Dual-input Function Research Articles

The Use of Population Pharmacokinetics to Extrapolate Food Effects from Human Adults and Beagle Dogs to the Pediatric Population Illustrated with Paracetamol as a Test Case.

To date, food-drug interactions in the pediatric population remain understudied. The current food effect studies are mostly performed in adults and do not mimic the real-life situation in the pediatric population. Since the potential benefits of food effect studies performed in pediatrics should be counterbalanced with the burden that these studies pose to the patients, alternative research strategies should be evaluated. The present study aimed to evaluate whether population pharmacokinetics (popPK) using data in beagle dogs and human adults could reliably assess food effects relevant for the pediatric population. PopPK was utilized to understand the performance of paracetamol under different dosing conditions (when the participants were fasted, with a reference meal, and with infant formula) in human adults (n = 8) and beagle dogs (n = 6) by constructing models to derive the pharmacokinetic parameters and to evaluate the food effects in both species. A two-compartment model with a single input function for the absorption phase best described the profiles of paracetamol in the beagle dogs. In the human adults, a one-compartment model with a dual input function for the absorption phase best described the data. The simulated profiles for the different dosing conditions demonstrated that both the human adults' and beagle dogs' simulations were able to acceptably describe the plasma concentration-time profiles of paracetamol observed in a representative pediatric population, which opens up perspectives on pediatric-relevant food effect predictions. However, the obtained results should be carefully interpreted, since an accurate validation of these findings was not possible due to the scarcity of the literature on observed pediatric data.

Quantification of the purinergic P2X7 receptor with [11C]SMW139 improves through correction for brain-penetrating radiometabolites

The membrane-based purinergic 7 receptor (P2X7R) is expressed on activated microglia and the target of the radioligand [11C]SMW139 for in vivo assessment of neuroinflammation. This study investigated the contribution of radiolabelled metabolites which potentially affect its quantification. Ex vivo high-performance liquid chromatography with a radio detector (radioHPLC) was used to evaluate the parent and radiometabolite fractions of [11C]SMW139 in the brain and plasma of eleven mice. Twelve healthy humans underwent 90-min [11C]SMW139 brain PET with arterial blood sampling and radiometabolite analysis. The volume of distribution was estimated by using one- and two- tissue compartment (TCM) modeling with single (VT) and dual (VTp) input functions. RadioHPLC showed three major groups of radiometabolite peaks with increasing concentrations in the plasma of all mice and humans. Two radiometabolite peaks were also visible in mice brain homogenates and therefore considered for dual input modeling in humans. 2TCM with single input function provided VT estimates with a wide range (0.10–10.74) and high coefficient of variation (COV: 159.9%), whereas dual input function model showed a narrow range of VTp estimates (0.04–0.24; COV: 33.3%). In conclusion, compartment modeling with correction for brain-penetrant radiometabolites improves the in vivo quantification of [11C]SMW139 binding to P2X7R in the human brain.

Advancing Estimation of Hepatobiliary Clearances in Physiologically Based Pharmacokinetic Models of Rosuvastatin Using Human Hepatic Concentrations.

To estimate hepatobiliary clearances of rosuvastatin via simultaneously fitting to reported human positron emission tomography (PET) data in the liver and gallbladder. A hepatobiliary model incorporating five intrinsic hepatobiliary clearances (active uptake clearance at the sinusoidal membrane, efflux clearance by passive diffusion through the sinusoidal membrane, influx clearance by passive diffusion through sinusoidal membrane, clearance of biliary excretion at the canalicular membrane, and intercompartment clearance from the intrahepatic bile duct to the gallbladder) and three compartments (liver, intrahepatic bile duct, and gallbladder) was developed to simultaneously fit rosuvastatin liver and gallbladder data from a representative subject reported by Billington et al. (1). Two liver blood supply input functions, arterial input function and dual input function (using peripheral venous as an alternative to portal vein), were assessed. Additionally, the predictive performance between the established model and four reported models trained with only systemic exposure data, was evaluated by comparing simulated liver and gallbladder profiles with observations. The established hepatobiliary model well captured the kinetic profiles of rosuvastatin in the liver and gallbladder during the PET scans. Application of dual input function led to a marked underestimation of liver concentrations at the initial stage after i.v. dosing which cannot be offset by altering model parameter values. The simulated hepatobiliary profiles from three of the reported models demonstrated substantial deviation from the observed data. The present study highlights the necessity of using hepatobiliary data to verify and improve the predictive performance of hepatic disposition of rosuvastatin.

Towards Improved Pharmacokinetic Models for the Analysis of Transporter-Mediated Hepatic Disposition of Drug Molecules with Positron Emission Tomography

Positron emission tomography (PET) imaging with radiolabeled drugs holds great promise to assess the influence of membrane transporters on hepatobiliary clearance of drugs. To exploit the full potential of PET, quantitative pharmacokinetic models are required. In this study, we evaluated the suitability of different compartment models to describe the hepatic disposition of [11C]erlotinib as a small-molecule model drug which undergoes transporter-mediated hepatobiliary excretion. We analyzed two different, previously published data sets in healthy volunteers, in which a baseline [11C]erlotinib PET scan was followed by a second PET scan either after oral intake of unlabeled erlotinib (300 mg) or after intravenous infusion of the prototypical organic anion-transporting polypeptide inhibitor rifampicin (600 mg). We assessed a three-compartment (3C) and a four-compartment (4C) model, in which either a sampled arterial blood input function or a mathematically derived dual input function (DIF), which takes the contribution of the portal vein to the liver blood supply into account, was used. Both models provided acceptable fits of the observed PET data in the liver and extrahepatic bile duct and gall bladder. Changes in model outcome parameters between scans were consistent with the involvement of basolateral hepatocyte uptake and canalicular efflux transporters in the hepatobiliary clearance of [11C]erlotinib. Our results demonstrated that inclusion of a DIF did not lead to substantial improvements in model fits. The models developed in this work represent a step forward in applying PET as a tool to assess the impact of hepatic transporters on drug disposition and their involvement in drug-drug interactions.

Kinetic analysis of FDG in rat liver: Effect of dietary intervention on arterial and portal vein input

Dietary conditions may affect liver [(18)F]FDG kinetics due to arterial and portal vein (PV) input. The purpose of this study was to evaluate kinetic models of [(18)F]FDG metabolism under a wide range of dietary interventions taking into account variations in arterial (HA) and portal vein (PV) input. The study consisted of three groups of rats maintained under different diet interventions: 12 h fasted, 24 h fasted and those fed with high fructose diet. [(15)O]H₂O PET imaging was used to characterize liver flow contribution from HA and PV to the liver's dual input function (DIF). [(18)F]FDG PET imaging was used to characterize liver metabolism. Differences in [(18)F]FDG kinetics in HA, PV and liver under different diet interventions were investigated. An arterial to PV Transfer Function (TF) was optimized in all three dietary states to noninvasively estimate PV activity. Finally, two compartment 3-parameter (2C3P), two compartment 4-parameter (2C4P), two compartment 5-parameter (2C5P), and three compartment 5-parameter (3C5P) models were evaluated and compared to describe the kinetics of [(18)F]FDG in the liver across diet interventions. Sensitivity of the compartmental models to ratios of HA to PV flow fractions was further investigated. Differences were found in HA and PV [(18)F]FDG kinetics across 12h fasted, 24h fasted and high fructose fed diet interventions. A two exponential TF model was able to estimate portal activity in all the three diet interventions. Statistical analysis suggests that a 2C3P model configuration was adequate to describe the kinetics of [(18)F]FDG in the liver under wide ranging dietary interventions. The net influx of [(18)F]FDG was lowest in the 12h fasted group, followed by 24 h fasted group, and high fructose diet. A TF was optimized to non-invasively estimate PV time activity curve in different dietary states. Several kinetic models were assessed and a 2C3P model was sufficient to describe [(18)F]FDG liver kinetics despite differences in HA and PV kinetics across wide ranging dietary interventions. The observations have broader implications for the quantification of liver metabolism in metabolic disorders and cancer, among others.

Functional Imaging Techniques for the Evaluation of Hepatocellular Carcinoma Using Dynamic 11C-Acetate PET Imaging

It was widely reported that 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) could not detect 40-50% of hepatocellular carcinoma (HCC), one of the most common malignancies worldwide. Recent research had demonstrated that 11C-acetate (ACT) was a complementary tracer to FDG and these 2 tracers together could maximize the detection accuracy of this tumor. Quantitative functional imaging techniques were, therefore, conducted to further characterize the underlying kinetic basis of this tracer in the detection of HCC. To describe the 11C-acetate molecular kinetic behavior in liver, a three-compartment model with fixed-weight dual-input function was initially proposed, together with a new physiologic parameter defined as the "local hepatic metabolic rate-constant of acetate (LHMRAct)". Preliminary results had shown that the LHMRAct of HCC was significantly higher than that of the non-tumor liver tissue. This tracer kinetic modeling technique provided the first quantitative and kinetic evidence that 11C-acetate was indeed metabolically incorporated in certain types of HCC. In real pathology, however, both tumor and non-tumor liver tissues were actually quite heterogeneous in the distribution and proportion of the two hepatic blood supplies: hepatic artery (HA) and portal vein (PV). To further improve the accuracy of our previous quantitative analysis, the individual proportion of HA/PV in different regions of interest (ROIs) was further studied. An extra parameter called "av", defined as the "relative portal venous contribution to the hepatic blood flow", was proposed (in substitute of the previously fixed weight HA:PV contribution) for the 11C-acetate dual-input liver model. Ten ROIs extracted from six patients were used to test the models with fixed/non-fixed weight dual-input function. The weighted non-linear least squares (NLS) algorithm was used to estimate all the parameters. Results showed that the new model structure could provide better characterization of the 11Cacetate kinetic behavior in liver by statistical study. The analysis was also able to provide a better understanding of the blood supply mechanism in the liver, proposing that the new parameter av, as a quantitatively derived vascular factor, might also provide useful diagnostic information for detection of HCC, particularly in situations when confounding hyperaemic variables such as dysplastic and regenerative nodules coexist in the setting of severe cirrhosis. Keywords: 11C-acetate, dual-input function, local hepatic metabolic rate-constant of acetate (LHMRAct), modeling, parameter estimation, positron emission tomography (PET)

Novel parameter estimation methods for /sup 11/C-acetate dual-input liver model with dynamic PET

The successful investigation of 11C-acetate in positron emission tomography (PET) imaging for marking hepatocellular carcinoma (HCC) has been validated by both clinical and quantitative modeling studies. In the previous quantitative studies, all the individual model parameters were estimated by the weighted nonlinear least squares (NLS) algorithm. However, five parameters need to be estimated simultaneously, therefore, the computational time-complexity is high and some estimates are not quite reliable, which limits its application in clinical environment. In addition, liver system modeling with dual-input function is very different from the widespread single-input system modeling. Therefore, most of the currently developed estimation techniques are not applicable. In this paper, two parameter estimation techniques: graphed NLS (GNLS) and graphed dual-input generalized linear least squares (GDGLLS) algorithms were presented for 11C-acetate dual-input liver model. Clinical and simulated data were utilized to test the proposed algorithms by a systematic statistical analysis. Compared to NLS fitting, these two novel methods achieve better estimation reliability and are computationally efficient, and they are extremely powerful for the estimation of the two potential HCC indicators: local hepatic metabolic rate-constant of acetate and relative portal venous contribution to the hepatic blood flow.

Fast parametric imaging algorithm for dual-input biomedical system parameter estimation

Medical parametric imaging with dynamic positron emission tomography (PET) plays an increasingly potential role in modern biomedical research and clinical diagnosis. The key issue in parametric imaging is to estimate parameters based on sampled data at the pixel-by-pixel level from certain dynamic processes described by valid mathematical models. Classic nonlinear least squares (NLS) algorithm requires a “good” initial guess and the computational time-complexity is high, which is impractical for image-wide parameter estimation. Although a variety of fast parametric imaging techniques have been developed, most of them focus on single input systems, which do not provide an optimal solution for dual-input biomedical system parameter estimation, which is the case of liver metabolism. In this study, a dual-input-generalized linear least squares (D-I-GLLS) algorithm was proposed to identify the model parameters including the parameter in the dual-input function. Monte Carlo simulation was conducted to examine this novel fast algorithm. The results of the quantitative analysis suggested that the proposed technique could provide comparable reliability of the parameter estimation with NLS fitting and accurately identify the parameter in the dual-input function. This method may be potentially applicable to other dual-input biomedical system parameter estimation as well.

Comparison of Parameter Estimations Using Dual-Input and Arterial-Input in Liver Kinetic Studies of FDG Metabolism.

Liver kinetic study of [18F]2-fluoro-2-deoxy-D-glucose (FDG) metabolism in human body is an important tool for functional modeling and glucose metabolic rate estimation. In general, the arterial blood time-activity curve (TAC) and the tissue TAC are required as the input and output functions for the kinetic model. For liver study, however, the arterial-input may be not consistent with the actual model input because the liver has a dual blood supply from the hepatic artery (HA) and the portal vein (PV) to the liver. In this study, the result of model parameter estimation using dual-input function is compared with that using arterial-input function. First, a dynamic positron emission tomography (PET) experiment is performed after injection of FDG into the human body. The TACs of aortic blood, PV blood, and five regions of interest (ROIs) in liver are obtained from the PET image. Then, the dual-input curve is generated by calculating weighted sum of both the arterial and PV input curves. Finally, the five liver ROIs' kinetic parameters are estimated with arterial-input and dual-input functions respectively. The results indicate that the two methods provide different parameter estimations and the dual-input function may lead to more accurate parameter estimation.

Impulse-response function of splanchnic circulation with model-independent constraints: theory and experimental validation.

Modeling physiological processes using tracer kinetic methods requires knowledge of the time course of the tracer concentration in blood supplying the organ. For liver studies, however, inaccessibility of the portal vein makes direct measurement of the hepatic dual-input function impossible in humans. We want to develop a method to predict the portal venous time-activity curve from measurements of an arterial time-activity curve. An impulse-response function based on a continuous distribution of washout constants is developed and validated for the gut. Experiments with simultaneous blood sampling in aorta and portal vein were made in 13 anesthetized pigs following inhalation of intravascular [15O]CO or injections of diffusible 3-O-[11C]methylglucose (MG). The parameters of the impulse-response function have a physiological interpretation in terms of the distribution of washout constants and are mathematically equivalent to the mean transit time (T) and standard deviation of transit times. The results include estimates of mean transit times from the aorta to the portal vein in pigs: T = 0.35 +/- 0.05 min for CO and 1.7 +/- 0.1 min for MG. The prediction of the portal venous time-activity curve benefits from constraining the regression fits by parameters estimated independently. This is strong evidence for the physiological relevance of the impulse-response function, which includes asymptotically, and thereby justifies kinetically, a useful and simple power law. Similarity between our parameter estimates in pigs and parameter estimates in normal humans suggests that the proposed model can be adapted for use in humans.