Pharmacokinetic–pharmacodynamic modelling in anaesthesia

Anaesthesiologists adjust drug dosing, administration system and kind of drug to the characteristics of the patient. They then observe the expected response and adjust dosing to the specific requirements according to the difference between observed response, expected response and the context of the surgery and the patient.The approach above can be achieved because on one hand quantification technology has made significant advances allowing the anaesthesiologist to measure almost any effect by using noninvasive, continuous measuring systems. On the other the knowledge on the relations between dosing, concentration, biophase dynamics and effect as well as detection of variability sources has been achieved as being the benchmark specialty for pharmacokinetic–pharmacodynamic (PKPD) modelling.The aim of the review is to revisit the most common PKPD models applied in the field of anaesthesia (i.e. effect compartmental, turnover, drug–receptor binding and drug interaction models) through representative examples. The effect compartmental model has been widely used in this field and there are multiple applications and examples. The use of turnover models has been limited mainly to describe respiratory effects. Similarly, cases in which the dissociation process of the drug–receptor complex is slow compared with other processes relevant to the time course of the anaesthetic effect are not frequent in anaesthesia, where in addition to a rapid onset, a fast offset of the response is required. With respect to the characterization of PD drug interactions different response surface models are discussed. Relevant applications that have changed the way modern anaesthesia is practiced are also provided.     

A review of disease progression models of Parkinson's disease and applications in clinical trials

Quantitative disease progression models for neurodegenerative disorders are gaining recognition as important tools for drug development and evaluation. In Parkinson's disease (PD), several models have described longitudinal changes in the Unified Parkinson's Disease Rating Scale (UPDRS), one of the most utilized outcome measures for PD trials assessing disease progression. We conducted a literature review to examine the methods and applications of quantitative disease progression modeling for PD using a combination of key words including “Parkinson disease,” “progression,” and “model.” For this review, we focused on models of PD progression quantifying changes in the total UPDRS scores against time. Four different models reporting equations and parameters have been published using linear and nonlinear functions. The reasons for constructing disease progression models of PD thus far have been to quantify disease trajectories of PD patients in active and inactive treatment arms of clinical trials, to quantify and discern symptomatic and disease‐modifying treatment effects, and to demonstrate how model‐based methods may be used to design clinical trials. The historical lack of efficiency of PD clinical trials begs for model‐based simulations in planning for studies that result in more informative conclusions, particularly around disease modification. © 2016 International Parkinson and Movement Disorder Society     

Optimal sampling of antipsychotic medicines: a pharmacometric approach for clinical practice

Aim

To determine optimal sampling strategies to allow the calculation of clinical pharmacokinetic parameters for selected antipsychotic medicines using a pharmacometric approach.

Methods

This study utilized previous population pharmacokinetic parameters of the antipsychotic medicines aripiprazole, clozapine, olanzapine, perphenazine, quetiapine, risperidone (including 9-OH risperidone) and ziprasidone. d-optimality was utilized to identify time points which accurately predicted the pharmacokinetic parameters (and expected error) of each drug at steady-state. A standard two stage population approach (STS) with MAP-Bayesian estimation was used to compare area under the concentration–time curves (AUC) generated from sparse optimal time points and rich extensive data. Monte Carlo Simulation (MCS) was used to simulate 1000 patients with population variability in pharmacokinetic parameters. Forward stepwise regression analysis was used to determine the most predictive time points of the AUC for each drug at steady-state.

Results

Three optimal sampling times were identified for each antipsychotic medicine. For aripiprazole, clozapine, olanzapine, perphenazine, risperidone, 9-OH risperidone, quetiapine and ziprasidone the CV% of the apparent clearance using optimal sampling strategies were 19.5, 8.6, 9.5, 13.5, 12.9, 10.0, 16.0 and 10.7, respectively. Using the MCS and linear regression approach to predict AUC, the recommended sampling windows were 16.5–17.5 h, 10–11 h, 23–24 h, 19–20 h, 16.5–17.5 h, 22.5–23.5 h, 5–6 h and 5.5–6.5 h, respectively.

Conclusion

This analysis provides important sampling information for future population pharmacokinetic studies and clinical studies investigating the pharmacokinetics of antipsychotic medicines.     

Population pharmacokinetics of valganciclovir prophylaxis in paediatric and adult solid organ transplant recipients

Aim

Our aims were to quantify ganciclovir pharmacokinetics in paediatric and adult kidney, liver and lung transplant patients taking a range of valganciclovir doses to prevent herpes virus infections, including a 450 mg regimen, and to identify sources of pharmacokinetic variability.

Method

Plasma samples were collected at 2, 4, 8 and 12 weeks post-transplant and at 4, 6, 8 and 12 months post-transplant in subjects prescribed longer courses. Ganciclovir was measured by liquid chromatography/ultraviolet detection. Non-linear mixed effects modelling was used to analyze the concentration–time data and evaluate demographic and transplant-related covariates.

Results

A two compartment model with first order absorption best described the data. Given the range of body sizes, clearance and volume of distribution terms were scaled using standard weight-based allometric exponents. Creatinine clearance was included on apparent oral clearance. Final estimates in a standard 70 kg individual for apparent oral clearance, central volume of distribution, intercompartmental clearance and peripheral volume of distribution were 14.5 l h⁻¹, 87.5 l, 4.80 l h⁻¹ and 42.6 l, respectively. The median terminal half-life for kidney, liver and lung transplant recipients was 9.4, 9.5 and 8.2 h, respectively. Median exposure (i.e. AUC(0,∞) in subjects taking valganciclovir 900 mg or 450 mg once daily was 57.4 and 34.3 μg ml⁻¹ h, respectively.

Conclusion

Allometric scaling allowed simultaneous analysis of data from children and adults. Ganciclovir pharmacokinetics were similar among kidney, liver and lung transplant recipients. Ganciclovir exposure after valganciclovir 450 mg once daily may be suboptimal in some individuals and requires evaluation along with virologic outcomes data.     

基于模型的药物研发

药物研发的高投入和高风险促使药物研发者和审评者积极尝试各种先进的研究方法与工具来提高药物研发效率。基于模型的药物研发理念（MBDD）是采用定量研究的方法,通过建模与模拟技术,进行药物研发的一种新的研发模式。MBDD强调药物研发全过程中学习的重要性,将隐藏在药物研发数据中的知识通过定量的方法挖掘出来,用以指导下一阶段的研究方案的设计,可大大提高药物研发资源的利用率,增加研发效率。综述MBDD的概念、发展以及应用,旨在为从事药物研发的工作者提供借鉴,希望国内有更多的研究者关注这一新的研究模式,以促进我国新药研发模式的转变。     

Vancomycin pharmacokinetic models: informing the clinical management of drug-resistant bacterial infections

This review aims to critically evaluate the pharmacokinetic literature describing the use of vancomycin in the treatment of methicillin-resistant Staphylococcus aureus (MRSA) infections. Guidelines recommend that trough concentrations be used to guide vancomycin dosing for the treatment of MRSA infections; however, numerous in vitro, animal model and clinical studies have demonstrated that the therapeutic effectiveness of vancomycin is best described by the area under the concentration versus time curve (AUC) divided by the minimum inhibitory concentration (MIC) of the infecting organism (AUC/MIC). Among patients with lower respiratory tract infections, an AUC/MIC ≥400 was associated with a superior clinical and bacteriological response. Similarly, patients with MRSA bacteremia who achieved an Etest AUC/MIC ≥320 within 48 h were 50% less likely to experience treatment failure. For other patient populations and different clinical syndromes (e.g., children, the elderly, patients with osteomyelitis, etc.), pharmacokinetic/pharmacodynamic studies and prospective clinical trials are needed to establish appropriate therapeutic targets.     

现代定量药理学的研究进展及展望

定量药理学是运用数学和统计方法,定量研究药理作用规律的一门分支学科,该学科在新药研发及临床药物治疗中正在发挥愈来愈重要的作用。近年国外学界提出了基于模型的新药研发等新理念,将定量药理学的重要性提升到了新的高度,定量药理学正迈入一个新的时代。国内该学科已有二十多年的发展历史,打下了良好的基础,但较国际先进水平还有一定差距,目前正面临着新的发展契机,机遇与挑战并存。本文首先辨析了学科定义,并简要回顾了国内外的学科发展简史;重点介绍了该学科的重要研究领域及热点技术,包括群体药动学/药效学、暴露-反应（药动学-药效学）关系、临床试验模拟、新型临床试验设计、生物标记物、疾病模型和试验模型、建模与模拟的方法学等;简介了基于模型的新药研发的新理念;最后,对该学科的国内发展前景进行了展望。     

模型引导下免疫检查点抑制剂的研发

免疫检查点抑制剂作为一种新型的抗肿瘤治疗药物,因其对多种肿瘤卓越的疗效及良好的安全性得到广泛认可。基于定量药理学的发展应运而生的模型引导的药物研发(model-informed drug development,MIDD),能加速新药临床试验的进程,提高新药研究过程中决策的正确率,尤其是针对研发难度较大而需求甚广的免疫检查点抑制剂类新药。本文主要以帕博利珠单抗为例,阐述MIDD方法在免疫检查点抑制剂研发过程中的具体应用,包括研发早期有效给药方案的拟定,研发晚期评估临床疗效和验证给药方案的可行性,再至上市后给药方案的再评估及变更,为MIDD指导抗肿瘤新药的研发提供参考。