-line treatment of erectile dysfunction, a condition associated with a higher BMI. In this paper, we examine the PDE5i vardenafil for possible post-bariatric changes in solubility/dissolution and absorption. Vardenafil solubility was determined in vitro, as well as ex vivo using aspirated gastric contents from patients prior to vs. following bariatric procedures. Dissolution was tested in vitro under unoperated stomach vs. post-gastric sleeve/bypass conditions. Lastly, the gathered solubility/dissolution data were used to produce an in silico physiologically based pharmacokinetic (PBPK) model (GastroPlus^®), where gastric volume, pH, and transit time, as well as proximal GI bypass (when relevant) were all adjusted for, evaluating vardenafil dissolution, gastrointestinal compartmental absorption, and pharmacokinetics before vs. after different bariatric procedures. pH-dependent solubility was demonstrated for vardenafil with low (pH 7) vs. high solubility (pH 1–5), which was confirmed ex vivo. The impaired dissolution of all vardenafil doses under post-gastric bypass conditions was demonstrated, contrary to complete (100%) dissolution under pre-surgery and post-sleeve gastrectomy conditions. Compared to unoperated individuals, PBPK simulations revealed altered pharmacokinetics post-gastric bypass (but not after sleeve gastrectomy), with 30% lower peak plasma concentration (C_max) and 40% longer time to C_max (T_max). Complete absorption after gastric bypass is predicted for vardenafil, which is attributable to significant absorption from the large intestine. The biopharmaceutics and PBPK analysis indicate that vardenafil may be similarly effective after sleeve gastrectomy as before the procedure. However, results after gastric bypass question the effectiveness of this PDE5i. Specifically, vardenafil’s onset of action might be delayed and unpredictable, negatively affecting the practicality of the intended use. Full article

Background: Accurately determining pediatric dosing is essential prior to initiating clinical trials or administering medications in routine clinical settings. In children, ethical considerations demand careful evaluation of both safety and effectiveness. Typically, dosing recommendations for therapeutic proteins, such as monoclonal antibodies (mAbs), are derived from adult dosages using body weight as a scaling factor. However, this method overlooks key physiological and biochemical distinctions between pediatric and adult patients. Therefore, this could lead to the underexposure of mAbs, limiting their efficacy in this population. Additional methods are necessary to predict pediatric doses mechanistically. For small molecules, physiologically based pharmacokinetic (PBPK) models have been extensively used to predict pediatric doses based on physiological age-related changes and enzymes/transporters ontogeny. This study aims to evaluate the ability of PBPK models to predict mAbs’ pediatric exposure. Methods: Three mAbs were used for model development and validation: bevacizumab, infliximab, and atezolizumab. The PBPK models were built using GastroPlus^© Biologics module. For each mAb, the PBPK model was developed based on observed data in healthy and/or patient adults. Then, the physiological parameters were scaled to describe the pediatric physiology to predict exposure to the pediatric populations. Predicted plasma concentration–time courses were overlaid with reported observed data to assess the ability of the PBPK model to predict pediatric exposure. Results: Results showed that PBPK models accurately predicted pediatric pharmacokinetics for mAbs. Conclusions: This research marks a significant step in validating mechanistic extrapolation methods for biologics exposure prediction in children using PBPK models. Full article