Pharmaceutical Research

Wang, Xin; Wu, Jiangfan; Ye, Hongjiang; Zhao, Xiaofang; Zhu, Shenyin

doi: 10.1007/s11095-024-03676-4pmid: 38383936

PurposeThe physiologically based pharmacokinetic (PBPK) modeling has received increasing attention owing to its excellent predictive abilities. However, there has been no bibliometric analysis about PBPK modeling. This research aimed to summarize the research development and hot points in PBPK model utilization overall through bibliometric analysis.MethodsWe searched for publications related to the PBPK modeling from 1999 to 2023 in the Web of Science Core Collection (WoSCC) database. The Microsoft Office Excel, CiteSpace and VOSviewers were used to perform the analyses.ResultsA total of 4,649 records from 1999 to 2023 were identified, and the largest number of publications focused in the period 2018–2023. The United States was the leading country, and the Environmental Protection Agency (EPA) was the leading institution. The journal Drug Metabolism and Disposition published and co-cited the most articles. Drug–drug interactions, special populations, and new drug development are the main topics in this research field.ConclusionWe first visualize the research landscape and hotspots of the PBPK modeling through bibliometric methods. Our study provides a better understanding for researchers, especially beginners about the dynamization of PBPK modeling and presents the relevant trend in the future.

Maleki, Farzaneh; Chang, Cheng; Purohit, Vivek S.; Nicholas, Timothy

doi: 10.1007/s11095-024-03654-wpmid: 38519816

IntroductionTopical brepocitinib, a tyrosine kinase (TYK)2/Janus kinase (JAK)1 inhibitor, is in development for psoriasis (PsO) and atopic dermatitis (AD). Quantitative analyses of prior clinical trial data were used to inform future clinical trial designs.MethodsTwo phase 2b studies in patients with AD and PsO were used to characterize the amount of topical brepocitinib and the resultant systemic trough concentration (CTrough) using a linear mixed-effects regression (LMER). This model was used to predict brepocitinib systemic CTrough for higher treated body surface areas (BSAs) in adults and children. Information from non-clinical and clinical trials with oral brepocitinib was leveraged to set safety thresholds. This combined approach was used to inform future dose-strength selection and treated BSA limits.ResultsData from 256 patients were analyzed. Patient type, dose strength, and frequency had significant impacts on the dose–exposure relationship. Systemic concentration in patients with PsO was predicted to be 45% lower than in patients with AD from the same dose. When topically applied to the same percentage BSA, brepocitinib systemic exposures are expected to be comparable between adults and children. The systemic steady-state exposure after 3% once daily and twice daily (2 mg/cm2) cream applied to less than 50% BSA in patients with AD and PsO, respectively, maintains at least a threefold margin to non-clinical safety findings and clinical hematologic markers.ConclusionThe relationship between the amount of active drug applied and brepocitinib systemic CTrough, described by LMER, may inform the development strategy for dose optimization in the brepocitinib topical program.

Wu, Yunjiao; Allegaert, Karel; Flint, Robert B.; Goulooze, Sebastiaan C.; Välitalo, Pyry A. J.; de Hoog, Matthijs; Mulla, Hussain; Sherwin, Catherine M. T.; Simons, Sinno H. P.; Krekels, Elke H. J.; Knibbe, Catherijne A. J.; Völler, Swantje

doi: 10.1007/s11095-024-03677-3pmid: 38472610

AimsWhether and when glomerular filtration rate (GFR) in preterms catches up with term peers is unknown. This study aims to develop a GFR maturation model for (pre)term-born individuals from birth to 18 years of age. Secondarily, the function is applied to data of different renally excreted drugs.MethodsWe combined published inulin clearance values and serum creatinine (Scr) concentrations in (pre)term born individuals throughout childhood. Inulin clearance was assumed to be equal to GFR, and Scr to reflect creatinine synthesis rate/GFR. We developed a GFR function consisting of GFRbirth (GFR at birth), and an Emax model dependent on PNA (with GFRmax, PNA50 (PNA at which half of GFRmax\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${GFR}_{max}$$\end{document} is reached) and Hill coefficient). The final GFR model was applied to predict gentamicin, tobramycin and vancomycin concentrations.ResultIn the GFR model, GFRbirth varied with birthweight linearly while in the PNA-based Emax equation, GA was the best covariate for PNA50, and current weight for GFRmax. The final model showed that for a child born at 26 weeks GA, absolute GFR is 18%, 63%, 80%, 92% and 96% of the GFR of a child born at 40 weeks GA at 1 month, 6 months, 1 year, 3 years and 12 years, respectively. PopPK models with the GFR maturation equations predicted concentrations of renally cleared antibiotics across (pre)term-born neonates until 18 years well.ConclusionsGFR of preterm individuals catches up with term peers at around three years of age, implying reduced dosages of renally cleared drugs should be considered below this age.

Cohen, Joseph R.; Brych, Stephen R.; Prabhu, Siddharth; Bi, Vivian; Elbaradei, Ahmed; Tokuda, Joshua M.; Xiang, Cathie; Hokom, Martha; Cui, Xiaohong; Ly, Claudia; Amos, Nathan; Sun, Jilin; Calamba, Dominador; Herskovitz, Jonathan; Capili, Allyson;

Nakamura, Kohei; Kambayashi, Atsushi; Onoue, Satomi

doi: 10.1007/s11095-024-03669-3pmid: 38472609

PurposeThe purpose of this study was to develop a simulation model for the pharmacokinetics (PK) of drugs undergoing enterohepatic circulation (EHC) with consideration to the environment in the gastrointestinal tract in the fed state in humans. The investigation particularly focused on the necessity of compensating for the permeability rate constant in the reabsorption process in consideration of drug entrapment in bile micelles.MethodsMeloxicam and ezetimibe were used as model drugs. The extent of the entrapment of drugs inside bile micelles was evaluated using the solubility ratio of Fed State Simulated Intestinal Fluid version 2 (FeSSIF-V2) to Fasted State Simulated Intestinal Fluid version 2 (FaSSIF-V2). Prediction accuracy was evaluated using the Mean Absolute Percentage Error (MAPE) value, calculated from the observed and predicted oral PK profiles.ResultsThe solubilization of ezetimibe by bile micelles was clearly observed while that of meloxicam was not. Assuming that only drugs in the free fraction of micelles permeate through the intestinal membrane, PK simulation for ezetimibe was performed in both scenarios with and without compensation by the permeation rate constant. The MAPE value of Zetia® tablet, containing ezetimibe, was lower with compensation than without compensation. By contrast, Mobic® tablet, containing meloxicam, showed a relatively low MAPE value even without compensation.ConclusionFor drugs which undergo EHC and can be solubilized by bile micelles, compensating for the permeation rate constant in the reabsorption process based on the free fraction ratio appears an important factor in increasing the accuracy of PK profile prediction.

Gahane, Avinash Y.; Verma, Devesh Pratap; Sarkar, Swagata; Thakur, Ashwani K.

doi: 10.1007/s11095-024-03690-6pmid: 38519814

ObjectiveTo assess the pharmacokinetic profile, in-vivo toxicity, and efficacy of 9-Fluorenylmethoxycarbonyl-L-phenylalanine (Fmoc-F) as a potential antibacterial agent, with a focus on its suitability for clinical translation.MethodsAn RP-HPLC-based bio-analytical method was developed and qualified to quantify Fmoc-F levels in mouse plasma for pharmacokinetic analysis. Oral bioavailability was determined, and in-vivo toxicity was evaluated following intra-peritoneal administration. Efficacy was assessed by measuring the reduction in Staphylococcus aureus burden and survival rates in BALB/c mice.ResultsThe RP-HPLC method is highly sensitive, detecting as low as 0.8 µg mL-1 (~ 2 µM) of Fmoc-F in blood plasma. This study revealed that Fmoc-F has an oral bioavailability of 65 ± 18% and suitable pharmacokinetic profile. Further, we showed that intra-peritoneal administration of Fmoc-F is well tolerated by BALB/c mice and Fmoc-F treatment (100 mg/kg, i.p.) significantly reduces Staphylococcus aureus burden from visceral organs in BALB/c mice but falls short in enhancing survival rates at higher bacterial loads.ConclusionsThe study provides crucial insights into the pharmacokinetic and pharmacodynamic properties of Fmoc-F. The compound displayed favourable oral bioavailability and in-vivo tolerance. Its significant reduction of bacterial burden underscores its potential as a treatment for systemic infections. However, limited effectiveness for severe infections, short half-life, and inflammatory response at higher doses need to be addressed for its clinical application.

Li, Jingxi; Li, Xue; Wu, Keheng; Long, Sihui; Zhao, Youni; Jin, Xiong; Zhang, Mengjun; Wu, Xinyi; Huang, Zhijun; Zhou, Zhou; Liu, Jack; Liu, Bo

doi: 10.1007/s11095-024-03691-5pmid:

Brigitha, Leiah J.; Mondelaers, Veerle; Liu, Yiwei; Albertsen, Birgitte K.; Zalewska-Szewczyk, Beata; Rizzari, Carmelo; Kotecha, Rishi S.; Pieters, Rob; Huitema, Alwin D. R.; van der Sluis, Inge M.

doi: 10.1007/s11095-024-03693-3pmid:

Romagnoli, Alessia; Ferrara, Francesco; Langella, Roberto; Zovi, Andrea

doi: 10.1007/s11095-024-03685-3pmid: 38443632

BackgroundNowadays, healthcare systems are coping with the challenge of countering the exponential growth of healthcare costs worldwide, to support sustainability and to guarantee access to treatment for all patients.MethodsArtificial Intelligence (AI) is the technology able to perform human cognitive functions through the creation of algorithms. The value of AI in healthcare and its ability to address healthcare delivery issues has been a subject of discussion within the scientific community for several years.ResultsThe aim of this work is to provide an overview of the primary uses of AI in the healthcare system, to discuss its desirable future uses while shedding light on the major issues related to implications within international regulatory processes. In this manuscript, it will be described the main applications of AI in various aspects of health care, from clinical studies to ethical implications, focusing on the international regulatory framework in countries in which AI is used, to discuss and compare strengthens and weaknesses.ConclusionsThe challenges in regulatory processes to facilitate the integration of AI in healthcare are significant. However, overcoming them is essential to ensure that AI-based technologies are adopted safely and effectively.

Shen, Chaozhuang; Yang, Hongyi; Shao, Wenxin; Zheng, Liang; Zhang, Wei; Xie, Haitang; Jiang, Xuehua; Wang, Ling

doi: 10.1007/s11095-024-03680-8pmid: 38443631

BackgroundVenlafaxine (VEN) is a commonly utilized medication for alleviating depression and anxiety disorders. The presence of genetic polymorphisms gives rise to considerable variations in plasma concentrations across different phenotypes. This divergence in phenotypic responses leads to notable differences in both the efficacy and tolerance of the drug.PurposeA physiologically based pharmacokinetic (PBPK) model for VEN and its metabolite O-desmethylvenlafaxine (ODV) to predict the impact of CYP2D6 and CYP2C19 gene polymorphisms on VEN pharmacokinetics (PK).MethodsThe parent-metabolite PBPK models for VEN and ODV were developed using PK-Sim® and MoBi®. Leveraging prior research, derived and implemented CYP2D6 and CYP2C19 activity score (AS)-dependent metabolism to simulate exposure in the drug-gene interactions (DGIs) scenarios. The model’s performance was evaluated by comparing predicted and observed values of plasma concentration–time (PCT) curves and PK parameters values.ResultsIn the base models, 91.1%, 94.8%, and 94.6% of the predicted plasma concentrations for VEN, ODV, and VEN + ODV, respectively, fell within a twofold error range of the corresponding observed concentrations. For DGI scenarios, these values were 81.4% and 85% for VEN and ODV, respectively. Comparing CYP2D6 AS = 2 (normal metabolizers, NM) populations to AS = 0 (poor metabolizers, PM), 0.25, 0.5, 0.75, 1.0 (intermediate metabolizers, IM), 1.25, 1.5 (NM), and 3.0 (ultrarapid metabolizers, UM) populations in CYP2C19 AS = 2.0 group, the predicted DGI AUC0-96 h ratios for VEN were 3.65, 3.09, 2.60, 2.18, 1.84, 1.56, 1.34, 0.61, and for ODV, they were 0.17, 0.35, 0.51, 0.64, 0.75, 0.83, 0.90, 1.11, and the results were similar in other CYP2C19 groups. It should be noted that PK differences in CYP2C19 phenotypes were not similar across different CYP2D6 groups.ConclusionsIn clinical practice, the impact of genotyping on the in vivo disposition process of VEN should be considered to ensure the safety and efficacy of treatment.