A four-compartment PBPK heart model accounting for cardiac metabolism - model development and application

In the field of cardiac drug efficacy and safety assessment, information on drug concentration in heart tissue is desirable. Because measuring drug concentrations in human cardiac tissue is challenging in healthy volunteers, mathematical models are used to cope with such limitations. With a goal of predicting drug concentration in cardiac tissue, we have developed a whole-body PBPK model consisting of seventeen perfusion-limited compartments. The proposed PBPK heart model consisted of four compartments: the epicardium, midmyocardium, endocardium, and pericardial fluid, and accounted for cardiac metabolism using CYP450. The model was written in R. The plasma:tissues partition coefficients (Kp) were calculated in Simcyp Simulator. The model was fitted to the concentrations of amitriptyline in plasma and the heart. The estimated parameters were as follows: 0.80 for the absorption rate [h(−1)], 52.6 for Kp(rest), 0.01 for the blood flow through the pericardial fluid [L/h], and 0.78 for the P-parameter describing the diffusion between the pericardial fluid and epicardium [L/h]. The total cardiac clearance of amitriptyline was calculated as 0.316 L/h. Although the model needs further improvement, the results support its feasibility, and it is a first attempt to provide an active drug concentration in various locations within heart tissue using a PBPK approach

An Open-Access dataset of thorough QT studies results

Along with the current interest in changes of cardiovascular risk assessment strategy and inclusion of in silico modelling into the applicable paradigm, the need for data has increased, both for model generation and testing. Data collection is often time-consuming but an inevitable step in the modelling process, requiring extensive literature searches and other identification of alternative resources providing complementary results. The next step, namely data extraction, can also be challenging. Here we present a collection of thorough QT/QTc (TQT) study results with detailed descriptions of study design, pharmacokinetics, and pharmacodynamic endpoints. The presented dataset provides information that can be further utilized to assess the predictive performance of di erent preclinical biomarkers for QT prolongation e ects with the use of various modelling approaches. As the exposure levels and population description are included, the study design and characteristics of the study population can be recovered precisely in the simulation. Another possible application of the TQT dataset is the analysis of drug characteristic/QT prolongation/TdP (torsade de pointes) relationship after the integration of provided information with other databases and tools. This includes drug cardiac safety classifications (e.g., CredibleMeds), Comprehensive in vitro Proarrhythmia Assay (CiPA) compounds classification, as well as those containing information on physico-chemical properties or absorption, distribution, metabolism, excretion (ADME) data like PubChem or DrugBank

Physiologically based pharmacokinetic-quantitative systems toxicology and safety (PBPK-QSTS) modeling approach applied to predict the variability of amitriptyline pharmacokinetics and cardiac safety in populations and in individuals

The physiologically based pharmacokinetic (PBPK) models allow for predictive assessment of variability in population of interest. One of the future application of PBPK modeling is in the field of precision dosing and personalized medicine. The aim of the study was to develop PBPK model for amitriptyline given orally, predict the variability of cardiac concentrations of amitriptyline and its main metabolite-nortriptyline in populations as well as individuals, and simulate the influence of those xenobiotics in therapeutic and supratherapeutic concentrations on human electrophysiology. The cardiac effect with regard to QT and RR interval lengths was assessed. The Emax model to describe the relationship between amitriptyline concentration and heart rate (RR) length was proposed. The developed PBPK model was used to mimic 29 clinical trials and 19 cases of amitriptyline intoxication. Three clinical trials and 18 cases were simulated with the use of PBPK-QSTS approach, confirming lack of cardiotoxic effect of amitriptyline in therapeutic doses and the increase in heart rate along with potential for arrhythmia development in case of amitriptyline overdose. The results of our study support the validity and feasibility of the PBPK-QSTS modeling development for personalized medicine

Drug-drug interactions and QT prolongation as a commonly assessed cardiac effect : comprehensive overview of clinical trials

BACKGROUND: Proarrhythmia assessment is one of the major concerns for regulatory bodies and pharmaceutical industry. ICH guidelines recommending preclinical tests have been established in attempt to eliminate the risk of drug-induced arrhythmias. However, in the clinic, arrhythmia occurrence is determined not only by the inherent property of a drug to block ion currents and disturb electrophysiological activity of cardiac myocytes, but also by many other factors modifying individual risk of QT prolongation and subsequent proarrhythmia propensity. One of those is drug-drug interactions. Since polypharmacy is a common practice in clinical settings, it can be anticipated that there is a relatively high risk that the patient will receive at least two drugs mutually modifying their proarrhythmic potential and resulting either in triggering the occurrence or mitigating the clinical symptoms. The mechanism can be observed either directly at the pharmacodynamic level by competing for the molecular targets, or indirectly by modifying the physiological parameters, or at the pharmacokinetic level by alteration of the active concentration of the victim drug. METHODS: This publication provides an overview of published clinical studies on pharmacokinetic and/or pharmacodynamic drug-drug interactions in humans and their electrophysiological consequences (QT interval modification). Databases of PubMed and Scopus were searched and combinations of the following keywords were used for Title, Abstract and Keywords fields: interaction, coadministration, combination, DDI and electrocardiographic, QTc interval, ECG. Only human studies were included. Over 4500 publications were retrieved and underwent preliminary assessment to identify papers accordant with the topic of this review. 76 papers reporting results for 96 drug combinations were found and analyzed. RESULTS: The results show the tremendous variability of drug-drug interaction effects, which makes one aware of complexity of the problem, and suggests the need for assessment of an additional risk factors and careful ECG monitoring before administration of drugs with anticipated QT prolongation. CONCLUSIONS: DDIs can play significant roles in drugs’ cardiac safety, as evidenced by the provided examples. Assessment of the pharmacodynamic effects of the drug interactions is more challenging as compared to the pharmacokinetic due to the significant diversity in the endpoints which should be analyzed specifically for various clinical effects. Nevertheless, PD components of DDIs should be accounted for as PK changes alone do not allow to fully explain the electrophysiological effects in clinic situations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40360-016-0053-1) contains supplementary material, which is available to authorized users

Model of the distribution of diastolic left ventricular posterior wall thickness in healthy adults and its impact on the behavior of a string of virtual cardiomyocytes

Correlation of the thickness of the left ventricular posterior wall (LVPWd) with various parameters, including age, gender, weight and height, was investigated in this study using regression models. Multicenter derived database comprised over 4,000 healthy individuals. The developed models were further utilized in the in vitro-in vivo (IVIV) translation of the drug cardiac safety data with use of the mathematical model of human cardiomyocytes operating at the virtual healthy population level. LVPWd was assumed to be equivalent to the length of one-dimensional string of virtual cardiomyocyte cells which was presented, as other physiological factors, to be a parameter influencing the simulated pseudo-ECG (pseudoelectrocardiogram), QTcF and $\Delta$QTcF, both native and modified by exemplar drug (disopyramide) after $I_{Kr}$ current disruption. Simulation results support positive correlation between the LVPWd and QTcF/$\Delta$QTc. Developed models allow more detailed description of the virtual population and thus inter-individual variability influence on the drug cardiac safet

Study of abnormal toxicokinetic profiles using population pharmacokinetics approaches

Dane pochodzące z obserwacji pacjentów hospitalizowanych z powodu ostrego zatrucia olanzapiną wskazują na inny niż oczekiwany przebieg krzywej: stężenie olanzapiny-czas w zakresie stężeń toksycznych. Niniejsza praca ma na celu odpowiedzieć na pytanie o przyczyny tej anomalii. Wykorzystując farmakokinetyczne modelowanie populacyjne, zweryfikowano dwie hipotezy: krążenie olanzapiny w cyklu jelitowo-wątrobowym (EHC) oraz tworzenie jej depozytu i desorpcję z powierzchni węgla aktywowanego użytego do dekontaminacji. Oceniono także użyteczność standardowych modeli farmakokinetycznych w toksykokinetycznej analizie populacyjnej olanzapiny.Dane poddane analizie zostały opracowane w rozprawie doktorskiej dra Krzysztofa Ciszowskiego. Do modelowania użyto programu Monolix wersję 4.1.3. oraz wersję 4.2.2.(Lixoft, Orsey, Francja), wykorzystujący do modelowania nieliniowych efektów mieszanych algorytm SAEM.Zaproponowano modele z pojedynczym oraz dwukrotnym opróżnianiem pęcherzyka żółciowego w nieregularnych odstępach czasu. Skonstruowano również modele uwzględniające desorpcję olanzapiny z powierzchni węgla aktywowanego, w których przyjęta dawka leku wchłania się w dwóch lub trzech różnych etapach.Praca doprowadziła do wniosku, że weryfikowane modele należy konstruować w oparciu o model dwukompartmentowy. Prawdopodobnie na parametry farmakokinetyczne olanzapiny wpływają: proces dekontaminacji, wcześniejsza terapia tym lekiem oraz paleniepapierosów i spożywanie alkoholu. W celu wiarygodnego przetestowania hipotez analiza powinna objąć większą liczbę danych, dla weryfikacji hipotezy EHC cenna byłaby także znajomość stężenia glukuronianu olanzapiny.Data comes from observations of patients who were hospitalised for acute olanzapine poisoning. It suggests olanzapine plasma concentration time curve in the range of toxic concentrations being different than expected. The aim of this study is to find the reasons for that anomaly. Using population pharmacokinetic modelling two hypotheses for olanzapinewere verified: entering the enterohepatic cycle (EHC) and drug deposition and its desorption from activated charcoal used for gastrointestinal decontamination. The usefulness of standard pharmacokinetic models in toxicokinetic population modeling of olanzapine was also valued. Data analysed in the study was taken from the Ph.D. Thesis of Dr. Krzysztof Ciszowski. To estimate the parameters program Monolix, in versions 4.1.3. and 4.2.2. (Lixoft, Orsey, France), was used. The primary algorithm implemented by Monolix is SAEM.Models with one or two gallbladder emptying occuring at irregular intervals were developed. Also, models that describe desorption of olanzapine from the charcoal surface, in which the dose was divided into two or three absorbed fractions, were constructed.Thesis leads to the conclusion that the models in question should be developed as extensions of two-compartmental models. Most likely, the pharmacokinetic parameters of olanzapine depend on gastrointestinal decontamination, previous olanzapine treatment, smoking and alcohol. To reliably test these hypotheses, more data should be analysed. To verify the EHC assumption, the knowledge of glucuronidated olanzapine serum concentration would be needed