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BACKGROUND AND PURPOSES: It is unclear whether the parent Saxagliptin (SAX) in vivo is the same as that in vitro, which is twice that of 5-hydroxy Saxagliptin (5-OH SAX). This study is to construct a Pharmacokinetic-Pharmacodynamic (PK-PD) link model to evaluate the genuine relationship between the concentration of parent SAX in vivo and the effect. METHODS: First, we established a reliable Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS/MS) method and DPP-4 inhibition ratio determination method. Then, the T2DM rats were randomly divided into four groups, intravenous injection of 5-OH SAX (0.5 mg/kg) and saline group, intragastric administration of SAX (10 mg/kg) and Sodium carboxymethyl cellulose (CMC-Na) group. Plasma samples were collected at different time points for subsequent testing. Finally, we used the measured concentrations and inhibition ratios to construct a PK-PD link model for 5-OH SAX and parent SAX. RESULTS: A two-compartment with additive model showed the pharmacokinetic process of SAX and 5-OH SAX, the concentration-effect relationship was represented by a sigmoidal Emax model and sigmoidal Emax with E0 model for SAX and 5-OH SAX, respectively. Fitting parameters showed SAX was rapidly absorbed after administration (Tmax=0.11 h, t1/2, ka=0.07 h), widely distributed in the body (V ≈ 20 L/kg), plasma exposure reached 3282.06 ng*h/mL, and the elimination half-life was 6.13 h. The maximum plasma dipeptidyl peptidase IV (DPP-4) inhibition ratio of parent SAX was 71.47%. According to the final fitting parameter EC50, EC50, 5-OH SAX=0.46EC50, SAX(parent), it was believed that the inhibitory effect of 5-OH SAX was about half of the parent SAX, which is consistent with the literature. CONCLUSIONS: The PK-PD link model of the parent SAX established in this study can predict its pharmacokinetic process in T2DM rats and the strength of the inhibitory effect of DPP-4 based on non-clinical data.

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Microplastics (MPs) waste is widespread globally in water systems. The opportunistic human pathogen Pseudomonas aeruginosa can cause serious acute and chronic infections that are notoriously difficult to treat. Ciprofloxacin (CIP) is broadly applied as an anti-P. aeruginosa drug. A growing evidence reveals that antibiotic-resistance genes-carrying Pseudomonas aeruginosa were detected on MPs forming plastisphere due to their adsorbability along with high occurrence of CIP in water environments. The MPs-niched CIP-resistant P. aeruginosa has been likely to emerge as an unignorable public health issue. Here, we offered a novel approach to assess the development of CIP-resistant P. aeruginosa under MPs-antibiotic coexistence at a water region scale. By combing the adsorption isotherm models used to estimate CIP condensation around MPs and a pharmacokinetic/pharmacodynamic-based microbial population dynamic model, we predicted the P. aeruginosa development on CIP-adsorbed MPs in waters. Our assessment revealed a high antibiotic resistance in the P. aeruginosa populations (∼50 %) with a wider range of waterborne total cell counts (∼10-2-104 cfu mL-1) among water regions in that the resistance proportion was primarily determined by CIP pollution level and relative abundance of various polymer type of MPs. We implicate that water region-specific MPs were highly likely to provide media for P. aeruginosa propagation. Our results highlight the importance of antibiotic-resistant pathogen colonization-emerging environmental medium interactions when addressing global threat from MPs pollution, in the context of MPs-antibiotics co-contamination assessment and for the continued provision of water system management.

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Background: Wendan Decoction (WDD) is a six-herb Chinese medicine recipe that was first mentioned in about 652 AD. It is frequently used to treat hyperlipidemic patients' clinical complaints. According to reports, oxidative stress has a significant role in hyperlipidemia. Purpose: There has not yet been a thorough pharmacokinetic-pharmacodynamic (PK-PD) examination of the clinical efficacy of WDD in the context of hyperlipemia-related oxidative stress. Therefore, the goal of this research is to explore the antioxidant essence of WDD by developing a PK-PD model, ordering to assure its implication in treating hyperlipidemia in medical practice. Methods: The model rats of foodborne hyperlipidemia were established by feeding with high-fat feed, and the lipid-lowering effect of WDD was explored. The plasma drug concentration of rats at different doses were measured by UPL-MS/MS technology, and PK parameters were calculated using Phoenix WinNonlin 8.1 software. The level of lipid peroxide (LPO) in plasma at different time points was measured by enzyme labeling instrument. Finally, the PK-PD model was established by using Phoenix WinNonlin 8.1 software, to explore the lipid-lowering effect of WDD and the relation between the dynamic changes of chemical components and antioxidant effect. Results: The findings suggested that, WDD can reduce the levels of triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) in plasma, and high-density lipoprotein cholesterol (HDL-C) was related to the dosage. Between the peak drug levels and the WDD's maximal therapeutic response, there existed a hysteresis. WDD's effect-concentration curves displayed a counterclockwise delaying loop. Alternatively, among the ten components of WDD, hesperetin, quercetin, naringenin and tangeretin might exert more significant effects in regulating the LPO levels in hyperlipidemic rats. Conclusion: This study can be helpful for other investigators to study the lipid-lowering effect of WDD.

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AIMS: C-reactive protein (CRP) is used to determine the effect of antibiotic treatment on sepsis in neonates/infants. We aimed to develop pharmacokinetic-pharmacodynamic (PKPD) model of meropenem and CRP in neonates/infants and evaluate its predictive performance of CRP dynamics. METHODS: Data from neonates/infants treated with meropenem in 3 previous studies were analysed. To the previously developed meropenem PK models, the addition of turnover, transit or effect compartment, delay differential equation PD models of CRP as a function of meropenem concentration or its cumulative area under the curve (AUC) were evaluated. The percentage of neonates/infants (P0.1 , P0.2 ) in whom the ratio of the fifth day CRP to its peak value was predicted with an error of <0.1 (<0.2) was calculated. RESULTS: A total of 60 meropenem treatment episodes (median [range] gestational age 27.6 [22.6-40.9] weeks, postnatal age 13 [2-89] days) with a total of 351 CRP concentrations (maximum value 65.5 [13-358.4] mg/L) were included. Turnover model of CRP as a function of meropenem cumulative AUC provided the best fit and included CRP at the start of treatment, use of prior antibiotics, study and causative agent Staphylococcus aureus or enterococci as covariates. Using meropenem population predictions and data available at 0, 24, 48, 72 h after the start of treatment, P0.1 (P0.2 ) was 36.4, 36.4, 60.6 and 66.7% (70.0, 66.7, 72.7 and 78.7%), respectively. CONCLUSION: The developed PKPD model of meropenem and CRP as a function of meropenem cumulative AUC incorporating several patient characteristics predicts CRP dynamics with an error of <0.2 in most neonates/infants.

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We present a novel Pharmacokinetic/Pharmacodynamic (PK/PD) model for the induction phase of anesthesia, incorporating the ψ-Caputo fractional derivative. By employing the Picard iterative process, we derive a solution for a nonhomogeneous ψ-Caputo fractional system to characterize the dynamical behavior of the drugs distribution within a patient's body during the anesthesia process. To explore the dynamics of the fractional anesthesia model, we perform numerical analysis on solutions involving various functions of ψ and fractional orders. All numerical simulations are conducted using the MATLAB computing environment. Our results suggest that the ψ functions and the fractional order of differentiation have an important role in the modeling of individual-specific characteristics, taking into account the complex interplay between drug concentration and its effect on the human body. This innovative model serves to advance the understanding of personalized drug responses during anesthesia, paving the way for more precise and tailored approaches to anesthetic drug administration.

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The study aimed to explore the pharmacokinetic and pharmacodynamic alterations of the active components of Shenkang injection (i.e. hydroxy saffron yellow pigment A [HSYA], tanshinol, rheum emodin, and astragaloside IV) in rats with chronic renal failure (CRF), and establish a pharmacokinetic-pharmacodynamic model (PK-PD model) in order to provide a scientific and theoretical basis for the rational clinical use of Shenkang injection. Sprague-Dawley (SD) rats were randomly divided into a normal group, model group, and Shenkang injection group. A rat model of CRF was induced by adenine gavage and then followed by drug administration via tail vein injection. Orbital blood was collected at different timepoints and the blood concentrations of the four active components were measured by UHPLC-Q-Orbitrap HRMS. Serum levels of creatinine (Scr), urea nitrogen (BUN), and uric acid (UA) were determined using an automatic biochemical analyzer. A PK-PD model was established, and DAS 3.2.6 software was used for model fitting as well as statistical analysis. TGF-ß1 was utilized to induce normal rat kidney cells to construct a renal fibrosis model to investigate the protective effect of the pharmacological components on renal fibrosis. The pharmacokinetic analysis of hydroxy saffron yellow pigment A, tanshinol, rheum emodin, and astragaloside IV based on UHPLC-Q-Orbitrap HRMS was stable. The linear regression equations for the four active components were as follows: Y = 0.031X + 0.0091 (R2  = 0.9986) for hydroxy saffron yellow pigment A, Y = 0.0389X + 0.164 (R2  = 0.9979) for tanshinol, Y = 0.0257X + 0.0146 (R2  = 0.9973) for rheum emodin, and Y = 0.0763X + 0.0139 (R2  = 0.9993) for astragaloside IV, which indicated good linear relationships. The methodological investigation was stable, with the interday and intraday precision RSD <10%. Meanwhile, the recoveries ranged between 90% and 120%, in accordance with the requirements for in vivo analysis of drugs. Compared with the model group, the levels of Scr, BUN, and UA were significantly decreased after 20 min in the Shenkang injection group (p < 0.01). The PK-PD model showed that the four active components in the Shenkang injection group could fit well with the three effect measures (i.e. Scr, BUN, and UA), with the measured values similar to the predicted values. The cell model of renal fibrosis showed that the connective tissue growth factor and FN1 protein expression levels were significantly lower in the Shenkang injection group than those in the model group, and the cell fibrosis was improved. The established method for in vivo analysis of Shenkang injection was highly specific, with good separation of the components and simple operation. The total statistical moment could well integrate the pharmacokinetic parameters of the four active components. After treatment with Shenkang injection, all indexes in the administered group improved and showed significant inhibition of renal cell fibrosis in vitro. This study could provide scientific reference ideas for the clinical rational use of traditional Chinese medicine.

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SARS-CoV-2 vaccinations were initially shown to substantially reduce risk of severe disease and death. However, pharmacokinetic (PK) waning and rapid viral evolution degrade neutralizing antibody (nAb) binding titers, causing loss of vaccinal protection. Additionally, there is inter-individual heterogeneity in the strength and durability of the vaccinal nAb response. Here, we propose a personalized booster strategy as a potential solution to this problem. Our model-based approach incorporates inter-individual heterogeneity in nAb response to primary SARS-CoV-2 vaccination into a pharmacokinetic/pharmacodynamic (PK/PD) model to project population-level heterogeneity in vaccinal protection. We further examine the impact of evolutionary immune evasion on vaccinal protection over time based on variant fold reduction in nAb potency. Our findings suggest viral evolution will decrease the effectiveness of vaccinal protection against severe disease, especially for individuals with a less durable immune response. More frequent boosting may restore vaccinal protection for individuals with a weaker immune response. Our analysis shows that the ECLIA RBD binding assay strongly predicts neutralization of sequence-matched pseudoviruses. This may be a useful tool for rapidly assessing individual immune protection. Our work suggests vaccinal protection against severe disease is not assured and identifies a potential path forward for reducing risk to immunologically vulnerable individuals.

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Ahead of Print article withdrawn by publisher.

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Laboratory experiments suggest that rapid cycling of antibiotics during the course of treatment could successfully counter resistance evolution. Drugs involving collateral sensitivity could be particularly suitable for such therapies. However, the environmental conditions in vivo differ from those in vitro. One key difference is that drugs can be switched abruptly in the laboratory, while in the patient, pharmacokinetic processes lead to changing antibiotic concentrations including periods of dose overlaps from consecutive administrations. During such overlap phases, drug-drug interactions may affect the evolutionary dynamics. To address the gap between the laboratory and potential clinical applications, we set up two models for comparison-a 'laboratory model' and a pharmacokinetic-pharmacodynamic 'patient model'. The analysis shows that in the laboratory, the most rapid cycling suppresses the bacterial population always at least as well as other regimens. For patient treatment, however, a little slower cycling can sometimes be preferable if the pharmacodynamic curve is steep or if drugs interact antagonistically. When resistance is absent prior to treatment, collateral sensitivity brings no substantial benefit unless the cell division rate is low and drug cycling slow. By contrast, drug-drug interactions strongly influence the treatment efficiency of rapid regimens, demonstrating their importance for the optimal choice of drug pairs.

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Survival is one of the most important endpoints in cancer therapy, and parametric survival analysis could comprehensively reveal the overall result of disease progression, drug efficacy, toxicity as well as their interactions. In this study we investigated the efficacy and toxicity of dexamethasone (DEX) combined with gemcitabine (GEM) in pancreatic cancer xenograft. Nude mice bearing SW1990 pancreatic cancer cells derived tumor were treated with DEX (4 mg/kg, i.g.) and GEM (15 mg/kg, i.v.) alone or in combination repeatedly (QD, Q3D, Q7D) until the death of animal or the end of study. Tumor volumes and net body weight (NBW) were assessed every other day. Taking NBW as a systemic safety indicator, an integrated pharmacokinetic/pharmacodynamic (PK/PD) model was developed to quantitatively describe the impact of tumor size and systemic safety on animal survival. The PK/PD models with time course data for tumor size and NBW were established, respectively, in a sequential manner; a parametric time-to-event (TTE) model was also developed based on the longitudinal PK/PD models to describe the survival results of the SW1990 tumor-bearing mice. These models were evaluated and externally validated. Only the mice with good tumor growth inhibition and relatively stable NBW had an improved survival result after DEX and GEM combination therapy, and the simulations based on the parametric TTE model showed that NBW played more important role in animals' survival compared with tumor size. The established model in this study demonstrates that tumor size was not always the most important reason for cancer-related death, and parametric survival analysis together with safety issues was also important in the evaluation of oncology therapies in preclinical studies.

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Computational models of disease progression have been constructed for a myriad of pathologies. Typically, the conceptual implementation for pathology-related in-silico intervention studies has been ad-hoc and similar in design to experimental studies. We introduce a multi-scale interventional design (MID) framework toward two key goals: tracking of disease dynamics from within-body to patient to population scale; and tracking impact(s) of interventions across these same spatial scales. Our MID framework prioritizes investigation of impact on individual patients within virtual pre-clinical trials, instead of replicating the design of experimental studies. We apply a MID framework to develop, organize, and analyze a cohort of virtual patients for the study of tuberculosis (TB) as an example disease. For this study, we use HostSim: our next-generation whole patient-scale computational model of individuals infected with Mycobacterium tuberculosis. HostSim captures infection within lungs by tracking multiple granulomas, together with dynamics occurring with blood and lymph node compartments, the compartments involved during pulmonary TB. We extend HostSim to include a simple drug intervention as an example of our approach and use our MID framework to quantify the impact of treatment at cellular and tissue (granuloma), patient (lungs, lymph nodes and blood), and population scales. Sensitivity analyses allow us to determine which features of virtual patients are the strongest predictors of intervention efficacy across scales. These insights allow us to identify patient-heterogeneous mechanisms that drive outcomes across scales.

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Drug-induced torsades de pointes (TdP) risks are responsible for the withdrawal of many drugs from the market. Nowadays, assessments of drug-induced TdP risks are mainly based on maximum effective free therapeutic plasma concentration (EFTPCmax) and cardiac ionic current inhibitions using the human ventricular myocytes model (Tor-ORd model). Myocytes are targets of drug-induced TdP. The TdP risks may be directly linked to myocyte drug concentrations. We aimed to develop a semi-physiologically based pharmacokinetic (Semi-PBPK) model linked to cardiac ionic current inhibition (pharmacodynamics, PD) (Semi-PBPK-PD) to simultaneously predict myocyte drug concentrations and their TdP risks in humans. Alterations in action potential duration (ΔAPD90) were simulated using the Tor-ORd model and ionic current inhibition parameters based on myocyte or plasma drug concentrations. The predicted ΔAPD90 values were translated into in vivo alterations in QT interval(ΔQTc) induced by moxifloxacin, dofetilide, or sotalol. Myocyte drug concentrations of moxifloxacin, dofetilide, and sotalol gave better predictions of ΔQTc than plasma. Following validating the developed semi-PBPK-PD model, TdP risks of 37 drugs were assessed using ΔAPD90 and early afterdepolarization occurrence, which were estimated based on 10 × EFTPCmax and 10 × EFTMCmax (maximum effective free therapeutic myocyte concentration). 10 × EFTMCmax gave more sensitive and accurate predictions of pro-arrhythmic cardiotoxicity and the predicted TdP risks were also closer to clinic practice than 10 × EFTPCmax. In conclusion, pharmacokinetics and TdP risks of 37 drugs were successfully predicted using the semi-PBPK-PD model. Myocyte drug concentrations gave better predictions of ΔQTc and TdP risks than plasma.

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Myelosuppression is a dose-limiting toxicity of uracil-tegafur (UFT), which contains uracil and the 5­fluorouracil prodrug tegafur, and inhibits the continuation of chemotherapy, causing treatment failure. A proper dosing strategy to avoid severe myelosuppression-induced discontinuation of chemotherapy is required.Plasma drug concentrations were determined in rats after single oral UFT administration of 15, 30, or 60 mg/kg. Blood cell counts were also measured after oral UFT administration for 5 days. Pharmacokinetic-toxicodynamic (PK-TD) modelling and simulation were performed to describe the time-course alterations in the blood cell counts.Severe neutropenia was observed in rats treated with 60 mg/kg UFT on day 7. A significant decrease in neutrophil counts from baseline levels prior to UFT administration was observed on day 3, whereas leukocyte and lymphocyte counts decreased on day 7. The semi-physiological PK-TD model successfully captured alterations in neutrophil counts after UFT administration, whereas the model could not well describe the platelet, leukocyte, and lymphocyte counts, possibly due to the absence of severe thrombocytopenia, leukocytopenia, and lymphocytopenia, respectively.Neutrophils are sensitive markers for estimating the grade of haematological toxicity of UFT, and a PK-TD model might be an attractive tool for quantitatively evaluating the onset and degree of myelosuppression.

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OBJECTIVE: Acetaminophen (APAP) is widely used as an analgesic for postoperative pain relief. However, the pharmacokinetic-pharmacodynamic (PK-PD) properties of intravenous APAP administration remain unclear. We developed a PK-PD model in adult volunteers. METHODS: APAP (1 g) was intravenously administered to 15 healthy volunteers. The pain equivalent current (PEC) was then measured using the pulse current, corresponding to the quantitative value of pain perception. The PK model was developed using a 2-compartment model, and the PD model was developed using a linear model and an effect compartment model. RESULTS: APAP plasma concentration peaked just administration, whereas PEC significantly increased at 90 minutes and lasted through the experimental period (300 minutes). APAP plasma concentrations and PEC were processed for use in the PK-PD model. The developed PK-PD model delineates the analgesic effect profile, which peaked at 188 minutes and lasted until 327 minutes. CONCLUSION: We developed the PK/PD model for APAP administered intravenously. The analgesic effect can be expected ∼90 minutes after administration and to last >5 hours. It is suggested that APAP be administered ∼90 minutes prior to the onset of anticipated postoperative pain.

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Polymyxin-based combination therapy is commonly used to treat carbapenem-resistant Acinetobacter baumannii (CRAB) infections. In the present study, the bactericidal effect of polymyxin B and minocycline combination was tested in three CRAB strains containing blaOXA-23 by the checkerboard assay and in vitro dynamic pharmacokinetics/pharmacodynamics (PK/PD) model. The combination showed synergistic or partial synergistic effect (fractional inhibitory concentration index ≤0.56) on the tested strains in checkboard assays. The antibacterial activity was enhanced in the combination group compared with either monotherapy in in vitro PK/PD model. The combination regimen (simultaneous infusion of 0.75 mg/kg polymyxin B and 100 mg minocycline via 2 h infusion) reduced bacterial colony counts by 0.9-3.5 log10 colony forming units per milliliter (CFU/mL) compared with either drug alone at 24 h. In conclusion, 0.75 mg/kg polymyxin B combined with 100 mg minocycline via 2 h infusion could be a promising treatment option for CRAB bloodstream infections.

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PURPOSE: Peptide-conjugated phosphorodiamidate morpholino oligomers (PPMOs) have shown promise in treating Duchenne muscular dystrophy (DMD). We evaluated a semi-mechanistic pharmacokinetic (PK) and pharmacodynamic (PD) model to capture the relationship between plasma and muscle tissue exposure/response in mdx mice treated by mouse surrogate PPMO. METHODS: A single or repeated (every 4 weeks for 20 weeks) intravenous PPMO dose was administered to mdx mice (n = 6/timepoint). A PK/PD model was built to characterize data via sequential modeling. A 2-compartment model was used to describe plasma PK. A simultaneous tissue PK/PD model was subsequently developed: 2-compartment model to describe muscle PK; linked to an indirect response model describing stimulation of synthesis of skipped transcript, which was in turn linked to stimulation of synthesis of dystrophin protein expression. RESULTS: Model performance assessment via goodness-of-fit plots, visual predictive checks, and accurate parameter estimation indicated robust fits of plasma PK and muscle PK/PD data. The model estimated a PPMO tissue half-life of 5 days-a useful parameter in determining the longevity of PPMOs in tissue and their limited accumulation after multiple doses. Additionally, the model successfully described dystrophin expression after single dosing and associated protein accumulation after multiple dosing (increasing ~ twofold accumulation from the first to last dose). CONCLUSIONS: This first PK/PD model of a PPMO in a DMD disease model will help characterize and predict the time course of PK/PD biomarkers in mdx mice. Furthermore, the model framework can be used to develop clinical PK/PD models and can be extended to other exon-skipping therapies and species.

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Sorafenib was suggested to cause drug-drug interaction (DDI) with the common anticoagulant, warfarin based on published studies. The inhibition on CYP2C9 enzyme was thought to be the mechanism, but further studies are warranted. Thus, a mechanistic PBPK/PD model for warfarin enantiomers was developed to predict DDI potential with sorafenib, aiming at providing reference for the rational use of both drugs. PBPK models of warfarin enantiomers were constructed by Simcyp software. A mechanistic PK/PD model was built in NONMEM software. PBPK model of sorafenib was fitted via a top-down method. The final PBPK/PD model of warfarin enantiomers was verified and validated by different dosing regimens, ethnicities and genetic polymorphisms, and used to perform DDI simulations between warfarin racemate and sorafenib among general populations and sub-populations with various CYP2C9 and VKORC1 genotypes. Results suggested low DDI risk between warfarin and sorafenib for general populations. Potentially serious consequence was seen for those carrying both CYP2C9 ∗2 and ∗3 and VKORC1 A/A genotypes. This PBPK/PD modeling approach for warfarin enantiomers enabled DDI evaluation with sorafenib. Close monitoring and warfarin dosage adjustment were recommended for patients carrying mutant genotypes. The novel model could be applied to investigate other drugs that may interact with warfarin.

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Human-derived in vitro models can provide high-throughput efficacy and toxicity data without a species gap in drug development. Challenges are still encountered regarding the full utilisation of massive data in clinical settings. The lack of translated methods hinders the reliable prediction of clinical outcomes. Therefore, in this study, in silico models were proposed to tackle these obstacles from in vitro to in vivo translation, and the current major cell culture methods were introduced, such as human-induced pluripotent stem cells (hiPSCs), 3D cells, organoids, and microphysiological systems (MPS). Furthermore, the role and applications of several in silico models were summarised, including the physiologically based pharmacokinetic model (PBPK), pharmacokinetic/pharmacodynamic model (PK/PD), quantitative systems pharmacology model (QSP), and virtual clinical trials. These credible translation cases will provide templates for subsequent in vitro to in vivo translation. We believe that synergising high-quality in vitro data with existing models can better guide drug development and clinical use.

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