Population pharmacokinetic characterization of BAY 81-8973, a full-length recombinant factor VIII: lessons learned - importance of including samples with factor VIII levels below the quantitation limit.

INTRODUCTION: The pharmacokinetics (PK), safety and efficacy of BAY 81-8973, a full-length, unmodified, recombinant human factor VIII (FVIII), were evaluated in the LEOPOLD trials. AIM: The aim of this study was to develop a population PK model based on pooled data from the LEOPOLD trials and to investigate the importance of including samples with FVIII levels below the limit of quantitation (BLQ) to estimate half-life. METHODS: The analysis included 1535 PK observations (measured by the chromogenic assay) from 183 male patients with haemophilia A aged 1-61 years from the 3 LEOPOLD trials. The limit of quantitation was 1.5 IU dL-1 for the majority of samples. Population PK models that included or excluded BLQ samples were used for FVIII half-life estimations, and simulations were performed using both estimates to explore the influence on the time below a determined FVIII threshold. RESULTS: In the data set used, approximately 16.5% of samples were BLQ, which is not uncommon for FVIII PK data sets. The structural model to describe the PK of BAY 81-8973 was a two-compartment model similar to that seen for other FVIII products. If BLQ samples were excluded from the model, FVIII half-life estimations were longer compared with a model that included BLQ samples. CONCLUSIONS: It is essential to assess the importance of BLQ samples when performing population PK estimates of half-life for any FVIII product. Exclusion of BLQ data from half-life estimations based on population PK models may result in an overestimation of half-life and underestimation of time under a predetermined FVIII threshold, resulting in potential underdosing of patients.

Drug effects on the CVS in conscious rats: separating cardiac output into heart rate and stroke volume using PKPD modelling.

BACKGROUND AND PURPOSE: Previously, a systems pharmacology model was developed characterizing drug effects on the interrelationship between mean arterial pressure (MAP), cardiac output (CO) and total peripheral resistance (TPR). The present investigation aims to (i) extend the previously developed model by parsing CO into heart rate (HR) and stroke volume (SV) and (ii) evaluate if the mechanism of action (MoA) of new compounds can be elucidated using only HR and MAP measurements. EXPERIMENTAL APPROACH: Cardiovascular effects of eight drugs with diverse MoAs (amiloride, amlodipine, atropine, enalapril, fasudil, hydrochlorothiazide, prazosin and propranolol) were characterized in spontaneously hypertensive rats (SHR) and normotensive Wistar-Kyoto (WKY) rats following single administrations of a range of doses. Rats were instrumented with ascending aortic flow probes and aortic catheters/radiotransmitters for continuous recording of MAP, HR and CO throughout the experiments. Data were analysed in conjunction with independent information on the time course of the drug concentration following a mechanism-based pharmacokinetic-pharmacodynamic modelling approach. KEY RESULTS: The extended model, which quantified changes in TPR, HR and SV with negative feedback through MAP, adequately described the cardiovascular effects of the drugs while accounting for circadian variations and handling effects. CONCLUSIONS AND IMPLICATIONS: A systems pharmacology model characterizing the interrelationship between MAP, CO, HR, SV and TPR was obtained in hypertensive and normotensive rats. This extended model can quantify dynamic changes in the CVS and elucidate the MoA for novel compounds, with one site of action, using only HR and MAP measurements. Whether the model can be applied for compounds with a more complex MoA remains to be established.

PKPD modelling of the interrelationship between mean arterial BP, cardiac output and total peripheral resistance in conscious rats.

BACKGROUND AND PURPOSE: The homeostatic control of arterial BP is well understood with changes in BP resulting from changes in cardiac output (CO) and/or total peripheral resistance (TPR). A mechanism-based and quantitative analysis of drug effects on this interrelationship could provide a basis for the prediction of drug effects on BP. Hence, we aimed to develop a mechanism-based pharmacokinetic-pharmacodynamic (PKPD) model in rats that could be used to characterize the effects of cardiovascular drugs with different mechanisms of action (MoA) on the interrelationship between BP, CO and TPR. EXPERIMENTAL APPROACH: The cardiovascular effects of six drugs with diverse MoA, (amlodipine, fasudil, enalapril, propranolol, hydrochlorothiazide and prazosin) were characterized in spontaneously hypertensive rats. The rats were chronically instrumented with ascending aortic flow probes and/or aortic catheters/radiotransmitters for continuous recording of CO and/or BP. Data were analysed in conjunction with independent information on the time course of drug concentration using a mechanism-based PKPD modelling approach. KEY RESULTS: By simultaneous analysis of the effects of six different compounds, the dynamics of the interrelationship between BP, CO and TPR were quantified. System-specific parameters could be distinguished from drug-specific parameters indicating that the model developed is drug-independent. CONCLUSIONS AND IMPLICATIONS: A system-specific model characterizing the interrelationship between BP, CO and TPR was obtained, which can be used to quantify and predict the cardiovascular effects of a drug and to elucidate the MoA for novel compounds. Ultimately, the proposed PKPD model could be used to predict the effects of a particular drug on BP in humans based on preclinical data.

A hidden Markov model to assess drug-induced sleep fragmentation in the telemetered rat.

Drug-induced sleep fragmentation can cause sleep disturbances either via their intended pharmacological action or as a side effect. Examples of disturbances include excessive daytime sleepiness, insomnia and nightmares. Developing drugs without these side effects requires insight into the mechanisms leading to sleep disturbance. The characterization of the circadian sleep pattern by EEG following drug exposure has improved our understanding of these mechanisms and their translatability across species. The EEG shows frequent transitions between specific sleep states leading to multiple correlated sojourns in these states. We have developed a Markov model to consider the high correlation in the data and quantitatively compared sleep disturbance in telemetered rats induced by methylphenidate, which is known to disturb sleep, and of a new chemical entity (NCE). It was assumed that these drugs could either accelerate or decelerate the transitions between the sleep states. The difference in sleep disturbance of methylphenidate and the NCE were quantitated and different mechanisms of action on rebound sleep were identified. The estimated effect showed that both compounds induce sleep fragmentation with methylphenidate being fivefold more potent compared to the NCE.

Clinical trial simulation: a review.

Modeling and simulation in general, and specifically clinical trial simulation (CTS), have been recognized by the (larger) pharmaceutical companies and regulatory authorities as being pivotal to improving the efficiency of the drug development process. This includes the use of CTS to learn about drug effectiveness and safety and to optimize trial designs at the various stages of development. By reviewing papers published during the period January 2000-January 2010, this paper discusses recent developments with respect to methodology, applications, and lessons learned in the use of CTS in the development and clinical use of specific drugs. It is expected that future CTS experiments will be aided by the hybridization of optimal design methods with computationally intensive stochastic simulations. This will take advantage of optimizing the experimental design and leave the task of evaluating the probable real-world performance of a limited number of candidate trial designs and analysis procedures.

Physiologically based pharmacokinetic modeling of glycyrrhizic acid, a compound subject to presystemic metabolism and enterohepatic cycling.

Glycyrrhizic acid is currently of clinical interest for treatment of chronic hepatitis. It is also applied as a sweetener in food products and chewing tobacco. In some highly exposed subgroups of the population, serious side effects such as hypertension and electrolyte disturbances have been reported. In order to analyze the health risks of exposure to this compound, the kinetics of glycyrrhizic acid and its active metabolites were evaluated quantitatively. Glycyrrhizic acid and its metabolites are subject to complex kinetic processes, including enterohepatic cycling and presystemic metabolism. In humans, detailed information on these processes is often difficult to obtain. Therefore, a model was developed that describes the systemic and gastrointestinal tract kinetics of glycyrrhizic acid and its active metabolite glycyrrhetic acid in rats. Due to the physiologically based structure of the model, data from earlier in vitro and in vivo studies on absorption, enterohepatic cycling, and presystemic metabolism could be incorporated directly. The model demonstrates that glycyrrhizic acid and metabolites are transported efficiently from plasma to the bile, possibly by the hepatic transfer protein 3-alpha-hydroxysteroid dehydrogenase. Bacterial hydrolysis of the biliary excreted metabolites following reuptake of glycyrrhetic acid causes the observed delay in the terminal plasma clearance of glycyrrhetic acid. These mechanistic findings, derived from analysis of experimental data through physiologically based pharmacokinetic modeling, can eventually be used for a quantitative health risk assessment of human exposure to glycyrrhizic acid containing products.

Estimation of systemic toxicity of acrylamide by integration of in vitro toxicity data with kinetic simulations.

Neurodegenerative properties of acrylamide were studied in vitro by exposure of differentiated SH-SY5Y human neuroblastoma cells for 72 h. The number of neurites per cell and the total cellular protein content were determined every 24 h throughout the exposure and the subsequent 96-h recovery period. Using kinetic data on the metabolism of acrylamide in rat, a biokinetic model was constructed in which the in vitro toxicity data were integrated. Using this model, we estimated the acute and subchronic toxicity of acrylamide for the rat in vivo. These estimations were compared to experimentally derived lowest observed effect doses (LOEDs) for daily intraperitoneal exposure (1, 10, 30, and 90 days) to acrylamide. The estimated LOEDs differed maximally twofold from the experimental LOEDs, and the nonlinear response to acrylamide exposure over time was simulated correctly. It is concluded that the integration of the present in vitro toxicity data with kinetic data gives adequate estimates of acute and subchronic neurotoxicity resulting from acrylamide exposure.