Ocular pharmacokinetic models of clonidine-3H hydrochloride

A single topical instillation of clonidine-3H HCl solution (0.2%) was administered to the rabbit eye (30 microliter) in order to study the drug's ocular pharmacokinetics. Seven different tissues and plasma were excised and assayed for drug over 180 min. By 45-60 min pseudoequilibrium is reached for the cornea, iris/ciliary body, and aqueous humor. Thereafter, drug levels in these tissues decline in parallel. The data are fit separately to a physiological model and a classical diffusion model for which seven ocular tissue compartments and a plasma reservoir are constructed for each model. Clearance terms and distribution equilibrium coefficients are determined from the tissue level data and used as parameters in fitting the mass balance differential equations representing the physiological model. The model parameters can also be fit to a 0.4% single dose. In a separate experiment, a topical infusion technique was designed to provide a constant rate input to the cornea until an apparent steady state was reached in aqueous humor at 55 min. Aqueous humor levels were assayed for clonidine over the infusion and postinfusion periods. The physiological model parameters are fit to the topical infusion data and show good agreement between the predicted and experimental data. The classical model is too complex to fit the data to integrated exponential equations primarily because the method of residuals is inadequate in determining a sufficient set of initial estimates. This is overcome by dividing the eight-compartment model into seven fragmental models, each representing one to five compartments. A stepwise procedure is developed in which initial estimates are obtained for each separate fragmental model and refined. The refined parameter values can then be used as initial estimates for the complex model. Differential equations for the complex model are fit simultaneously to tissue levels representing each compartment. By observation, the classical model fit the data more closely than the physiological model. Statistical moment theory is also applied to the topical infusion data to determine ocular pharmacokinetic parameters for clonidine. The calculated values are: corneal absorption rate constant ka, 0.00139 min-1, aqueous humor elimination rate constant k10, 0.0658 min-1; mean residence time MRTd, 35.6 min; apparent steady-state volume of distribution Vss, 0.530 ml; and ocular clearance Qe, 14.9 microliter/min. The fraction absorbed from the single instillation is estimated as 0.0163.     

生理药代动力学模型在药物基因组学中的应用

生理药代动力学模型作为药代动力学的新兴工具,可以有效用于表征各种情况下由基因组学多态性导致的体内药动学变化.本文介绍生理药代动力学模型在药物基因组学研究中的基本原理并讨论其适用性,从I相代谢酶、II相代谢酶和转运体的基因多态性角度总结了模型的应用情况,以期了解药物基因组学的新型研究手段,为促进药物临床应用和提高药物研发...     

Advanced pharmacokinetic models based on organ clearance, circulatory, and fractal concepts

Three advanced models of pharmacokinetics are described. In the first class are physiologically based pharmacokinetic models based on in vitro data on transport and metabolism. The information is translated as transporter and enzyme activities and their attendant heterogeneities into liver and intestine models. Second are circulatory models based on transit time distribution and plasma concentration time curves. The third are fractal models for nonhomogeneous systems and non-Fickian processes are presented. The usefulness of these pharmacokinetic models, with examples, is compared.     

Differential pharmacokinetic drug-drug interaction potential of eletriptan between oral and subcutaneous routes

Abstract

1. Pharmacokinetic drug-drug interaction (DDI) data is important from a label claim either in combination drug usage or in polypharmacy situation.

2. Eletriptan undergoes first pass related metabolism through CYP3A4 enzyme to form pharmacologically active N-desmethyl metabolite.

3. Differential DDI interaction of the concomitant oral dosing of ketoconazole (20.1?mg/kg), a CYP3A4 inhibitor, with oral (4.2?mg/kg) or subcutaneous dose (2.1?mg/kg) of eletriptan was evaluated in male Sprague Dawley rats. Serial pharmacokinetic samples were collected and simultaneously analysed for eletriptan/N-desmethyl eletriptan using validated assay. Non-compartmentally derived pharmacokinetic parameters for various treatments were analysed statistically.

4. After oral eletriptan in presence of ketoconazole, C_max (40 vs. 32?ng/mL alone) and AUC_inf (81 vs. 24?ng.h/mL alone) of eletriptan increased; the formation of N-desmethyl eletriptan decreased (C_max=1.1?ng/mL, 3.9%) with ketoconazole as compared to without treatment (C_max=3.7?ng/mL, 11.2%). After subcutaneous eletriptan in presence of ketoconazole, there was no change in C_max (153 vs.152?ng/mL) or AUC_inf (267 vs. 266?ng.h/mL) of eletriptan. Formation of N-desmethyl eletriptan after the subcutaneous dose was determined at few intermittent time points with/without ketoconazole.

5. Preclinical data support differential DDI of eletriptan when dosed oral vs. subcutaneous, which need to be evaluated in a clinical setting.     

阿托伐他汀生理药动学模型的建立

目的:建立阿托伐他汀在健康人群中的生理药动学模型,预测其在人体内的组织分布及特征,为优化阿托伐他汀的治疗方案提供依据。方法:文献中获取关于阿托伐他汀理化参数及体外酶促动力学参数及数值。结合药物理化参数得到组织-血浆分配平衡系数(K_p),应用GastroPlus软件,建立阿托伐他汀的生理药动学模型, 验证模型有效性, 预测各器官组织中阿托伐他汀的经时变化,并运用模型预测阿托伐他汀在儿童及老年人群体内各器官组织中药物的经时变化,为个体化用药提供依据。结果:经验证,模型的有效性良好。阿托伐他汀在14个组织室均有分布,其中在血液、皮肤、肺中分布较高,C_max分别为6.04,1.70,1.32 ng·ml^-1;在脂肪和脑中分布较低,C_max分别为0.31,0.33 ng·ml^-1。儿童及老年人群体各器官组织阿托伐他汀的经时变化模型预测发现,儿童血液、皮肤、肺分布较高,C_max分别为12.49,3.52,2.73 ng·ml^-1;脑分布最低,C_max为0.69 ng·ml^-1;老年血液、皮肤、肺分布较高,C_max分别为8.97,2.53,1.96 ng·ml^-1;肌肉分布最低,C_max为0.63 ng·ml^-1。结论:儿童及老年体内阿托伐他汀不同组织分布的C_max为青年健康人群的两倍,显示年龄影响阿托伐他汀在体内的分布,儿童和老年人应用阿托伐他汀,存在较高发生不良反应的风险,应根据生理生化指标调整剂量,避免不良反应的发生。     

生理药代动力学模型及其在药物相互作用研究中的应用

生理药代动力学模型(PBPK model)在毒理学和药理学领域得到越来越多的关注和应用,如用于药物-药物相互作用(DDI)等研究.DDI会影响药物的安全性、有效性、药物标识及选择药物联用的合理性,其在药物研发和上市后研究中已成为临床药理研究的重要组成部分.基于模型的分析方法被证明是评价DDI作用的有力工具.本文对PBPK模型的特征及其在DDI研究中的应用现状进行阐述.     

Characterizing uncertainty and variability in physiologically based pharmacokinetic models: state of the science and needs for research and implementation.

Physiologically based pharmacokinetic (PBPK) models are used in mode-of-action based risk and safety assessments to estimate internal dosimetry in animals and humans. When used in risk assessment, these models can provide a basis for extrapolating between species, doses, and exposure routes or for justifying nondefault values for uncertainty factors. Characterization of uncertainty and variability is increasingly recognized as important for risk assessment; this represents a continuing challenge for both PBPK modelers and users. Current practices show significant progress in specifying deterministic biological models and nondeterministic (often statistical) models, estimating parameters using diverse data sets from multiple sources, using them to make predictions, and characterizing uncertainty and variability of model parameters and predictions. The International Workshop on Uncertainty and Variability in PBPK Models, held 31 Oct-2 Nov 2006, identified the state-of-the-science, needed changes in practice and implementation, and research priorities. For the short term, these include (1) multidisciplinary teams to integrate deterministic and nondeterministic/statistical models; (2) broader use of sensitivity analyses, including for structural and global (rather than local) parameter changes; and (3) enhanced transparency and reproducibility through improved documentation of model structure(s), parameter values, sensitivity and other analyses, and supporting, discrepant, or excluded data. Longer-term needs include (1) theoretical and practical methodological improvements for nondeterministic/statistical modeling; (2) better methods for evaluating alternative model structures; (3) peer-reviewed databases of parameters and covariates, and their distributions; (4) expanded coverage of PBPK models across chemicals with different properties; and (5) training and reference materials, such as cases studies, bibliographies/glossaries, model repositories, and enhanced software. The multidisciplinary dialogue initiated by this Workshop will foster the collaboration, research, data collection, and training necessary to make characterizing uncertainty and variability a standard practice in PBPK modeling and risk assessment.     

Utility of real time breath analysis and physiologically based pharmacokinetic modeling to determine the percutaneous absorption of methyl chloroform in rats and humans.

Due to the large surface area of the skin, percutaneous absorption has the potential to contribute significantly to the total bioavailability of some compounds. Breath elimination data, acquired in real-time using a novel MS/MS system, was assessed using a PBPK model with a dermal compartment to determine the percutaneous absorption of methyl chloroform (MC) in rats and humans from exposures to MC in non-occluded soil or occluded water matrices. Rats were exposed to MC using a dermal exposure cell attached to a clipper-shaved area on their back. The soil exposure cell was covered with a charcoal patch to capture volatilized MC and prevent contamination of exhaled breath. This technique allowed the determination of MC dermal absorption kinetics under realistic, non-occluded conditions. Human exposures were conducted by immersing one hand in 0.1% MC in water, or 0.75% MC in soil. The dermal PBPK model was used to estimate skin permeability (Kp) based on the fit of the exhaled breath data. Rat skin K(p)s were estimated to be 0.25 and 0.15 cm/h for MC in water and soil matrices, respectively. In comparison, human permeability coefficients for water matrix exposures were 40-fold lower at 0.006 cm/h. Due to evaporation and differences in apparent Kp, nearly twice as much MC was absorbed from the occluded water (61.3%) compared to the non-occluded soil (32.5%) system in the rat. The PBPK model was used to simulate dermal exposures to MC-contaminated water and soil in children and adults using worst-case EPA default assumptions. The simulations indicate that neither children nor adults will absorb significant amounts of MC from non-occluded exposures, independent of the length of exposure. The results from these simulations reiterate the importance of conducting dermal exposures under realistic conditions.     

一种纳米粒细胞动力学的生理药动学模型的建立与解析

目的：以纳米粒与细胞的相互作用过程为基础,建立一种纳米粒细胞动力学的生理药动学模型。方法：以受体介导的纳米粒细胞摄取过程为基础,建立描述纳米粒细胞摄取和细胞清除的动力学模型,对纳米粒的细胞摄取和清除数据进行拟合,获取模型参数,并将拟合结果与实验数据进行对比。结果：建立了一种包含纳米粒隔室和纳米粒清除隔室的动力学模型,并且获得了细胞内纳米粒含量和纳米粒消除量的数值计算方法。通过对白蛋白纳米粒的细胞摄取数据和细胞清除数据的拟合,获取了模型参数,并且模型的拟合结果与实验测定结果相符。结论：该模型能较好地对纳米粒的细胞摄取-细胞清除的动力学进行模拟。同房室模型相比,该模型含有与细胞生理因素有关的模型参数,因此该模型在对纳米粒多细胞动力学研究中具有较大的优势。     

Physiologically based pharmacokinetic modelling to predict exposure differences in healthy volunteers and subjects with renal impairment: Ceftazidime case study

Ceftazidime is a widely used β‐lactam antibiotic and almost entirely excreted via glomerular filtration in kidney. The objective of this analysis was to assess the ability of physiologically based pharmacokinetic (PBPK) model to predict ceftazidime exposure in healthy volunteers and subjects with renal impairment. A full PBPK model of ceftazidime was developed using physiochemical properties and clinical data. The total clearance of 115 mL/min and renal clearance of 100 mL/min were obtained from ceftazidime package insert. Healthy and chronic kidney disease (CKD) populations were applied for sampling of virtual subjects. The established PBPK model predicted mean plasma AUC_inf were 138.5 ± 19.6, 230.7 ± 22.2, 369.3 ± 53.1 and 561.8 ± 92.4 h   µg/mL in healthy, mild, moderate and severe renal impairment subjects, respectively, after administration of 1 g ceftazidime intravenous bolus dose. The predicted values were in close agreement with the weighted mean of the five reported clinical studies. The exposure was slightly under predicted in subjects with severely impaired renal function, but still within 1.5‐fold range. The concentration‐time profiles of ceftazidime were also well captured in healthy volunteers and subjects with renal impairment. The developed PBPK model along with systems pharmacokinetics (PK) (renal impaired populations) well predicted the ceftazidime exposure. PBPK models verified with clinical study in healthy volunteers could be potentially applied to predict PK and recommend dose adjustment for CKD patients.     

Development of a Korean‐specific virtual population for physiologically based pharmacokinetic modelling and simulation

Physiologically based pharmacokinetic (PBPK) modelling and simulation is a useful tool in predicting the PK profiles of a drug, assessing the effects of covariates such as demographics, ethnicity, genetic polymorphisms and disease status on the PK, and evaluating the potential of drug–drug interactions. We developed a Korean‐specific virtual population for the SimCYP® Simulator (version 15 used) and evaluated the population's predictive performance using six substrate drugs (midazolam, S‐warfarin, metoprolol, omeprazole, lorazepam and rosuvastatin) of five major drug metabolizing enzymes (DMEs) and two transporters. Forty‐three parameters including the proportion of phenotypes in DMEs and transporters were incorporated into the Korean‐specific virtual population. The simulated concentration–time profiles in Koreans were overlapped with most of the observed concentrations for the selected substrate drugs with a < 2‐fold difference in clearance. Furthermore, we found some drug models within the SimCYP® library can be improved, e.g., the minor allele frequency of ABCG2 and the fraction metabolized by UGT2B15 should be incorporated for rosuvastatin and lorazepam, respectively. The Korean‐specific population can be used to evaluate the impact of ethnicity on the PKs of a drug, particularly in various stages of drug development.     

Physiologically based pharmacokinetic modelling of oxycodone drug–drug interactions

Oxycodone is an opioid analgesic with several pharmacologically active metabolites and relatively narrow therapeutic index. Cytochrome P450 (CYP) 3A4 and CYP2D6 play major roles in the metabolism of oxycodone and its metabolites. Thus, inhibition and induction of these enzymes may result in substantial changes in the exposure of both oxycodone and its metabolites. In this study, a physiologically based pharmacokinetic (PBPK) model was built using GastroPlus™ software for oxycodone, two primary metabolites (noroxycodone, oxymorphone) and one secondary metabolite (noroxymorphone). The model was built based on literature and in house in vitro and in silico data. The model was refined and verified against literature clinical data after oxycodone administration in the absence of drug–drug interactions (DDI). The model was further challenged with simulations of oxycodone DDI with CYP3A4 inhibitors ketoconazole and itraconazole, CYP3A4 inducer rifampicin and CYP2D6 inhibitor quinidine. The magnitude of DDI (AUC ratio) was predicted within 1.5-fold error for oxycodone, within 1.8-fold and 1.3–4.5-fold error for the primary metabolites noroxycodone and oxymorphone, respectively, and within 1.4–4.5-fold error for the secondary metabolite noroxymorphone, when compared to the mean observed AUC ratios. This work demonstrated the capability of PBPK model to simulate DDI of the administered compounds and the formed metabolites of both DDI victim and perpetrator. However, the predictions for the formed metabolites tend to be associated with higher uncertainty than the predictions for the administered compound. The oxycodone model provides a tool for forecasting oxycodone DDI with other CYP3A4 and CYP2D6 DDI perpetrators that may be co-administered with oxycodone.     

Predicting the oral absorption of a poorly soluble,poorly permeable weak base using biorelevant dissolution and transfer model tests coupled with a physiologically based pharmacokinetic model

通过构建瑞舒伐他汀空腹状态下的生理药动学(physiologically based pharmacokinetic model,PBPK)模型,预测其餐后状态下的吸收,并探究其可能的食物效应机制,为服用他汀类药物的高脂血症患者提出合理的饮食建议,提高BCSⅢ类他汀类药物的药物吸收。

根据文献和已有研究获得瑞舒伐他汀建模的理化参数、生物药剂学参数以及药动学参数,利用GastroPlus^TM软件建立瑞舒伐他汀餐后给药的PBPK预测模型,并结合实测的血药浓度数据验证模型,判断是否可以准确预测出瑞舒伐他汀餐后的药物吸收结果,并进行参数敏感性分析。

通过构建瑞舒伐他汀PBPK模型预测其餐后吸收,计算得到模型预测数据与实测数据的平均折叠误差和绝对平均折叠误差<2,结合模型验证的拟合相关系数表明拟合效果较好,同时参数敏感性分析提示高热量饮食、药物的油水分配系数(LogD)和渗透性对瑞舒伐他汀的吸收影响较大。

所建立的模型能够较好地预测瑞舒伐他汀餐后状态下的吸收,基于参数敏感性分析结果,为服用BCSⅢ类他汀类药物的高脂血症患者提出合理的饮食建议,包括适当增加饮食中蛋白质的比重、减少脂肪和水溶性膳食纤维的占比等,可提高BCSⅢ类他汀类药物的肠道吸收。

     

Physiologically based pharmacokinetic modeling to predict complex drug–drug interactions: a case study of AZD2327 and its metabolite,competitive and time‐dependent CYP3A inhibitors

4‐{(R)‐(3‐Aminophenyl)[4‐(4‐fluorobenzyl)‐piperazin‐1‐yl]methyl}‐N,N‐diethylbenzamide (AZD2327) is a highly potent and selective agonist of the δ ‐opioid receptor. AZD2327 and N‐deethylated AZD2327 (M1) are substrates of cytochrome P450 3A (CYP3A4) and comprise a complex multiple inhibitory system that causes competitive and time‐dependent inhibition of CYP3A4. The aim of the current work was to develop a physiologically based pharmacokinetic (PBPK) model to predict quantitatively the magnitude of CYP3A4 mediated drug–drug interaction with midazolam as the substrate. Integrating in silico, in vitro and in vivo PK data, a PBPK model was successfully developed to simulate the clinical accumulation of AZD2327 and its primary metabolite. The inhibition of CYP3A4 by AZD2327, using midazolam as a probe drug, was reasonably predicted. The predicted maximum concentration (C_max) and area under the concentration–time curve (AUC) for midazolam were increased by 1.75 and 2.45‐fold, respectively, after multiple dosing of AZD2327, indicating no or low risk for clinically relevant drug–drug interactions (DDI). These results are in agreement with those obtained in a clinical trial with a 1.4 and 1.5‐fold increase in C_max and AUC of midazolam, respectively. In conclusion, this model simulated DDI with less than a two‐fold error, indicating that complex clinical DDI associated with multiple mechanisms, pathways and inhibitors (parent and metabolite) can be predicted using a well‐developed PBPK model. Copyright © 2015 John Wiley & Sons, Ltd.     

用GastroPlus构建茶碱的早产儿生理药代动力学模型研究

目的构建茶碱的早产儿生理药代动力学(PBPK)模型,并进行药代动力学(PK)行为预测。方法通过文献收集茶碱的理化性质参数和临床试验数据,用Gastro Plus软件搭建PBPK模型,验证在不同人群的准确性及适用性,并用于预测早产儿人群,通过参数优化预测茶碱在早产儿个体的PK行为。结果经验证模型有良好的准确性和适用性,药物浓度-时间曲线下面积AUC_预测/AUC_观测比值在0.85~1.15,且决定系数(R^2)>0.85,观测值与预测曲线的重合度良好,误差较小。结论用Gastro Plus构建的茶碱早产儿PBPK模型能够较好地模拟药物在体内的PK过程,为个体化给药提供参考;同时,补充中国早产儿和婴幼儿PBPK建模的重要生理和解剖学数据,可以提高模拟的准确性。     

Predicting age-appropriate pharmacokinetics of six volatile organic compounds in the rat utilizing physiologically based pharmacokinetic modeling.

The capability of physiologically based pharmacokinetic models to incorporate age-appropriate physiological and chemical-specific parameters was utilized to predict changes in internal dosimetry for six volatile organic compounds (VOCs) across different ages of rats. Typical 6-h animal inhalation exposures to 50 and 500 ppm perchloroethylene, trichloroethylene, benzene, chloroform, methylene chloride, or methyl ethyl ketone (MEK) were simulated for postnatal day 10 (PND10), 2-month-old (adult), and 2-year-old (aged) rats. With the exception of MEK, predicted venous blood concentrations of VOCs in the aged rat were equal or up to 1.5-fold higher when compared to the adult rat at both exposure levels, whereas levels were predicted to be up to 3.8-fold higher in the case of PND10 at 50 ppm. Predicted blood levels of MEK were similar in the adult and aged rat, but were more than 5-fold and 30-fold greater for PND10 rats at 500 and 50 ppm, respectively, reflecting high water solubility along with lower metabolic capability and faster ventilation rate per unit body weight (BW) of PND10 animals. Steady-state blood levels of VOCs, simulated by modeling constant exposure, were predicted to be achieved in the order PND10 > adult > aged, largely due to increasing fat volume. The dose metric, total amount metabolized per unit liver volume was generally much lower in PND10 than in adult rats. The blood:air partition coefficient, fat volume, and fat blood flow were identified as critical determinants for the predicted differences in venous blood concentrations between the adult and aged. The lower metabolic capability, largely due to a smaller liver size, and faster ventilation rate per unit BW of PND10 animals contribute the most to the differences between PND10 and adult rats. This study highlights the pharmacokinetic differences and the relevant parameters that may contribute to differential susceptibility to the toxic effects of VOCs across life stages of the rat.     

Diazepam Pharamacokinetics from Preclinical to Phase I Using a Bayesian Population Physiologically Based Pharmacokinetic Model with Informative Prior Distributions in Winbugs

Modelling is an important applied tool in drug discovery and development for the prediction and interpretation of drug pharmacokinetics. Preclinical information is used to decide whether a compound will be taken forwards and its pharmacokinetics investigated in human. After proceeding to human little to no use is made of these often very rich data. We suggest a method where the preclinical data are integrated into a whole body physiologically based pharmacokinetic (WBPBPK) model and this model is then used for estimating population PK parameters in human. This approach offers a continuous flow of information from preclinical to clinical studies without the need for different models or model reduction. Additionally, predictions are based upon single parameter values, but making realistic predictions involves incorporating the various sources of variability and uncertainty. Currently, WBPBPK modelling is undertaken as a two-stage process: (i) estimation (optimisation) of drug-dependent parameters by either least squares regression or maximum likelihood and (ii) accounting for the existing parameter variability and uncertainty by stochastic simulation. To address these issues a general Bayesian approach using WinBUGS for estimation of drug-dependent parameters in WBPBPK models is described. Initially applied to data in rat, this approach is further adopted for extrapolation to human, which allows retention of some parameters and updating others with the available human data. While the issues surrounding the incorporation of uncertainty and variability within prediction have been explored within WBPBPK modeling methodology they have equal application to other areas of pharmacokinetics, as well as to pharmacodynamics.