Search Results (29)

Background/Objectives: Linezolid is a first-in-class oxazolidinone antibiotic that exhibits activity against Gram-positive pathogens, including methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci. However, its clinical use is often restricted because of hematological toxicities, particularly thrombocytopenia, in patients with renal impairment. That side effect is thought to result from the systemic accumulation of pharmacologically inactive metabolites generated by oxidative degradation and ring-opening of the morpholine, but the details remain unclear. In this study, we established a novel synthetic route for four linezolid metabolites (PNU-142618, 142300, 142586 and 173558). Methods: The four major metabolites, which are secondary or tertiary amines, were synthesized using the aniline derivatives protected with a 2-nitrobenzensulfonyl (Ns) group. Results: Application of this Ns strategy enabled selective N-alkylation, enabling efficient synthesis of the target metabolites. The desired metabolites containing a carboxylic acid group were obtained as their sodium salts. This is the first report on the synthesis of PNU-142618 and 173558. Conclusions: The established synthetic pathway provides access to four linezolid metabolites. The results facilitated the provision of compounds necessary for comprehensive pharmacokinetic and toxicological studies. Full article

Background/Objectives: In recent years, clinical pharmacometrics has become vital for drug development and clinical practice, particularly for predicting drug efficacy and safety. Population pharmacokinetic models are used for drugs for which therapeutic drug monitoring is recommended in clinical practice. Numerous population pharmacokinetic models have been developed for patients with similar clinical and demographic characteristics, resulting in reduced inter-individual variability. Despite the existence of diverse-population pharmacokinetic models, selecting an appropriate model for bedside use remains challenging. This study proposes a model-simulated model-based meta-analysis (M-cubed) to construct a unified model capable of accommodating a wide range of patient backgrounds. Methods: Vancomycin (VCM), a drug used for therapeutic drug monitoring, was used as an example. Using information from published VCM models, the M-cubed method was employed to generate virtual patient data for each publication through simulation, followed by modeling the integrated dataset. Results: Population pharmacokinetic analysis was performed on data from 19 virtual patient models, resulting in a total of 2303 cases. Covariates in the final model included creatinine clearance and body weight. The predictive ability of the model was robust. Conclusions: A model that integrates several population studies using the M-cubed method is required to address the need in clinical practice. Full article

Polypharmacy is typically seen as an unavoidable consequence of multimorbidity and aging, with clinicians addressing complex medication lists unsystematically. In this perspective, we argue that polypharmacy should be managed as a chronic condition. Like diabetes or hypertension, for example, the medication burden shows persistence, progression in its absence despite active management, predictable complications (such as falls, delirium, renal injury, functional decline), and a need for structured surveillance. We introduce a pragmatic diagnostic framework that moves beyond pill counts to modality-agnostic, regimen-level risk across prescribed and non-prescribed medicines. Diagnosis rests on prolonged exposure, composite burden indices (e.g., anticholinergic/sedative load), medication-related complications or prescribing cascades, and the need for a planned review. As biologics, gene therapies and long-acting formulations can lower tablet numbers while increasing monitoring, administration, and interaction complexity. We treat polypharmacy as cumulative pharmacodynamic and operational burden. We advocate stage matched care with unique, functional aims—decreasing the harmful burden instead of mass deprescribing—and position a structured medication review as the standard for polypharmacy with support from pharmacists, shared decision making, and safety netted taper plans. The framework fosters patient-centred care, embedding continuity and equity, and outlines a concise outcome set that integrates pharmacometric measures with patient-reported function and treatment burden. At the systems level, the framework enables registries, recall systems, decision support, and audit/feedback mechanisms to shift from sporadic medication list clean-up to a structured, measurable long-term program. Redefining polypharmacy in this way aligns clinical practice, education, and policy with real-world evidence, fostering a cohesive pathway to safer, streamlined, and more patient-centred care in community settings. Full article

Background/Objectives: The administration of human monoclonal antibodies (mAb) in preclinical pharmacokinetics and toxicology studies often triggers an immune response, leading to the formation of anti-drug antibodies (ADA). To mitigate this effect, we have recently performed and reported on studies using short-term immunosuppressive regimens to induce prolonged immune tolerance towards a human mAb, erenumab, in rats. Here, we report on the development of a semi-mechanistic modeling approach that quantitatively integrates pharmacokinetic and immunogenicity assessments from immune tolerance induction studies to provide a framework for the simulation-based evaluation of different immune induction scenarios for the maintenance of prolonged immune tolerance towards human mAbs. Methods: The integrated pharmacokinetic/pharmacodynamic (PK/PD) modeling approach combined a semi-mechanistic model of the adaptive immune system to predict ADA formation kinetics with a population pharmacokinetic model to assess the impact of the time course of the ADA magnitude on the PK of erenumab in rats. Model-derived erenumab concentration–time profiles served as input for a quantitative system pharmacology-style semi-mechanistic model of the adaptive immune system to conceptualize the ADA response as a function of the kinetics of CD4⁺ T helper cells and T regulatory cells. Results: The model adequately described the observed ADA magnitude–time profiles in all treatment groups and reasonably simulated the kinetics of selected immune cells responsible for ADA formation. It also successfully captured the impact of tacrolimus/sirolimus immunomodulation on ADA formation, demonstrating that the regimen effectively suppressed ADA formations and induced immune tolerance. Conclusions: This work demonstrates the utility of modeling approaches to integrate pharmacokinetic and immunogenicity assessment data for the prospective planning of long-term toxicology studies to support the preclinical development of mAbs. Full article

Cisplatin (cis-diamminedichloro-platinum; CDDP) is a chemotherapeutic agent that frequently induces peripheral neuropathy characterized by mechanical allodynia. Herein, we aimed to determine the effects of valproic acid (VPA) on cisplatin-induced mechanical allodynia in rats and elucidate the underlying mechanisms. A single administration of VPA (150 mg/kg) transiently suppressed CDDP-induced mechanical allodynia, correlating with serum VPA concentrations. Repeated VPA administration before or after the onset of CDDP-induced mechanical allodynia significantly attenuated allodynia even after VPA discontinuation, suggesting fundamental treatment potential. Mechanistically, CDDP increased the expression of neurokinin 1 receptor (NK1R) mRNA in the dorsal horn of the spinal cord, and this increased expression was suppressed by repeated VPA administration. Treatment with an NK1R antagonist alleviated CDDP-induced mechanical allodynia, indicating the involvement of NK1R in allodynia. In vitro assays revealed that VPA did not affect the cytotoxicity of CDDP in Walker 256 cells, suggesting that VPA does not interfere with the antitumor activity of CDDP. Overall, repeated VPA administration may fundamentally ameliorate CDDP-induced peripheral neuropathy by suppressing the CDDP-induced increased NK1R expression without compromising the antitumor effects of CDDP. These findings provide insights into the potential use of VPA as a therapeutic agent for managing CDDP-induced peripheral neuropathy. Full article

Autoimmune diseases (AIDs) are a group of disorders in which the immune system attacks the body’s own tissues, leading to chronic inflammation and organ damage. These diseases are difficult to treat due to variability in drug PK among individuals, patient responses to treatment, and the side effects of long-term immunosuppressive therapies. In recent years, pharmacometrics has emerged as a critical tool in drug discovery and development (DDD) and precision medicine. The aim of this review is to explore the diverse roles that pharmacometrics has played in addressing the challenges associated with DDD and personalized therapies in the treatment of AIDs. Methods: This review synthesizes research from the past two decades on pharmacometric methodologies, including Physiologically Based Pharmacokinetic (PBPK) modeling, Pharmacokinetic/Pharmacodynamic (PK/PD) modeling, disease progression (DisP) modeling, population modeling, model-based meta-analysis (MBMA), and Quantitative Systems Pharmacology (QSP). The incorporation of artificial intelligence (AI) and machine learning (ML) into pharmacometrics is also discussed. Results: Pharmacometrics has demonstrated significant potential in optimizing dosing regimens, improving drug safety, and predicting patient-specific responses in AIDs. PBPK and PK/PD models have been instrumental in personalizing treatments, while DisP and QSP models provide insights into disease evolution and pathophysiological mechanisms in AIDs. AI/ML implementation has further enhanced the precision of these models. Conclusions: Pharmacometrics plays a crucial role in bridging pre-clinical findings and clinical applications, driving more personalized and effective treatments for AIDs. Its integration into DDD and translational science, in combination with AI and ML algorithms, holds promise for advancing therapeutic strategies and improving autoimmune patients’ outcomes. Full article

Similar to other populations, care of neonates strongly relies on robust guidance on neonatal pharmacotherapy, covering an age-appropriate drug formulation, an individualized dose, and information on its efficacy and safety for a specific indication in this population, preferably weighted to alternative approaches [...] Full article

The antiparasitic drug ivermectin is approved for persons > 15 kg in the US and EU. A pharmacometric (PMX) population model with clinical PK data was developed (i) to characterize the effect of the patient-friendly ivermectin formulation CHILD-IVITAB on the absorption process and (ii) to evaluate dosing for studies in children < 15 kg. Simulations were performed to identify dosing with CHILD-IVITAB associated with similar exposure coverage in children ≥ 15 kg and < 15 kg as observed in adults receiving the reference formulation STROMECTOL^®. A total of 448 ivermectin concentrations were available from 16 healthy adults. The absorption rate constant was 2.41 h⁻¹ (CV 19%) for CHILD-IVITAB vs. 1.56 h⁻¹ (CV 43%) for STROMECTOL^®. Simulations indicated that 250 µg/kg of CHILD-IVITAB is associated with exposure coverage in children < 15 kg consistent with that observed in children ≥ 15 kg and adults receiving 200 µg/kg of STROMECTOL^®. Performed analysis confirmed that CHILD-IVITAB is associated with faster and more controlled absorption than STROMECTOL^®. Simulations indicate that 250 µg/kg of CHILD-IVITAB achieves equivalent ivermectin exposure coverage in children < 15 kg as seen in children ≥ 15 kg and adults. Full article

The landscape of medical treatments is undergoing a transformative shift. Precision medicine has ushered in a revolutionary era in healthcare by individualizing diagnostics and treatments according to each patient’s uniquely evolving health status. This groundbreaking method of tailoring disease prevention and treatment considers individual variations in genes, environments, and lifestyles. The goal of precision medicine is to target the “five rights”: the right patient, the right drug, the right time, the right dose, and the right route. In this pursuit, in silico techniques have emerged as an anchor, driving precision medicine forward and making this a realistic and promising avenue for personalized therapies. With the advancements in high-throughput DNA sequencing technologies, genomic data, including genetic variants and their interactions with each other and the environment, can be incorporated into clinical decision-making. Pharmacometrics, gathering pharmacokinetic (PK) and pharmacodynamic (PD) data, and mathematical models further contribute to drug optimization, drug behavior prediction, and drug–drug interaction identification. Digital health, wearables, and computational tools offer continuous monitoring and real-time data collection, enabling treatment adjustments. Furthermore, the incorporation of extensive datasets in computational tools, such as electronic health records (EHRs) and omics data, is also another pathway to acquire meaningful information in this field. Although they are fairly new, machine learning (ML) algorithms and artificial intelligence (AI) techniques are also resources researchers use to analyze big data and develop predictive models. This review explores the interplay of these multiple in silico approaches in advancing precision medicine and fostering individual healthcare. Despite intrinsic challenges, such as ethical considerations, data protection, and the need for more comprehensive research, this marks a new era of patient-centered healthcare. Innovative in silico techniques hold the potential to reshape the future of medicine for generations to come. Full article

Model-informed precision dosing (MIPD) might be used to optimize antibiotic treatment. Procalcitonin (PCT) is a biomarker for severity of infection and response to antibiotic treatment. The aim of this study was to assess the impact of MIPD on the course of PCT and to investigate the association of PCT with pharmacodynamic target (PDT) attainment in critically ill patients. This is a secondary analysis of the DOLPHIN trial, a multicentre, open-label, randomised controlled trial. Patients with a PCT value available at day 1 (T1), day 3 (T3), or day 5 (T5) after randomisation were included. The primary outcome was the absolute difference in PCT concentration at T1, T3, and T5 between the MIPD and the standard dosing group. In total, 662 PCT concentrations from 351 critically ill patients were analysed. There was no statistically significant difference in PCT concentration between the trial arms at T1, T3, or T5. The median PCT concentration was highest in patients who exceeded 10× PDT at T1 [13.15 ng/mL (IQR 5.43–22.75)]. In 28-day non-survivors and in patients that exceeded PDT at T1, PCT decreased significantly between T1 and T3, but plateaued between T3 and T5. PCT concentrations were not significantly different between patients receiving antibiotic treatment with or without MIPD guidance. The potential of PCT to guide antibiotic dosing merits further investigation. Full article

Currently, there is insufficient information on the variability in levocetirizine pharmacometrics among individuals, a crucial aspect for establishing its clinical use. The gender differences in pharmacokinetics and the extent of variation in pharmacodynamics have not been definitively identified. The primary goal of this study was to investigate gender differences in levocetirizine pharmacokinetics and quantitatively predict and compare how these gender-related pharmacokinetic differences impact pharmacodynamics, using population pharmacokinetic–pharmacodynamic modeling. Bioequivalence results for levocetirizine (only from the control formulation) were obtained from both healthy Korean men and women. Physiological and biochemical parameters for each individual were utilized as pharmacokinetic comparison and modeling data between genders. Pharmacodynamic modeling was performed using reported data on antihistamine responses following levocetirizine exposure. Gender, weight, body surface area, peripheral distribution volume, albumin, central–peripheral inter-compartmental clearance, and the fifth sequential absorption rate constant were explored as effective covariates. A comparison of the model simulation results showed a higher maximum concentration and faster plasma loss in females than in males, resulting in a faster recovery to baseline of the antihistamine effect; however, the absolute differences between genders in the mean values were not large within 10 ng/mL (for plasma concentrations) or % (wheal and flare size changes). Regarding the pharmacokinetics and pharmacodynamics of levocetirizine, the gender effect may not be significant when applying the usual dosage (5 mg/day). This study will be useful for bridging the knowledge gap in scientific precision medicine by introducing previously unconfirmed information regarding gender differences in levocetirizine pharmacometrics. Full article

In the intensive care unit (ICU), infection-related mortality is high. Although adequate antibiotic treatment is essential in infections, beta-lactam target non-attainment occurs in up to 45% of ICU patients, which is associated with a lower likelihood of clinical success. To optimize antibiotic treatment, we aimed to develop beta-lactam target non-attainment prediction models in ICU patients. Patients from two multicenter studies were included, with intravenous intermittent beta-lactam antibiotics administered and blood samples drawn within 12–36 h after antibiotic initiation. Beta-lactam target non-attainment models were developed and validated using random forest (RF), logistic regression (LR), and naïve Bayes (NB) models from 376 patients. External validation was performed on 150 ICU patients. We assessed performance by measuring discrimination, calibration, and net benefit at the default threshold probability of 0.20. Age, sex, serum creatinine, and type of beta-lactam antibiotic were found to be predictive of beta-lactam target non-attainment. In the external validation, the RF, LR, and NB models confirmed good discrimination with an area under the curve of 0.79 [95% CI 0.72–0.86], 0.80 [95% CI 0.73–0.87], and 0.75 [95% CI 0.67–0.82], respectively, and net benefit in the RF and LR models. We developed prediction models for beta-lactam target non-attainment within 12–36 h after antibiotic initiation in ICU patients. These online-accessible models use readily available patient variables and help optimize antibiotic treatment. The RF and LR models showed the best performance among the three models tested. Full article

A permeability-limited physiologically based pharmacokinetic (PBPK) model featuring four subcompartments (corresponding to the intracellular and extracellular water of the tissue, the residual plasma, and blood cells) for each tissue has been developed in MATLAB/SimBiology and applied to various what-if scenario simulations. This model allowed us to explore the complex interplay of passive permeability, metabolism in tissue or residual blood, active uptake or efflux transporters, and different dosing routes (intravenous (IV) or oral (PO)) in determining the dynamics of the tissue/plasma partition coefficient (Kp) and volume of distribution (Vd) within a realistic pseudo-steady state. Based on the modeling exercise, the permeability, metabolism, and transporters demonstrated significant effects on the dynamics of the Kp and Vd for IV bolus administration and PO fast absorption, but these effects were not as pronounced for IV infusion or PO slow absorption. Especially for low-permeability compounds, uptake transporters were found to increase both the Kp and Vd at the pseudo-steady state (Vdss), while efflux transporters had the opposite effect of decreasing the Kp and Vdss. For IV bolus administration and PO fast absorption, increasing tissue metabolism was predicted to elevate the Kp and Vdss, which contrasted with the traditional derivation from the steady-state perfusion-limited PBPK model. Moreover, metabolism in the residual blood had more impact on the Kp and Vdss compared to metabolism in tissue. Due to its ability to offer a more realistic description of tissue dynamics, the permeability-limited PBPK model is expected to gain broader acceptance in describing clinical PK and observed Kp and Vdss, even for certain small molecules like cyclosporine, which are currently treated as perfusion-limited in commercial PBPK platforms. Full article

Rabeprazole is a proton pump inhibitor that inhibits gastric acid production and increases gastric pH; it is widely used clinically as a treatment option for gastritis and gastric ulcers. However, information on the inter-individual variability of rabeprazole pharmacometrics, which is a key element in establishing its scientific clinical use, is still lacking. Particularly, the differences in pharmacokinetics between genders and the degree of variation in pharmacodynamics have not been clearly identified. Thus, the main purpose of this study was to explore any differences in rabeprazole pharmacokinetics between genders and to quantitatively predict and compare the effects of any differences in pharmacokinetics between genders on known pharmacodynamics using population pharmacokinetic–pharmacodynamic modeling. To compare pharmacokinetics and modeling data between genders, bioequivalence results were used simultaneously on healthy Korean men and women using the physiological and biochemical parameters derived from each individual. Pharmacodynamic modeling was performed based on the data of previously reported gastric pH changes in response to rabeprazole plasma concentrations, which was co-linked to the central compartmental bioavailable concentration in the population pharmacokinetic model. There was no significant difference in the level of rabeprazole exposure and elimination of plasma between genders following oral administration of 10 mg enteric-coated rabeprazole tablets; however, there was a clear delay in absorption in women compared to men. Additionally, a comparison of pharmacokinetic parameters normalized to body weight between genders showed that the maximum plasma concentrations were significantly higher in women than in men, again suggesting gender differences in rabeprazole absorption. The population pharmacokinetic profiles for rabeprazole were described using a three-sequential multi-absorption with lag time (T_lag) two-compartment model, whereas body surface area and gender were explored as effective covariates for absorption rate constant and T_lag, respectively. The effect of increased gastric pH due to plasma exposure to rabeprazole was explained using the Sigmoid Emax model, with the baseline as a direct response. The significantly longer rabeprazole T_lag in females delayed the onset of an effect by an average of 1.58 times (2.02–3.20 h), yet the overall and maximum effects did not cause a significant difference within 15%. In the relative comparison of the overall efficacy of rabeprazole enteric-coated tablet administration between genders, it was predicted based on the model that males would have higher efficacy. This study will be very useful in broadening the perspective of interpreting drug diversity between individuals and narrowing the gap in knowledge related to scientific precision medicine by presenting new information on gender differences in rabeprazole pharmacometrics that had not been previously identified. Full article

The genesis of cancer is a precisely organized process in which normal cells undergo genetic alterations that cause the cells to multiply abnormally, colonize, and metastasize to other organs such as the liver, lungs, colon, and brain. Potential drugs that could modify these carcinogenic pathways are the ones that will be used in clinical trials as anti-cancer drugs. Resveratrol (RES) is a polyphenolic natural antitoxin that has been utilized for the treatment of several diseases, owing to its ability to scavenge free radicals, control the expression and activity of antioxidant enzymes, and have effects on inflammation, cancer, aging, diabetes, and cardioprotection. Although RES has a variety of pharmacological uses and shows promising applications in natural medicine, its unpredictable pharmacokinetics compromise its therapeutic efficacy and prevent its use in clinical settings. RES has been encapsulated into various nanocarriers, such as liposomes, polymeric nanoparticles, lipidic nanocarriers, and inorganic nanoparticles, to address these issues. These nanocarriers can modulate drug release, increase bioavailability, and reach therapeutically relevant plasma concentrations. Studies on resveratrol-rich nano-formulations in various cancer types are compiled in the current article. Studies relating to enhanced drug stability, increased therapeutic potential in terms of pharmacokinetics and pharmacodynamics, and reduced toxicity to cells and tissues are the main topics of this research. To keep the readers informed about the current state of resveratrol nano-formulations from an industrial perspective, some recent and significant patent literature has also been provided. Here, the prospects for nano-formulations are briefly discussed, along with machine learning and pharmacometrics methods for resolving resveratrol’s pharmacokinetic concerns. Full article