A Study on the Multi-Compartment Linear Circulation Pharmacokinetic Model for the Targeting Drug Delivery System

By analyzing the observed phenomena and the data collected in the study, a multi-compartment linear circulation model for targeting drug delivery system was developed and the function formulas of the drug concentration-time in blood and target organ by computing were figured out. The drug concentration-time curve for target organ can be plotted with reference to the data of drug concentration in blood according to the model. The pharmacokinetic parameters of the drug in target organ could also be obtained. The practicability of the model was further checked by the curves of drug concentration-time in blood and target organ(liver) of liver-targeting nanoparticles in animal tests. Based on the liver drug concentration-time curves calculated by the function formula of the drug in target organ, the pharmacokinetic behavior of the drug in target organ(liver) was analyzed by statistical moment, and its pharmacokinetic parameters in liver were obtained. It is suggested that the (relative targeting index( can be used for quantitative evaluation of the targeting drug delivery systems.

Propofol Target-Controlled Infusion Modeling in Rabbits:Pharmacokinetic and Pharmacodynamic Analysis

This study aimed to establish a new propofol target-controlled infusion（TCI） model in animals so as to study the general anesthetic mechanism at multi-levels in vivo. Twenty Japanese white rabbits were enrolled and propofol（10 mg/kg） was administrated intravenously. Artery blood samples were collected at various time points after injection, and plasma concentrations of propofol were measured. Pharmacokinetic modeling was performed using Win Nonlin software. Propofol TCI within the acquired parameters integrated was conducted to achieve different anesthetic depths in rabbits, monitored by narcotrend. The pharmacodynamics was analyzed using a sigmoidal inhibitory maximal effect model for narcotrend index（NI） versus effect-site concentration. The results showed the pharmacokinetics of propofol in Japanese white rabbits was best described by a two-compartment model. The target plasma concentrations of propofol required at light anesthetic depth was 9.77±0.23 μg/m L, while 12.52±0.69 μg/m L at deep anesthetic depth. NI was 76.17±4.25 at light anesthetic depth, while 27.41±5.77 at deep anesthetic depth. The effect-site elimination rate constant（ke0） was 0.263/min, and the propofol dose required to achieve a 50% decrease in the NI value from baseline was 11.19 μg/m L（95% CI, 10.25–13.67）. Our results established a new propofol TCI animal model and proved the model controlled the anesthetic depth accurately and stably in rabbits. The study provides a powerful method for exploring general anesthetic mechanisms at different anesthetic depths in vivo.

Numerical Simulations of One-Directional Fractional Pharmacokinetics Model

In this paper,we present a three-compartment of pharmacokinetics model with irreversible rate constants.The compartment consists of arterial blood,tissues and venous blood.Fick’s principle and the law of mass action were used to develop the model based on the diffusion process.The model is modified into a fractional pharmacokinetics model with the sense of Caputo derivative.The existence and uniqueness of the model are investigated and the positivity of the model is established.The behaviour of the model is investigated by implementing numerical algorithms for the numerical solution of the system of fractional differential equations.MATLAB software is used to plot the graphs for illustrating the variation of drug concentration concerning time.Therefore,the numerical simulations of the model are presented for different values ofαwhich verified the theoretical analysis.Besides,we also observed the pattern of the simulations at the three-compartment of the model by using different values of initial conditions.

The Presence of Phases and the Inability of the Classical Compartment Models to Provide Pharmacokinetic Parameters of Physiological Significance for Lipophilic Drugs

The first biphasic open one-compartment pharmacokinetic model is described. Its analytical solutions to drug concentration were developed from parameters of an open two-compartment pharmacokinetic model. The model is used to explain the unusually large compartment volumes and apparent volumes of distribution of lipophilic drugs, as well as to identify which of the pharmacokinetic parameters of the classical compartment models are biologically relevant.

RESEARCH ON THE ESTIMATE OF SAFETY AND TOXICITY OF P-NITROPHENOL SODIUM WITHA PHYSIOLOGICALLY BASED PHARMACOKINETICS MODEL

The safety and toxicity of chemicals given first to animals and finally to humans are generally estimated with a method of safe coefficient, which is scientifically a way lack of grounds. To make a change of the old method, we designed a Physiologically Based Pharmacokinetics Medel for the estimate of safety and toxicity of chemicais. As an example,p-nitrophenol sodium (PNP-Na) is used in the research work. Studies of the PNP-Na pharmacokinetics in bodies of rat as well as humans are made, and possibilities of making use of the Model in the estimate of safety and toxicity of chemicals are discussed.

On the Origin of the Apparent Volume of Distribution and Its Significance in Pharmacokinetics

The apparent volume of distribution was defined for the first time as the phase volume that can hold the total amount of a substance at the measured phase substance concentration, in a system composed of two immiscible media that are in contact under conditions of constant phase volumes, at equilibrium. Its value is not affected by the total system solute mass and it only depends on the total system volume, the phase volumes and the affinity of the solute for the two phases in the system. Using this new concept of the apparent volume of distribution, we were able to demonstrate that under certain conditions compartment volumes in multi-compartment and multi-phasic pharmacokinetic models represent the actual physiological volumes of body fluids accessible by drugs. The classical pharmacokinetic models are now fully explained and can be used to provide accurate estimation of the pharmacokinetic parameters for hydrophilic drugs. In contrast, in the absence of tissue-plasma partition coefficients, lipophilic drugs that do not follow a one-compartment model are unlikely to be adequately described with classical multi-compartment pharmacokinetic models.

In vitro - in vivo - in silico approach in the development of inhaled drug products: Nanocrystal-based formulations with budesonide as a model drug

This study aims to understand the absorption patterns of three different kinds of inhaled formulations via in silico modeling using budesonide(BUD)as a model drug.The formulations investigated in this study are:(i)commercially available micronized BUD mixed with lactose(BUD-PT),(ii)BUD nanocrystal suspension(BUD-NC),(iii)BUD nanocrystals embedded hyaluronic acid microparticles(BUD-NEM).The deposition patterns of the three inhaled formulations in the rats’lungs were determined in vivo and in silico predicted,which were used as inputs in GastroPlus TM software to predict drug absorption following aerosolization of the tested formulations.BUD pharmacokinetics,estimated based on intravenous data in rats,was used to establish a drug-specific in silico absorption model.The BUD-specific in silico model revealed that drug pulmonary solubility and absorption rate constant were the key factors affecting pulmonary absorption of BUD-NC and BUD-NEM,respectively.In the case of BUD-PT,the in silico model revealed significant gastrointestinal absorption of BUD,which could be overlooked by traditional in vivo experimental observation.This study demonstrated that in vitro-in vivo-in silico approach was able to identify the key factors that influence the absorption of different inhaled formulations,which may facilitate the development of orally inhaled formulations with different drug release/absorption rates.

Model-based meta-analysis of pharmacokinetics of direct-acting antiviral agents,ledipasvir and sofosbuvir,in healthy subjects and chronic HCV patients

A tablet consisting of direct-acting antiviral agents,ledipasvir（a NS5 A protein inhibitor） and sofosbuvir（a NS5 B polymerase inhibitor）,is the first fixed-dose preparation used in the antiviral therapy of hepatitis C.A model-based meta-analysis of ledipasvir and GS331007,the primary metabolite of sofosbuvir,enabled the integration of pharmacokinetic（PK） information from separate clinical trials and the quantitative characterization of the population pharmacokinetics of these two drugs.A systematic publication search was conducted for the clinical studies of ledipasvir and sofosbuvir.A total of 401 arm-level aggregate concentrations of GS331007 and 188 concentrations of ledipasvir were used for PK modeling.A two-compartment disposition model was used for both ledipasvir and GS331007.Zero-order absorption was applied for ledipasvir PK modeling,and a combined zero- and first-order absorption was used for the modeling of GS331007.Absorption lag was observed in concentration-time profiles of both ledipasvir and GS331007.To aid the development of direct-acting antiviral drugs,our established PK models provided a basis for the further PK-viral kinetic studies of ledipasvir and sofosbuvir.

An Application of Prony’s Sum of Exponentials Method to Pharmacokinetic Data Analysis

We discuss the basic concept of compartmental modelling in pharmacokinetics and demonstrate that all the solutions admitted by multi-compartment models of classical pharmacokinetics are expressed as linear combinations of exponential functions of time.This lends itself to data analysis that depends on fitting exponential functions to finite size sets.A mathematical method developed a long time ago to deal with this type of problem is called Prony’s method.We discuss the usefulness of this method in pharmacokinetic modeling and apply it to a particular data set obtained for the drug mibefradil.In spite of the method’s power in dealing with well-behaved data sets,we indicate the existence of severe limitations since real concentration curves coming from pharmacokinetic data are seldom purely exponential.

Bile duct ligation differently regulates protein expressions of organic cation transporters in intestine,liver and kidney of rats through activation of farnesoid X receptor by cholate and bilirubin

Body is equipped with organic cation transporters(OCTs).These OCTs mediate drug transport and are also involved in some disease process.We aimed to investigate whether liver failure alters intestinal,hepatic and renal Oct expressions using bile duct ligation(BDL)rats.Pharmacokinetic analysis demonstrates that BDL decreases plasma metformin exposure,associated with decreased intestinal absorption and increased urinary excretion.Western blot shows that BDL significantly downregulates intestinal Oct2 and hepatic Oct1 but upregulates renal and hepatic Oct2.In vitro cell experiments show that chenodeoxycholic acid(CDCA),bilirubin and farnesoid X receptor(FXR)agonist GW4064 increase OCT2/Oct2 but decrease OCT1/Oct1,which are remarkably attenuated by glycine-β-muricholic acid and silencing FXR.Significantly lowered intestinal CDCA and increased plasma bilirubin levels contribute to different Octs regulation by BDL,which are confirmed using CDCA-treated and bilirubin-treated rats.A disease-based physiologically based pharmacokinetic model characterizing intestinal,hepatic and renal Octs was successfully developed to predict metformin pharmacokinetics in rats.In conclusion,BDL remarkably downregulates expressions of intestinal Oct2 and hepatic Oct1 protein while upregulates expressions of renal and hepatic Oct2 protein in rats,finally,decreasing plasma exposure and impairing hypoglycemic effects of metformin.BDL differently regulates Oct expressions via Fxr activation by CDCA and bilirubin.

Genome-scale metabolic modeling in antimicrobial pharmacology

The increasing antimicrobial resistance has seriously threatened human health worldwide over the last three decades.This severe medical crisis and the dwindling antibiotic discovery pipeline require the development of novel antimicrobial treatments to combat life-threatening infections caused by multidrug-resistant micro-bial pathogens.However,the detailed mechanisms of action,resistance,and toxicity of many antimicrobials remain uncertain,significantly hampering the development of novel antimicrobials.Genome-scale metabolic model(GSMM)has been increasingly employed to investigate microbial metabolism.In this review,we discuss the latest progress of GSMM in antimicrobial pharmacology,particularly in elucidating the complex interplays of multiple metabolic pathways involved in antimicrobial activity,resistance,and toxicity.We also highlight the emerging areas of GSMM applications in modeling non-metabolic cellular activities(e.g.,gene expression),identi-fication of potential drug targets,and integration with machine learning and pharmacokinetic/pharmacodynamic modeling.Overall,GSMM has significant potential in elucidating the critical role of metabolic changes in antimi-crobial pharmacology,providing mechanistic insights that will guide the optimization of dosing regimens for the treatment of antimicrobial-resistant infections.

An update on placental drug transport and its relevance to fetal drug exposure

Pregnant women are often complicated with diseases that require treatment with medication.Most drugs administered to pregnant women are off-label without the necessary dose,efficacy,and safety information.Knowledge concerning drug transfer across the placental barrier is essential for understanding fetal drug exposure and hence drug safety and efficacy to the fetus.Transporters expressed in the placenta,including adenosine triphosphate(ATP)-binding cassette efflux transporters and solute carrier uptake transporters,play important roles in determining drug transfer across the placental barrier,leading to fetal exposure to the drugs.In this review,we provide an update on placental drug transport,including in vitro cell/tissue,ex vivo human placenta perfusion,and in vivo animal studies that can be used to determine the expression and function of drug transporters in the placenta as well as placental drug transfer and fetal drug exposure.We also describe how the knowledge of placental drug transfer through passive diffusion or active transport can be combined with physiologically based pharmacokinetic modeling and simulation to predict systemic fetal drug exposure.Finally,we highlight knowledge gaps in studying placental drug transport and predicting fetal drug exposure and discuss future research directions to fill these gaps.