Modeling and simulation of adherence: Approaches and applications in therapeutics

Partial adherence with a prescribed or randomly assigned dose gives rise to unintended variability in actual drug exposure in clinical practice and during clinical trials. There are tremendous costs associated with incomplete and/or improper drug intake-to both individual patients and society as a whole. Methodology for quantifying the relation between adherence, exposure and drug response is an area of active research. Modeling and statistical approaches have been useful in evaluating the impact of adherence on therapeutics and in addressing the challenges of confounding and measurement error which arise in this context. This paper reviews quantitative approaches to using adherence information in improving therapeutics. It draws heavily on applications in the area of HIV pharmacology.     

Population pharmacokinetics/pharmacodynamics of anesthetics

In this article we review how population pharmacokinetic/pharmacodynamic (PD) modeling has evolved in the specialty of anesthesiology, how anesthesiology benefited from the mixed-effects approach, and which features of modeling need careful attention. Key articles from the anesthesiology literature are selected to discuss the modeling of typical anesthesiological PD end points, such as level of consciousness and analgesia, interactions between hypnotics and analgesics, estimation with poor and sometimes rich data sets from populations of various sizes, covariate detection, covariances between random effects, and Bayesian forecasting.     

药动药效联合模型定量分析方法的研究现状

药动药效联合模型在药理学研究中正在发挥越来越重要的作用。本文介绍了近年来该领域定量计算方面的一些新概念和新进展，包括药动学和药效学模型、药动药效联合模型的四个属性、Sheiner效应室理论应用时应该注意的问题及药动药效联合模型的计算程序等。     

Population Pharmacokinetic-Pharmacodynamic Model of Craving in an Enforced Smoking Cessation Population: Indirect Response and Probabilistic Modeling

Purpose. A population pharmacokinetic-pharmacodynamic model accounting for placebo effect was used to relate nicotine concentration and enforced smoking cessation craving score measured by the Tiffany rating scale short form. Methods. Twenty-four smokers were enrolled in a placebo-controlled, randomized, double-blind, three periods, crossover trial. The study objective was to describe the nicotine-induced changes on craving scores. Two modeling strategies based on a mechanistic (indirect response models with drug-related inhibition on the k_in synthesis rate and with a drug-related stimulation of the k_out removal rate were evaluated) and a probabilistic (logistic regression) approach were used. Results. Placebo response model properly fitted the circadian changes on craving scores. The analysis revealed that the indirect response model with inhibition on k_in was the preferred model for the smoking data whereas the preferred model for the Nicotine Replacement Therapy data was the one with stimulation on k_out. The logistic analysis showed that the nicotine concentration was a significant predictor of reduction in craving during the free-smoking period. Conclusions. Nicotine dosage regimen can influence the nicotine mechanism of action: an instantaneous delivery at an individually selected time seems to inhibit the onset of craving while constant delivery at a pre-defined time seems to attenuate the craving.     

Development of QTc prolongation model incorporating circadian rhythm using harmonic model

Abstract

1. QT prolongation is one of the major safety tests used in the development of a new drug. The ICH guidelines for the evaluation of QT prolongation recommend the use of the in vitro hERG assay and the in vivo telemetry test. However, QT intervals change under normal conditions due to circadian rhythm and can affect the results of the tests. In this study, we developed a PK/PD model to describe the QT interval after the administration of astemizole allowing for the normal changes by circadian rhythm.

2. The typical PK parameters of absorption rate constant (k_a), volume of distribution (V_c and V_m), metabolism (k_m), and elimination rate constant (k_el and k_el-m) were 0.49?h^?1, 4950?L, 20?L, 0.0127?h^?1, 0.0095?h^?1, and 0.95?h^?1, respectively. The final PK/PD model was the biophase model with the modified harmonic model. The typical PK/PD parameters, base QTc interval (QT₀), amplitude (T₁, T₃), period of QTc interval changing (T₂, T₄), and EC₅₀ were 233?ms, 3.31, 1.5, ?9.24?h, 1.85?h, and 0.81?ng/ml, respectively.

3. The PK/PD model to explain the changes of the QT interval that allows normal changes in the circadian rhythm after the administration of astemizole was developed successfully. This final model can be applied to the development of a human model.     

Facilitating Compound Progression of Antiretroviral Agents via Modeling and Simulation

Pharmacotherapy in human immunodeficiency virus (HIV)-infected patients and the development of safe and effective antiretroviral dosing regimens has been hindered by numerous issues, including the rapid development of viral resistance to drug therapy, the narrow therapeutic window of the drug compounds, and lack of fundamental knowledge concerning the sources of variation in exposure and response to antiretroviral agents. Sources of variation may include factors such as interpatient differences in genetic expression, immunological response, pathogenesis, epidemiologic and socioeconomic factors, and demographics. Modeling and simulation (M&S) techniques have become valuable tools to identify and quantify variability in exposure and response to antiretroviral agents throughout the drug development process. Before actual entry into human safety and pharmacokinetic (PK) trials, in vitro screening and in vivo pharmacology studies conducted to assess compound potency and compatibility with agents included in acceptable antiretroviral therapy (ART) regimens can be characterized via quantitative relationships. In addition, physiochemical data is initially used to screen drug candidates based on favorable PK and biopharmaceutic properties. Compound progression can likewise be supported with M&S exercises to ensure the traceability of key assumptions and decisions. The underlying techniques utilize nonlinear mixed effect modeling, Monte Carlo simulation, Neural networks, several regression-based approaches, and less computationally intensive techniques. The application of such an approach promises to be an essential component in the development of new agents to treat HIV-1 and is being implemented in the context of evaluating Nk1r antagonists as potential candidates to treat NeuroAIDS.     

Pharmacokinetic/pharmacodynamic studies on exenatide in diabetic rats

Aim:

To quantitatively evaluate the blood glucose-lowering effect of exenatide in diabetic rats.

Methods:

Male Harlan-Sprague-Dawley rats were treated with high-fat diet/streptozotocin to induce type 2 diabetes. After subcutaneous administration of a single dose of exenatide (4.2, 42, or 210 μg/kg), serum exenatide, insulin concentration and blood glucose were measured. The pharmacokinetics of exenatide was characterized by a two-compartment model with first-order absorption. Insulin turnover was characterized by an effect compartment and indirect response combined model. Glucose turnover was described using an indirect response model with insulin (in effect compartment) stimulating glucose disposition and insulin (in insulin compartment) inhibiting glucose production simultaneously. The model parameters were estimated using nonlinear mixed-effects model program. Visual predictive check and model evaluation were used to make assessments.

Results:

Exenatide exhibited rapid absorption with k_a=4.45 h^-1, and the two-compartment model well described its pharmacokinetic profile. For the pharmacodynamic model, exenatide increased insulin release with the estimated S_m1 of 0.822 and SC₅₀ of 4.02 μg/L. It was demonstrated that insulin stimulated glucose dissipation (S_m2=0.0513) and inhibited the production of glucose (I_m=0.0381). Visual predictive check and model evaluation study indicated that a credible model was developed.

Conclusion:

The glucose-lowering effect of exenatide in diabetic rats is reliably described and predicted by the combined effect compartment/indirect response model.     

Modeling of tumor growth and anticancer effects of combination therapy

Combination therapies are widely used in the treatment of patients with cancer. Selecting synergistic combination strategies is a great challenge during early drug development. Here, we present a pharmacokinetic/pharmacodynamic (PK/PD) model with a smooth nonlinear growth function to characterize and quantify anticancer effect of combination therapies using time-dependent data. To describe the pharmacological effect of combination therapy, an interaction term was introduced into a semi-mechanistic anticancer PK/PD model. This approach enables testing of a pharmacological hypothesis with respect to an anticipated pharmacological synergy of drug combinations, such as an assumed pharmacological synergy of complementary inhibition of a particular signaling pathway. The model was applied to three real data sets derived from preclinical screening experiments using xenograft mice. The suggested model fitted well the observed data from mono- to combination-therapy and allowed physiologically meaningful interpretation of the experiments. The tested drug combinations were assessed for their ability to act as synergistic modulators of tumor growth inhibition by the interaction parameter ψ. The presented approach has practical implications because it can be applied to standard xenograft experiments and may assist in the selection of both optimal drug combinations and administration schedules. The unique feature of the presented approach is the ability to characterize the nature of combined drug interaction as well as to quantify the intensity of such interactions by assessing the time course of combined drug effect.     

Influence of the pharmacokinetic profile on the plasma glucose lowering effect of the PPARγ agonist pioglitazone in Wistar fatty rats

Although the mechanism of action for peroxisome proliferator‐activated receptor gamma (PPARγ) agonists has been extensively explored, the impact of the pharmacokinetic (PK) profile on the pharmacodynamic (PD) effects of PPARγ agonists has not been elucidated in detail. The importance of the PK profile of PPARγ agonist was evaluated for its PD effect based on population PK/PD analysis. Pioglitazone hydrochloride, the PPARγ agonist, was administered orally to Wistar fatty rats once a day (q.d.) or once every other day (q.2d.) as double the amount for the q.d. treatment. The plasma glucose lowering effect was selected as a surrogate PD effect for an anti‐diabetic effect. The model fitting was conducted using the non‐linear mixed effect modeling (NONMEM) method. The indirect response model described well the plasma glucose concentration–time profile. The q.d. treatment showed a stronger impact on the plasma glucose lowering effect than did the q.2d. treatment. The results of PK/PD modeling suggested that the sensitivity (i.e. EC ₅₀) between each group was comparable. On the other hand, the time above the effective concentration in the q.d. treatment group was longer than that in the q.2d. treatment group. The simulation of various dose regimens suggested that the much longer exposure duration within the effective level showed a stronger plasma glucose lowering effect, even with identical exposure to pioglitazone in the plasma. The PK/PD analysis clarified that the PK profile affected the pharmacological response and that continuous exposure at an appropriate effective level would be efficient for the anti‐diabetic effect of the PPARγ agonist.     

Stochastic Differential Equations in NONMEM®: Implementation,Application, and Comparison with Ordinary Differential Equations

Purpose The objective of the present analysis was to explore the use of stochastic differential equations (SDEs) in population pharmacokinetic/pharmacodynamic (PK/PD) modeling.Methods The intra-individual variability in nonlinear mixed-effects models based on SDEs is decomposed into two types of noise: a measurement and a system noise term. The measurement noise represents uncorrelated error due to, for example, assay error while the system noise accounts for structural misspecifications, approximations of the dynamical model, and true random physiological fluctuations. Since the system noise accounts for model misspecifications, the SDEs provide a diagnostic tool for model appropriateness. The focus of the article is on the implementation of the Extended Kalman Filter (EKF) in NONMEM^® for parameter estimation in SDE models.Results Various applications of SDEs in population PK/PD modeling are illustrated through a systematic model development example using clinical PK data of the gonadotropin releasing hormone (GnRH) antagonist degarelix. The dynamic noise estimates were used to track variations in model parameters and systematically build an absorption model for subcutaneously administered degarelix.Conclusions The EKF-based algorithm was successfully implemented in NONMEM for parameter estimation in population PK/PD models described by systems of SDEs. The example indicated that it was possible to pinpoint structural model deficiencies, and that valuable information may be obtained by tracking unexplained variations in parameters.     

利奈唑胺的PK/PD与给药方案优化设计研究进展

通过CNKI、PUBMED等文献库查阅相关文献进行分析,介绍利奈唑胺在不同疾病中PK/PD特点,从而为临床合理应用提供参考.以PK/PD参数为依据,对给药方案进行优化,可以更好地发挥抗菌药物的临床治疗效果,降低不良反应和耐药性的发生率,减轻患者经济负担.利奈唑胺具有强大的抗革兰阳性菌活性,由于不同病理生理因素与其PK/PD特点,研究优化给药方案、促进合理用药具有重大意义.     

Collapsing Mechanistic Models: An Application to Dose Selection for Proof of Concept of a Selective Irreversible Antagonist

When data fail to support fully mechanistic models, alternative modeling strategies must be pursued. Simpler, more empirical models or the fixing of various rate constants are necessary to avoid over-parameterization. Fitting empirical models can dilute information, limit interpretation, and cloud inference. Fixing rate constants requires external, relevant, and reliable information on the mechanism and can introduce subjectivity as well as complicate determining the validity of model extrapolation. Furthermore, both these methods ignore the possibility that failure of the data to support the mechanistic model could contain information about the pharmacodynamic process. If the pathway has processes with “fast” dynamics, these steps could collapse yielding parametrically simpler classes of models. The collapsed models would retain the mechanistic interpretation of the full model, which is crucial for performing substantive inference, while reducing the number of parameters to be estimated. These concepts are illustrated through their manifestations on the dose–effect relationship and ensuing dose selection for a proof of concept study. Specifically, a mechanistic model for a selective irreversible antagonist was posited and candidate classes of models were derived utilizing “fast dynamics” assumptions. Model assessment determined the rate-limiting step facilitating pertinent inference with respect to the mechanism. For comparison, inference using a more empirical modeling strategy is also presented. A general solution for the collapse of the typical PK–PD model differential equations is provided in Appendix A     

Pharmacokinetic and pharmacodynamic modeling of the metastin/kisspeptin analog,TAK-448, for its anti-tumor efficacy in a rat xenograft model

TAK-448 is the investigational metastin/kisspeptin analog, which is known to have an anti-tumor effect through suppression of androgen hormones (luteinizing hormone and testosterone) levels. This study developed pharmacokinetic-pharmacodynamic (PK/PD) models of TAK-448 and leuprorelin acetate (TAP-144) in a rat vertebral-cancer of the prostate (VCaP) androgen-sensitive prostate cancer xenograft model to quantitatively assess and compare the anti-tumor effects of both drugs. A potential contribution of the hormone-independent direct effects of TAK-448 to the tumor growth inhibition was also investigated in the in vivo rat xenograft model, because our in vitro experiments revealed that TAK-448 may also directly suppress VCaP cellular proliferation. The PK/PD model successfully described the time course of tumor growth inhibition after drug treatment as well as the development of resistance to the inhibition of androgen hormones, following drug treatment or castration. The EC₅₀ of the hormone-dependent inhibitory effect of TAK-448 was much lower than that of TAP-144, and TAK-448 also has a faster onset of anti-tumor effect than TAP-144, demonstrating that TAK-448 has a stronger overall anti-tumor effect than TAP-144. In addition, model inference, by incorporating a hormone-independent inhibition pathway of TAK-448 into the PK-PD model, suggested that such a direct inhibition pathway for TAK-448 cannot be excluded, as also indicated by in vitro studies, but its EC₅₀ would be approximately three orders of magnitude higher than that of the hormone-dependent pathway. This study helps to understand the potential and mechanism of TAK-448 as a prostate cancer treatment.     

Population pharmacokinetic/pharmacodynamic (PK/PD) modelling of the hypothalamic-pituitary-gonadal axis following treatment with GnRH analogues

AIMS: To develop a population pharmacokinetic/pharmacodynamic (PK/PD) model of the hypothalamic-pituitary-gonadal (HPG) axis describing the changes in luteinizing hormone (LH) and testosterone concentrations following treatment with the gonadotropin-releasing hormone (GnRH) agonist triptorelin and the GnRH receptor blocker degarelix. METHODS: Fifty-eight healthy subjects received single subcutaneous or intramuscular injections of 3.75 mg of triptorelin and 170 prostate cancer patients received multiple subcutaneous doses of degarelix of between 120 and 320 mg. All subjects were pooled for the population PK/PD data analysis. A systematic population PK/PD model-building framework using stochastic differential equations was applied to the data to identify nonlinear dynamic dependencies and to deconvolve the functional feedback interactions of the HPG axis. RESULTS: In our final PK/PD model of the HPG axis, the half-life of LH was estimated to be 1.3 h and that of testosterone 7.69 h, which corresponds well with literature values. The estimated potency of LH with respect to testosterone secretion was 5.18 IU l(-1), with a maximal stimulation of 77.5 times basal testosterone production. The estimated maximal triptorelin stimulation of the basal LH pool release was 1330 times above basal concentrations, with a potency of 0.047 ng ml(-1). The LH pool release was decreased by a maximum of 94.2% by degarelix with an estimated potency of 1.49 ng ml(-1). CONCLUSIONS: Our model of the HPG axis was able to account for the different dynamic responses observed after administration of both GnRH agonists and GnRH receptor blockers, suggesting that the model adequately characterizes the underlying physiology of the endocrine system.     

Investigation of Drug Delivery in Rats via Subcutaneous Injection: Case Study of Pharmacokinetic Modeling of Suspension Formulations

With the rising cost of drug research, “do more with less” has become a new emphasis in the pharmaceutical industry. Consequently, the early analysis of pharmacokinetic/pharmacodynamic, efficacy, and safety parameters for a new drug target is critical for ensuring informed decision-making as soon as possible during the drug discovery process. When absorption, distribution, metabolism, and excretion properties of compounds are suboptimal which is especially true during the early stages of drug discovery, obtaining the desired exposure can be challenging via the most common routes (oral, intravenous). Therefore, subcutaneous (SC) injection is often explored as an alternate route of delivery. Although SC injection is used widely in the industry, information about how to model and predict the absorption of drugs administered via SC injection is not readily available. In the current research, we analyzed the absorption behavior of 12 model compounds covering a wide range of physicochemical properties following SC injection. We introduced a compound-specific parameter, the absorption factor from single SC injections of suspension doses of each compound, to aid in modeling and predicting of drug absorption profiles. The pharmacokinetic models derived in this study are capable of describing and predicting the absorption properties of SC injection for individual compounds.     

基于治疗药物监测及Bayesian反馈法的美罗培南注射剂药代动力学/药效学研究

由于抗菌药物的不合理使用,造成细菌耐药率逐年升高。抗菌药物的药物代谢动力学/药物效应动力学（PK/PD）研究可充分考虑病原体、宿主和药物三者的相互关系,反映抗菌药物杀菌效应及不良反应与血药浓度变化之间的关系,对抗菌药物的开发及使用等具有重要价值。从PK/PD模型、相关理论及其在临床应用等方面进行综述,旨在为临床合理使用抗菌药物,减少耐药菌的产生提供参考。

     

构建沙格列汀PK/PD模型——模拟其在健康人群和肝损伤患者的药动学和药效学

在本次研究中,我们旨在开发和评价沙格列汀的全身生理药代动力学(WB-PBPK)/药效学(PD)模型,模拟其在健康成人及肝功能损害患者中的药代动力学和药效学特性,为特殊患者的临床药学研究提供新方法.基于文献中获取的如logD和血浆蛋白结合率等药物特征参数,建立WB-PBPK模型和PD模型.将模拟所得的血药浓度-时间曲线及...     

CCR2拮抗剂研究进展

细胞表面趋化因子受体2(CCR2)属于G蛋白偶联受体(GPCR)超家族成员,并且是单核细胞趋化蛋白1～4(MCP1～4)的受体.MCP1～4是促炎症反应的化学诱导物,CCR2和MCP-1在人类侵蚀性疾病模型如动脉粥状硬化、多发性硬化症中均起显著作用.大量研究证明CCR2和MCP-1拮抗剂可以减少临床炎症模型的发病率,这些化学拮抗剂的结构多样,主要包括γ-氨基丁酰胺类、甘胺酰胺类、噻唑类、吲哚类、二取代双哌啶醇类、季铵盐类和不饱和杂环类等,它们表现出不同的药理活性.CCR2拮抗剂对各种与趋化因子相关的疾病具有较好的疗效,部分药物已经进入临床试验阶段,综述CCR2及其受体拮抗剂的研究进展.