Pharmacodynamic Model Research Articles

Model-based comparison of subcutaneous versus sublingual apomorphine administration in the treatment of motor fluctuations in Parkinson’s disease

The objective of this study was to compare the effectiveness of subcutaneous (SC) and sublingual (SL) formulations of apomorphine for the treatment of motor fluctuations in Parkinson’s disease using a pharmacokinetics (PK)/pharmacodynamics (PD) modeling approach. The PK of SC and SL apomorphine are best described by a one-compartment model with first-order absorption and a two-compartment model with delayed absorption, respectively. The PK/PD model relating apomorphine plasma concentrations to the Unified Parkinson’s Disease Rating Scale (UPDRS) motor scores was described by a sigmoidal Emax model assuming effective concentration = drug concentration in an effect compartment. Apomorphine concentrations and UPDRS motor scores were simulated from the PK/PD models using 500 hypothetical subjects. UPDRS motor score change from baseline was evaluated using time to clinically relevant response, response duration, area under the curve, maximal response, and time to maximal response. Higher doses of each apomorphine formulation were associated with shorter time to response, longer response duration, and greater maximal response. Although the mean maximal responses to SC and SL apomorphine were comparable, the time to response was four times shorter (7 vs. 31 min) and time to maximal response was two times shorter (27 vs. 61 min) for 4 mg SC vs. 50 mg SL. Thus, faster onset of action was observed for the SC formulation compared to SL. These data may be useful for physicians when selecting “on demand” therapy for patients with Parkinson’s disease experiencing motor fluctuations.

Dosing optimization of rituximab for primary membranous nephropathy by population pharmacokinetic and pharmacodynamic study.

Primary membranous nephropathy (PMN) is the most common cause for adult nephrotic syndrome. Rituximab has demonstrated promising clinical efficacy by random controlled trials and the off-label use is widely adopted in PMN. However, the standard dosage is borrowed from B cell lymphoma treatment with far more antigens and is oversaturated for PMN treatment, accompanied with additional safety risk and unnecessary medical cost. More than 15% serious adverse events were observed under standard dosage and low dose therapies were explored recently. Dose optimization by clinical trials is extremely time- and cost-consuming and can be significantly accelerated with the aid of model-informed drug development. Here, we aim to establish the first population pharmacokinetic and pharmacodynamic (PPK/PD) model for rituximab in PMN to guide its dosage optimization. Rituximab pharmacokinetic and pharmacodynamic data from 41 PMN patients in a retrospective study under a newly proposed monthly mini-dose were used to construct quantitative dose-exposure-response relationship via mechanistic target-mediated drug disposition (TMDD) model followed by regression between the reduction of anti-PLA2R titer and time after the treatment. The final model, validated by goodness-of-fit plots, visual predictive checks and bootstrap, was used to recommend the optimized dosing regimen by simulations. The model was well validated for PK/PD prediction. The systemic clearance and half-life are 0.54L/h and 14.7 days, respectively. Simulation of a novel regimen (6 monthly doses of 100mg) indicated the comparable ability and superior duration time of CD20+ B cell depletion compared with standard dosage, while the cumulative dosage and safety risk was significantly decreased. We established the first PPK/PD model and provide evidence to support the dosage optimization based on monthly mini-dose. Our study can also efficiently accelerate dosage optimization of novel anti-CD20 antibodies in PMN and other indications.

Abstract 4503: Preclinical characterization of PRT7732: A highly potent, selective, and orally bioavailable targeted protein degrader of SMARCA2

Abstract SWI/SNF (BAF) complexes play an important role in controlling gene expression by remodeling chromatin. SMARCA2 (BRM) and SMARCA4 (BRG1) are the core catalytic subunits of the SWI/SNF complexes, containing an ATPase domain and a bromodomain. SMARCA4 protein expression is lost in some cancers due to loss-of-function (LOF) mutations and homozygous deletions, and SMARCA4-deleted cancer cells are highly dependent on its paralog gene SMARCA2 for their survival. Therefore, targeting SMARCA2 in SMARCA4-deficient cancers using selective SMARCA2 degraders induces synthetic lethality while sparing SMARCA4 wild type (WT) normal cells. We have recently identified a series of orally bioavailable SMARCA2 selective degraders that demonstrate robust efficacy in pre-clinical animal models with favorable pharmacokinetic properties and safety profiles. Our nomination candidate PRT7732 exhibits >1000x selectivity for SMARCA2 over SMARCA4 in cell-based assays, with DC50 values in cancer cell lines in the low nanomolar range. The PRT7732-induced SMARCA2 degradation was rescued by a proteasome inhibitor and neddylation inhibitor, indicating ubiquitin-proteasome dependent degradation. Furthermore, PRT7732 does not change levels of known CRBN ligand neo-substrates such as IKZF2/3, GSPT1 and SALL4. PRT7732 inhibits only SMARCA4-deficient cancer cell proliferation with IC50 values ranging from 5.0-50 nM, but not SMARCA4 WT cells in vitro. Oral administration of PRT7732 resulted in near-total degradation of SMARCA2 protein with complete selectivity over SMARCA4 protein in a SMARCA4 WT lung cancer model in mice, consistent with the SMARCA2 degradation kinetics-based pharmacodynamic prediction model. PRT7732 oral daily administration showed significant tumor growth inhibition of SMARCA4-deficient lung cancer xenograft models at well tolerated doses. The treated tumor tissues show robust SMARCA2 protein reduction for 24h post dosing. In summary, our orally bioavailable SMARCA2 degraders induce synthetic lethality in SMARCA4-deficient cancers in vitro and in vivo. Efforts to further evaluate these compounds in additional models and in combination with other agents are ongoing. Citation Format: Artem Shvartsbart, Koichi Ito, Joseph Rager, Michael Hulse, Anjana Agarwal, Komali Vykuntam, Jessica Burtell, Min Wang, Justin Kurian, Miles Cowart, Joy Cote, Nick Stahl, Monisha Sivakumar, Anthony Reichelderfer, Jack Carter, Alexander Grego, Andrew Moore, Neha Bhagwat, Ross Kuskovsky, Shanthi Ganesan, Stefan Ruepp, Tom Emm, Philip Pitis, Corey Basch, Klare Bersch, Yongchun Pan, Song Mei, Raul Leal, John Rose, Dani Roth, Chaoyi Xu, Ganfeng Cao, Kris Vaddi, Sang Hyun Lee, Sandy Geeganage, Andrew Combs, Peggy Scherle. Preclinical characterization of PRT7732: A highly potent, selective, and orally bioavailable targeted protein degrader of SMARCA2 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4503.

Use of multiple pharmacodynamic measures to deconstruct the Nix-TB regimen in a short-course murine model of tuberculosis.

A major challenge for tuberculosis (TB) drug development is to prioritize promising combination regimens from a large and growing number of possibilities. This includes demonstrating individual drug contributions to the activity of higher-order combinations. A BALB/c mouse TB infection model was used to evaluate the contributions of each drug and pairwise combination in the clinically relevant Nix-TB regimen [bedaquiline-pretomanid-linezolid (BPaL)] during the first 3 weeks of treatment at human equivalent doses. The rRNA synthesis (RS) ratio, an exploratory pharmacodynamic (PD) marker of ongoing Mycobacterium tuberculosis rRNA synthesis, together with solid culture CFU counts and liquid culture time to positivity (TTP) were used as PD markers of treatment response in lung tissue; and their time-course profiles were mathematically modeled using rate equations with pharmacologically interpretable parameters. Antimicrobial interactions were quantified using Bliss independence and Isserlis formulas. Subadditive (or antagonistic) and additive effects on bacillary load, assessed by CFU and TTP, were found for bedaquiline-pretomanid and linezolid-containing pairs, respectively. In contrast, subadditive and additive effects on rRNA synthesis were found for pretomanid-linezolid and bedaquiline-containing pairs, respectively. Additionally, accurate predictions of the response to BPaL for all three PD markers were made using only the single-drug and pairwise effects together with an assumption of negligible three-way drug interactions. The results represent an experimental and PD modeling approach aimed at reducing combinatorial complexity and improving the cost-effectiveness of in vivo systems for preclinical TB regimen development.

Two-way pharmacodynamic modeling of drug combinations and its application to pairs of repurposed Ebola and SARS-CoV-2 agents.

Existing pharmacodynamic (PD) mathematical models for drug combinations discriminate antagonistic, additive, multiplicative, and synergistic effects, but fail to consider how concentration-dependent drug interaction effects may vary across an entire dose-response matrix. We developed a two-way pharmacodynamic (TWPD) model to capture the PD of two-drug combinations. TWPD captures interactions between upstream and downstream drugs that act on different stages of viral replication, by quantifying upstream drug efficacy and concentration-dependent effects on downstream drug pharmacodynamic parameters. We applied TWPD to previously published in vitro drug matrixes for repurposed potential anti-Ebola and anti-SARS-CoV-2 drug pairs. Depending on the drug pairing, the model recapitulated combined efficacies as or more accurately than existing models and can be used to infer efficacy at untested drug concentrations. TWPD fits the data slightly better in one direction for all drug pairs, meaning that we can tentatively infer the upstream drug. Based on its high accuracy, TWPD could be used in concert with PK models to estimate the therapeutic effects of drug pairs in vivo.

Establishment of a pharmacokinetics and pharmacodynamics model of Schisandra lignans against hippocampal neurotransmitters in AD rats based on microdi-alysis liquid chromatography-mass spectrometry.

Objective: Our previous studies substantiated that the biological activity of Schisandra chinensis lignans during the treatment of Alzheimer's disease (AD) was mediated by neurotransmitter levels, and 15 of its active components were identified. However, the pharmacokinetic and pharmacodynamic relationship of Schisandra chinensis lignans has been less studied. The objective of this study was to investigate the relationship between the pharmacokinetics and pharmacodynamics of Schisandra chinensis lignans in the treatment of AD, and to establish a pharmacokinetic-pharmacodynamic (PK-PD) model. Methods and Results: Herein, we established a microdialysis-ultra performance liquid chromatography-triple quadruple mass spectrometry (MD-LC-TQ-MS) technique that could simultaneously and continuously collect and quantitatively analyze the active compounds and neurotransmitters related to the therapeutic effects of Schisandra chinensis in awake AD rats. Eight lignans were detected in the hippocampus, and a PK-PD model was established. The fitted curves highlighted a temporal lag between the maximum drug concentration and the peak drug effect. Following treatment, the levels of four neurotransmitters tended to converge with those observed in the sham operation group. Conclusion: By establishing a comprehensive concentration-time-effect relationship for Schisandra chinensis lignans in AD treatment, our study provides novel insights into the in vivo effects of these lignans in AD rats.

Pharmacokinetic and Pharmacodynamic Modeling Analysis of Delpazolid (LCB01-0371) in Adult Patients with Pulmonary Tuberculosis.

Delpazolid (LCB01-0371) is a novel oxazolidinone derivative with a good safety profile for treating gram-positive pathogenic infections such as Mycobacterium abscessus, a highly pathogenic drug-resistant Mycobacterium. In this study, we evaluated the pharmacokinetics (PK) and pharmacodynamics (PD) of delpazolid after 14 days of multiple oral administration, using data from adult patients with pulmonary tuberculosis. 800 mg once a day, 400 mg twice a day, 800 mg twice a day, and 1200 mg once a day delpazolid for 14 days were tested in 63 patients with pulmonary tuberculosis. For PK blood collection, inpatient and outpatient scheduling were separately implemented. Plasma concentrations of delpazolid were measured at visits 2, 4, 6, and 8 in outpatients, and four sparse blood samples were measured in inpatients. PD models were sequentially fitted using individual PK parameter estimates obtained from PK compartmental models. For PK modeling, 180 plasma concentrations of delpazolid from 56 patients were included. A two-compartment mixed first- and zero-order absorption model best described the time course of plasma concentration. For the PD model, 448 bacterial titer data from 60 patients were used. The time course of bacterial titers (log10 CFU/mL) was described by a model that consists of the growth and killing rate of bacteria with the sigmoid Emax model. The PK-PD simulation suggested that the bacterial titers are the lowest on the 800 mg bid regimen among the four, consistent with observed data, as all regimens substantially decrease. In the dose-response relationship, the effectiveness of delpazolid was suggested.

Programmable intratumoral drug delivery to breast cancer using wireless bioelectronic device with electrochemical actuation

ABSTRACT Objective Breast cancer is a global health concern that demands attention. In our contribution to addressing this disease, our study focuses on investigating a wireless micro-device for intratumoral drug delivery, utilizing electrochemical actuation. Microdevices have emerged as a promising approach in this field due to their ability to enable controlled injections in various applications. Methods Our study is conducted within a computational framework, employing models that simulate the behavior of the microdevice and drug discharge based on the principles of the ideal gas law. Furthermore, the distribution of the drug within the tissue is simulated, considering both diffusion and convection mechanisms. To predict the therapeutic response, a pharmacodynamic model is utilized, considering the chemotherapeutic effects and cell proliferation. Results The findings demonstrate that an effective current of 3 mA, along with an initial gas volume equal to the drug volume in the microdevice, optimizes drug delivery. Microdevices with multiple injection capabilities exhibit enhanced therapeutic efficacy, effectively suppressing cell proliferation. Additionally, tumors with lower microvascular density experience higher drug concentrations in the extracellular space, resulting in significant cell death in hypoxic regions. Conclusions Achieving an efficient therapeutic response involves considering both the characteristics of the tumor microenvironment and the frequency of injections within a specific time frame.

Design and selection of drug properties to increase the public health impact of next-generation seasonal malaria chemoprevention: a modelling study.

Seasonal malaria chemoprevention (SMC) is recommended for disease control in settings with moderate to high Plasmodium falciparum transmission and currently depends on the administration of sulfadoxine-pyrimethamine plus amodiaquine. However, poor regimen adherence and the increased frequency of parasite mutations conferring sulfadoxine-pyrimethamine resistance might threaten the effectiveness of SMC. Guidance is needed to de-risk the development of drug compounds for malaria prevention. We aimed to provide guidance for the early prioritisation of new and alternative SMC drugs and their target product profiles. In this modelling study, we combined an individual-based malaria transmission model that has explicit parasite growth with drug pharmacokinetic and pharmacodynamic models. We modelled SMC drug attributes for several possible modes of action, linked to their potential public health impact. Global sensitivity analyses identified trade-offs between drug elimination half-life, maximum parasite killing effect, and SMC coverage, and optimisation identified minimum requirements to maximise malaria burden reductions. Model predictions show that preventing infection for the entire period between SMC cycles is more important than drug curative efficacy for clinical disease effectiveness outcomes, but similarly important for impact on prevalence. When children younger than 5 years receive four SMC cycles with high levels of coverage (ie, 69% of children receiving all cycles), drug candidates require a duration of protection half-life higher than 23 days (elimination half-life >10 days) to achieve reductions higher than 75% in clinical incidence and severe disease (measured over the intervention period in the target population, compared with no intervention across a range of modelled scenarios). High coverage is crucial to achieve these targets, requiring more than 60% of children to receive all SMC cycles and more than 90% of children to receive at least one cycle regardless of the protection duration of the drug. Although efficacy is crucial for malaria prevalence reductions, chemoprevention development should select drug candidates for their duration of protection to maximise burden reductions, with the duration half-life determining cycle timing. Explicitly designing or selecting drug properties to increase community uptake is paramount. Bill & Melinda Gates Foundation and the Swiss National Science Foundation.

Population pharmacokinetics, enzyme occupancy, and pharmacodynamic modeling of soticlestat in patients with developmental and epileptic encephalopathies.

Soticlestat (TAK-935) is a first-in-class, selective inhibitor of cholesterol 24-hydroxylase (CH24H) under phase III development for the treatment of the developmental and epileptic encephalopathies (DEEs), Dravet syndrome (DS), and Lennox-Gastaut syndrome (LGS). A previous model characterized the pharmacokinetics (PKs), CH24H enzyme occupancy (EO), and pharmacodynamics (PDs) of soticlestat in healthy volunteers. The present study extended this original model for patients with DEEs and investigated sources of variability. Model-based simulations were carried out to optimize dosing strategies for use in clinical trials. Data from eight phase I and II trials of healthy volunteers or patients with DEEs receiving oral soticlestat 15-1350 mg were included, encompassing 218 individuals for population PK (PopPK) analyses and 306 individuals for PK/PD analyses. Dosing strategies were identified through model-based simulations. The final mixed-effect PopPK/EO/PD model consisted of a two-compartment PK model and an effect-site compartment in the PK/EO model; soticlestat concentrations at the effect site were linked to 24S-hydroxycholesterol plasma concentrations using a semimechanistic inhibitory indirect response model. Covariates were included to account for sources of variability. Pediatric dosing strategies were developed for four body weight bands (10 to <15, 15 to <30, 30 to <45, and 45-100 kg) to account for covariate effects by body weight. The final PopPK and PK/EO/PD models accurately described PK, EO, and PD profiles of soticlestat in healthy volunteers and patients with DEEs. Covariate analyses and model-based simulations facilitated optimization of phase III trial dosing strategies for patients with DS or LGS.

Asia-Inclusive Global Development of Enpatoran: Results of an Ethno-Bridging Study, Intrinsic/Extrinsic Factor Assessments and Disease Trajectory Modeling to Inform Design of a Phase II Multiregional Clinical Trial.

Enpatoran is a novel, highly selective, and potent dual toll-like receptor (TLR)7 and TLR8 inhibitor currently under development for the treatment of autoimmune disorders including systemic lupus erythematosus (SLE), cutaneous lupus erythematosus (CLE), and myositis. The ongoing phase II study (WILLOW; NCT05162586) is evaluating enpatoran for 24 weeks in patients with active SLE or CLE and is currently recruiting. To support development of WILLOW as an Asia-inclusive multiregional clinical trial (MRCT) according to International Conference on Harmonisation E5 and E17 principles, we have evaluated ethnic sensitivity to enpatoran based on clinical pharmacokinetic (PK), pharmacodynamic (PD), and safety data from an ethno-bridging study (NCT04880213), supplemented by relevant quantitative PK, PD, and disease trajectory modeling (DTM) results, and drug metabolism/disease knowledge. A single-center, open-label, sequential dose group study in White and Japanese subjects matched by body weight, height, and sex demonstrated comparable PK and PD properties for enpatoran in Asian vs. non-Asian (White and other) subjects across single 100, 200, and 300 mg orally administered doses. DTM suggested no significant differences in SLE disease trajectory for Asian vs. non-Asian individuals. Aldehyde oxidase (AOX) is considered to be a key contributor to enpatoran metabolism, and a literature review indicated no relevant ethnic differences in AOX function based on in vitro and clinical PK data from marketed drugs metabolized by AOX, supporting the conclusion of low ethnic sensitivity for enpatoran. Taken together, the inclusion of Asian patients in MRCTs including WILLOW was informed based on a Totality of Evidence approach.

Estimation of trajectory of protective efficacy in infectious disease prevention trials using recurrent event times.

In studies of infectious disease prevention, the level of protective efficacy of medicinal products such as vaccines and prophylactic drugs tends to vary over time. Many products require administration of multiple doses at scheduled times, as opposed to one-off or continual intervention. Accurate information on the trajectory of the level of protective efficacy over time facilitates informed clinical recommendations and implementation strategies, for example, with respect to the timing of administration of the doses. Based on concepts from pharmacokinetic and pharmacodynamic modeling, we propose a non-linear function for modeling the trajectory after each dose. The cumulative effect of multiple doses of the products is captured by an additive series of the function. The model has the advantages of parsimony and interpretability, while remaining flexible in capturing features of the trajectories. We incorporate this series into the Andersen-Gill model for analysis of recurrent event time data and compare it with alternative parametric and non-parametric functions. We use data on clinical malaria disease episodes from a trial of four doses of an anti-malarial drug combination for chemoprevention to illustrate, and evaluate the performance of the methods using simulation. The proposed method out-performed the alternatives in the analysis of real data in terms of Akaike and Bayesian Information Criterion. It also accurately captured the features of the protective efficacy trajectory such as the area under curve in simulations. The proposed method has strong potential to enhance the evaluation of disease prevention measures and improve their implementation strategies.

Pharmacokinetic-Pharmacodynamic Modelling in Hemophilia A: Relating Thrombin and Plasmin Generation to Factor VIII Activity After Administration of a VWF/FVIII Concentrate.

Hemophilia A patients are treated with factor (F) VIII prophylactically to prevent bleeding. In general, dosage and frequency are based on pharmacokinetic measurements. Ideally, an alternative dose adjustment can be based on the hemostatic potential, measured with a thrombin generation assay (TGA), like the Nijmegen hemostasis assay. The objective of this study was toinvestigate the predicted performance of a previously developed pharmacokinetic-pharmacodynamic model for FVIII replacement therapy, relating FVIII dose and FVIII activity levels with thrombin and plasmin generation parameters. Pharmacokinetic and pharmacodynamic measurements were obtained from 29 severe hemophilia A patients treated with pdVWF/FVIII concentrate (Haemate P®). The predictive performance of the previously developed pharmacokinetic-pharmacodynamic model was evaluated using nonlinear mixed-effects modeling (NONMEM). When predictions of FVIII activity or TGA parameters were inadequate [median prediction error (MPE) > 20%], a new model was developed. The original pharmacokinetic model underestimated clearance and was refined based on a two-compartment model. The pharmacodynamic model displays no bias in the observed normalized thrombin peak height and normalized thrombin potential (MPE of 6.83% and 7.46%). After re-estimating pharmacodynamic parameters, EC50 and Emax values were relatively comparable between the original model and this group. Prediction of normalized plasmin peak height was inaccurate (MPE 58.9%). Our predictive performance displayed adequate thrombin pharmacodynamic predictions of the original model, but a new pharmacokinetic model was required. The pharmacodynamic model is not factor specific and applicable to multiple factor concentrates. A prospective study is needed to validate the impact of the FVIII dosing pharmacodynamic model on bleeding reduction in patients.

Predicting pharmacodynamic effects through early drug discovery with artificial intelligence-physiologically based pharmacokinetic (AI-PBPK) modelling.

A mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model links the concentration-time profile of a drug with its therapeutic effects based on the underlying biological or physiological processes. Clinical endpoints play a pivotal role in drug development. Despite the substantial time and effort invested in screening drugs for favourable pharmacokinetic (PK) properties, they may not consistently yield optimal clinical outcomes. Furthermore, in the virtual compound screening phase, researchers cannot observe clinical outcomes in humans directly. These uncertainties prolong the process of drug development. As incorporation of Artificial Intelligence (AI) into the physiologically based pharmacokinetic/pharmacodynamic (PBPK) model can assist in forecasting pharmacodynamic (PD) effects within the human body, we introduce a methodology for utilizing the AI-PBPK platform to predict the PK and PD outcomes of target compounds in the early drug discovery stage. In this integrated platform, machine learning is used to predict the parameters for the model, and the mechanism-based PD model is used to predict the PD outcome through the PK results. This platform enables researchers to align the PK profile of a drug with desired PD effects at the early drug discovery stage. Case studies are presented to assess and compare five potassium-competitive acid blocker (P-CAB) compounds, after calibration and verification using vonoprazan and revaprazan.

Pharmacokinetic/pharmacodynamic modeling of cortical dopamine concentrations after quetiapine lipid core nanocapsules administration to schizophrenia phenotyped rats.

Schizophrenia (SCZ) response to pharmacological treatment is highly variable. Quetiapine (QTP) administered as QTP lipid core nanocapsules (QLNC) has been shown to modulate drug delivery to the brain of SCZ phenotyped rats (SPR). In the present study, we describe the brain concentration-effect relationship after administrations of QTP as a solution or QLNC to SPR and naïve animals. A semimechanistic pharmacokinetic (PK) model describing free QTP concentrations in the brain was linked to a pharmacodynamic (PD) model to correlate the drug kinetics to changes in dopamine (DA) medial prefrontal cortex extracellular concentrations determined by intracerebral microdialysis. Different structural models were investigated to fit DA concentrations after QTP dosing, and the final model describes the synthesis, release, and elimination of DA using a pool compartment. The results show that nanoparticles increase QTP brain concentrations and DA peak after drug dosing to SPR. To the best of our knowledge, this is the first study that combines microdialysis and PK/PD modeling in a neurodevelopmental model of SCZ to investigate how a nanocarrier can modulate drug PK and PD, contributing to the development of new treatment strategies for SCZ.

Population Pharmacodynamic Models of Risperidone on PANSS Total Scores and Prolactin Levels in Schizophrenia.

Currently, research predominantly focuses on evaluating clinical effects at specific time points while neglecting underlying patterns within the treatment process. This study aims to analyze the dynamic alterations in PANSS total scores and prolactin levels in patients with schizophrenia treated with risperidone, along with the influencing covariates. Using data from an 8-week randomized, double-blind, multicenter clinical trial, a population pharmacodynamic model was established for the PANSS total scores of and prolactin levels in patients treated with risperidone. The base model employed was the Emax model. Covariate selection was conducted using a stepwise forward inclusion and backward elimination approach. A total of 144 patients were included in this analysis, with 807 PANSS total scores and 531 prolactin concentration values. The PANSS total scores of the patients treated with risperidone decreased over time, fitting a proportionally parameterized sigmoid Emax model with covariates including baseline score, course of the disease, gender, plasma calcium ions, and lactate dehydrogenase levels. The increase in prolactin levels conformed to the ordinary Emax model, with covariates encompassing course of the disease, gender, weight, red blood cell count, and triglyceride levels. The impacts of the baseline scores and the course of the disease on the reduction of the PANSS scores, as well as the influence of gender on the elevation of prolactin levels, each exceeded 20%. This study provides valuable quantitative data regarding PANSS total scores and prolactin levels among patients undergoing risperidone treatment across various physiological conditions.

Is Gender an Important Factor in the Precision Medicine Approach to Levocetirizine?

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.

Using Pharmacokinetic-Pharmacodynamic Modeling to Study the Main Active Substances of the Anticancer Effect in Mice from Panax ginseng-Ophiopogon japonicus.

Ginseng Radix et Rhizoma Rubra (Panax ginseng C.A. Mey, Hongshen, in Chinese) and Ophiopogonis Radix (Ophiopogon japonicus (L.f) Ker-Gawl., Maidong, in Chinese) are traditional Chinese herbal pairs, which were clinically employed to enhance the immune system of cancer patients. This study employed the pharmacokinetic and pharmacodynamic (PK-PD) spectrum-effect association model to investigate the antitumor active substances of P. ginseng and O. japonicus (PG-OJ). The metabolic processes of 20 major bioactive components were analyzed using Ultra-Performance Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (UPLC-MS/MS) in the lung tissue of tumor-bearing mice treated with PG-OJ. The ELISA method was employed to detect the levels of TGF-β1, TNF-α, and IFN-γ in the lung tissue of mice at various time points, and to analyze their changes after drug administration. The results showed that all components presented a multiple peaks absorption pattern within 0.083 to 24 h post-drug administration. The tumor inhibition rate of tumor and repair rate of IFN-γ, TNF-α, and TGF-β1 all increased, indicating a positive therapeutic effect of PG-OJ on A549 tumor-bearing mice. Finally, a PK-PD model based on the GBDT algorithm was developed for the first time to speculate that Methylophiopogonanone A, Methylophiopogonanone B, Ginsenoside Rb1, and Notoginsenoside R1 are the main active components in PG-OJ for lung cancer treatment.

Assessment of Quinidine-Induced Torsades de Pointes Risks Using a Whole-Body Physiologically Based Pharmacokinetic Model Linked to Cardiac Ionic Current Inhibition.

The lethality of torsades de pointes (TdP) by drugs is one of main reasons that some drugs were withdrawn from the market. In order to assess drug-induced TdP risks, a model of cardiac ionic current suppression in human ventricular myocytes (ToR-ORd model), combined with the maximum effective free therapeutic plasma concentration or the maximum effective free therapeutic myocyte concentration was often used, with the latter proved to be more relevant and more accurate. We aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) model, incorporated with a human cardiomyocyte pharmacodynamic (PD) model, to provide a comprehensive assessment of drug-induced TdP risks in normal and specific scenarios. Quinidine served as an example to validate the PBPK-PD model via predicting plasma quinidine concentrations and quinidine-induced changes in QT interval (ΔQTc). The predicted plasma quinidine concentrations and ΔQTc values following oral administration or intravenous administration of quinidine were comparable to clinic observations. Visual predictive checks showed that most of the observed plasma concentrations and ΔQTc values fell within the 5th and 95th percentiles of simulations. The validated PBPK-PD model was further applied to assess the TdP risks using frequencies of early afterdepolarization and long-QT syndrome occurrence in 4 scenarios, such as therapeutic dose, supra-therapeutic dose, alkalosis, and hyperkalemia in 200 human subjects. In conclusion, the developed PBPK-PD model may be applied to predict the quinidine pharmacokinetics and quinidine-induced TdP risks in healthy subjects, but also simulate quinidine-induced TdP risks under disease conditions, such as hypokalemia and alkalosis.

Resveratrol Improves Mechanical Allodynia and Inflammation: Focus on Sex Differences in Rats

Inflammatory pain is a complex phenomenon arising from various etiological factors, resulting in diverse symptoms that can lead to persistent debilitations. The management of chronic inflammatory pain predominantly involves non-steroidal anti-inflammatory drugs, despite their association with adverse cardiovascular and gastrointestinal effects. Consequently, the pursuit of innovative therapeutic avenues for pain intervention is of paramount importance. Resveratrol, renowned for its anti-inflammatory and anti-oxidative attributes, emerges as a promising candidate in this regard. In this work, we assessed the potential of resveratrol to elicit anti-nociceptive and anti-inflammatory effects in two distinct models of peripheral inflammation: carrageenan and complete Freund’s adjuvant, conducted in male and female rats. In rats treated with carrageen, resveratrol administration yielded an elevation in mechanical thresholds in both sexes, concurrently inducing a reduction in paw diameter specifically among male rats. Furthermore, the administration of resveratrol in complete Freund’s adjuvant–treated rats led to an analogous increase of mechanical thresholds, a response observed in both male and female subjects. These compelling outcomes underscore the analgesic and anti-inflammatory attributes inherent to resveratrol, thereby offering a fresh insight into the intricate realm of sex-related variances in two well-characterized pharmacodynamics models of inflammatory pain.Graphical