Two-compartment Model Parameters Research Articles

A systematic review of allometric scaling exponents for IgG mAbs

Increasing complexity of mAbs in development creates challenges in predicting human pharmacokinetic (PK) parameters from preclinical data. The aim of this analysis was to identify optimal allometric scaling exponents. Data were extracted from literature to create a central database (currently the largest available published database) of two-compartment model parameters for mAbs (n = 59) in cynomolgus monkey (CM) and human. Global allometric exponents were calculated and drug-dependent factors were investigated as potential variables in determining the optimal scaling factor. The global exponents for scaling CM mAb PK data were 0.74 (CL), 0.80 (CL with Fc-modified mAbs excluded), 0.44 (CL with Fc-modified mAbs only), 0.71 (Q), 1.12 (V1), and 0.99 (V2). These values are in line with previously published literature values.

Determination of the two-compartment model parameters of exhaled HCN by fast negative photoionization mass spectrometry

Breath exhaled hydrogen cyanide (HCN) has been identified to be associated with several respiratory diseases. Accurately distinguishing the concentration and release rate of different HCN sources is of great value in clinical research. However, there are still significant challenges due to the high adsorption and low concentration characteristics of exhaled HCN. In this study, a two-compartment kinetic model method based on negative photoionization mass spectrometry was developed to simultaneously determine the kinetic parameters including concentrations and release rates in the airways and alveoli. The influences of the sampling line diameter, length, and temperature on the response time of the sampling system were studied and optimized, achieving a response time of 0.2 s. The negative influence of oral cavity-released HCN was reduced by employing a strategy based on anatomical lung volume calculation. The calibration for HCN in the dynamic range of 0.5–100 ppbv and limit of detection (LOD) at 0.3 ppbv were achieved. Subsequently, the experiments of smoking, short-term passive smoking, and intake of bitter almonds were performed to examine the influences of endogenous and exogenous factors on the dynamic parameters of the model method. The results indicate that compared with steady-state concentration measurements, the kinetic parameters obtained using this model method can accurately and significantly reflect the changes in different HCN sources, highlighting its potential for HCN-related disease research.

Optimization of rabies (Rhabdoviridae: Lyssavirus) dog vaccination schedule using a mathematical model

Most cases of human rabies are caused by dog (Canis lupus familiaris) bites. Therefore, the implementation of vaccination programs of these animals is one of the urgent tasks.The work aims to identify the factors influencing the production of antirabies virus-neutralizing antibodies (VNAs) in vaccinated dogs, and to formulate recommendations for adjusting the vaccination schedule using mathematical modeling (MM). We used a fixed-effects modeling procedure to estimate the two-compartment model parameters using log-transformed data (obtained by RFFIT, rapid fluorescent focus inhibition test; and FAVN, fluorescent antibody virus-neutralization test) on the VNAs levels in the serum of vaccinated dogs. More vigorous immune response after a two-dose primary vaccination is formed in juvenile dogs at the age of 3 months to 1 year compared to the adult dogs. Following the primary vaccination and revaccination 1 year after, VNAs were produced more intensively in adult stray dogs than in domestic dogs. The short-term immune response observed in dogs aged up to 3 months is due to the presence of colostral antibodies and the active growth of the organism at this age. The results of our study confirm that most of the dogs have a level of antirabies VNAs of ≥0.5 IU/ml up to two or more years following immunization. However, only regular annual revaccination ensures the protective VNAs level in animals that responded poorly to vaccination due to various factors. The following antirabies vaccination schedule is recommended: primary vaccination of the dog at the age of 3 months up to 1 year with 1-2 month intervals, then revaccination annually. This work also demonstrates the possibility of a wider application of MM methods for solving problems of vaccine prevention.

Effect of pharmacokinetic model misspecification on antibiotic probability of target attainment predicted by Monte Carlo simulation .

The first aim of this study was to compare the predictability of efficacy by Monte Carlo simulation between a true one-compartment model and a true two-compartment model for doripenem. The second aim was to explore how we can identify the usefulness of a one-compartment model when the pharmacokinetic/pharmacodynamic (PK/PD) indices between three misspecified one-compartment models and a true two-compartment model are compared. The reported two-compartment model parameters of two doripenem studies and a vancomycin study were used to generate 200 virtual concentration-time profiles for each study. Sparse and dense sampling designs were selected to build the one- and two-compartment models, respectively. The probability of target attainment (PTA) for the PK/PD indices were compared between the one- and two-compartment models of the same drug, applying the clinical breakpoint distribution of minimum inhibitory concentrations (MICs). The simulated concentration-time profiles reproduced the original data well. In addition, PTAs were similar between the one- and two-compartment models when infusion time and MIC were the same in the doripenem studies. For vancomycin simulations, the maximum difference was 65.9% between a misspecified one-compartment model and the true two-compartment model. When a misspecified one-compartment model was established with sparse sampling data, the PTA was significantly different from that of the two-compartment model. Thus, a useful PK model must be verified through diagnostic plots and visual predictive checks and the range of sampling time should be sufficient to explain the PK of a drug.

Predicting pharmacokinetic profile of therapeutic antibodies after iv injection from only the data after sc injection in cynomolgus monkey

1. The number of developed therapeutic monoclonal antibodies (mAbs) has increased in this decade. This study aims to predict their pharmacokinetic profiles after intravenous (iv) injection using only the data taken after subcutaneous (sc) injection in cynomolgus monkey.2. Two-compartment model parameters, Q, Vc and Vp, were collected from the published data after iv injection in cynomolgus monkey for 21 mAbs (Group A). Bioavailability after sc injection (F), CL and serum/plasma concentration after iv injection of other published 19 mAbs (Group B) were predicted using the estimated geometric means of Q, Vc and Vp in Group A and the serum/plasma concentration after sc injection in Group B.3. F and CL of 18 out of 19 mAbs in Group B were successfully predicted within 30% difference of observed value. Moreover, most of the observed serum/plasma concentrations after iv injection of mAbs in Group B were successfully predicted within 2-fold difference. Our approach suggests that iv injection might not be required to evaluate absorption of mAbs after sc injection in cynomolgus monkey. Therefore, our approach might reduce the time and cost of drug development, reduce the burden on resources, and also contribute to animal welfare.

Prediction of drug concentration-time data in humans from animals: a comparison of three methods

The main objective of this work is to evaluate three methods to predict concentration-time data of drugs in humans in a multi-compartment system using animal pharmacokinetic parameters following intravenous administration. The prediction of concentration-time data in humans in a multi-compartment system was based on two proposed methods of Mordenti. The third method was based on the assumption that all drugs follow a single-compartment system.Ten drugs from the literature were chosen that were described by two-compartment model in both human and animals. Two-compartment model parameters (CL, Vc, Vss, Vβ, α, A, β and B) of at least 3 animals were scaled to humans and then were used to predict plasma concentrations-time data in humans. Allometrically scaled pharmacokinetic parameters from animals were also used to predict human profile using one-compartment model as a comparison.The results indicated that in a multi-compartment system, application of pharmacokinetic constants provided better prediction of concentration-time data in humans than the assumption that all drugs follow a single-compartment model. Both the proposed methods of Mordenti provided almost similar concentration-time profiles for most of the drugs. For some drugs, predicted α values were substantially higher than the observed values. This prediction error in α resulted in under-prediction of drug concentrations in distribution phase. In order to reduce the prediction error in α, Waijma’s method for the prediction of α was modified which resulted in an improved prediction of concentration-time data in humans. Overall, Mordenti’s proposed 2 methods and where necessary by modifying Waijma’s method for the prediction of α can be used for reasonably accurate prediction of concentration-time data of drugs in humans.

Volume kinetics of 6% hydroxyethyl starch 130/0.4 in healthy volunteers

Objective To investigate the volume kinetics of 6% hydroxyethyl starch 130/0.4 in healthy volunteers.Methods Seven healthy volunteers aged 18-32 yr weighing 46-84 kg were selected in this study. 6% hydroxyethyl starch 130/0.4 30 ml/kg was infused over 60 min. Volume kinetics analysis of 6% hydroxyethyl starch 130/0.4 was performed with Matlab 6.0 software, compartment model was determined by F test.Results One-compartment model parameters: basic clearance, clearance and distribution volume of one-compartment model were (3.5 ± 1.3) ml/min,(19± 11) ml/min and (5746 ± 1371) ml respectively. Two-compartment model parameters: clearance, K1, the volume of central compartment, the volume of peripheral compartment, distribution volume of two-compartment model were (63 ±29) ml/min,(11 ±4) ml/min, (1551 ± 995) ml, (908 ±398) ml,(2460 ± 1332) ml respectively. There was no difference between the distribution volume of one-compartment model and blood volume of healthy volunteers ( P ＞ 0.05) .The distribution of infused 6% hydroxyethyl starch 130/0.4 was accordant with one-compartment model (F value was 3.81, P ＞ 0.05)and 4 h clearance was (75 ± 10)% .Conclusion The distribution of infused 6% hydroxyethyl starch 130/0.4 for volume expansion is accordant with one-compartment model, and the effective duration of plasma volume expansion is 4 h. Key words: Hetastarch; Fluid therapy; Kinetics

Comparison of tumor histology to dynamic contrast enhanced magnetic resonance imaging-based physiological estimates

The purpose of this study was to compare histologically determined cellularity and extracellular space to dynamic contrast-enhanced magnetic resonance imaging (DCE MRI)-based maps of a two-compartment model's parameters describing tumor contrast agent extravasation, specifically tumor extravascular extracellular space (EES) volume fraction (ve), tumor plasma volume fraction (vp) and volume-normalized contrast agent transfer rate between tumor plasma and interstitium (KTRANS/VT). Obtained ve, vp and KTRANS/VT maps were estimated from gadolinium diethylenetriamine penta-acetic acid DCE T1-weighted gradient-echo images at resolutions of 469, 938 and 2500 microm. These parameter maps were compared at each resolution to histologically determined tumor type, and the high-resolution 469-microm maps were compared with automated cell counting using Otsu's method and a color-thresholding method for estimated intracellular (Vintracellular) and extracellular (Vextracellular) space fractions. The top five KTRANS/VT values obtained from each tumor at 469 and 938 microm resolutions are significantly different from those obtained at 2500 microm (P<.0001) and from one another (P=.0014). Using these top five KTRANS/VT values and the corresponding tumor EES volume fractions ve, we can statistically differentiate invasive ductal carcinomas from noninvasive papillary carcinomas for the 469- and 938-microm resolutions (P=.0017 and P=.0047, respectively), but not for the 2500-microm resolution (P=.9008). The color-thresholding method demonstrated that ve measured by DCE MRI is statistically similar to histologically determined EES. The Vextracellular obtained from the color-thresholding method was statistically similar to the ve measured with DCE MRI for the top 10 KTRANS/VT values (P>.05). DCE MRI-based KTRANS/VT estimates are not statistically correlated with histologically determined cellularity. DCE MRI estimates of tumor physiology are a limited representation of tumor histological features. Extracellular spaces measured by both DCE MRI and microscopic analysis are statistically similar. Tumor typing by DCE MRI is spatial resolution dependent, as lower resolutions average out contributions to voxel-based estimates of KTRANS/VT. Thus, an appropriate resolution window is essential for DCE MRI tumor diagnosis. Within this resolution window, the top KTRANS/VT values with corresponding ve are diagnostic for the tumor types analyzed in this study.

Parameter-extraction of a two-compartment model for whole-cell data analysis

Neuronal modeling of patch-clamp data is based on approximations which are valid under specific assumptions regarding cell properties and morphology. Certain cells, which show a biexponential capacitance transient decay, can be modeled with a two-compartment model. However, for parameter-extraction in such a model, approximations are required regarding the relative sizes of the various model parameters. These approximations apply to certain cell types or experimental conditions and are not valid in the general case. In this paper, we present a general method for the extraction of the parameters in a two-compartment model without assumptions regarding the relative size of the parameters. All the passive electrical parameters of the two-compartment model are derived in terms of the available experimental data. The experimental data is obtained from a DC measurement (where the command potential is a hyperpolarizing DC voltage) and an AC measurement (where the command potential is a sinusoidal stimulus on a hyperpolarized DC potential) performed on the cell under test. Computer simulations are performed with a circuit simulator, XSPICE, to observe the effects of varying the two-compartment model parameters on the capacitive transients of the current response. Our general solution for the parameter-estimation of a two-compartment model may be used to model any neuron, which has a biexponential capacitive current decay. In addition, our model avoids the need for simplifying and perhaps erroneous approximations. Our equations may be easily implemented in hardware/software compensation schemes to correct the recorded currents for any series resistance or capacitive transient errors. Our general solution reduces to the results of previous researchers under their approximations.

CFD analysis of turbulence non-homogeneity in mixing vessels: A two-compartment model

A two-compartment model has been developed for calculating the droplet/particle size distribution in suspension polymerization reactors by taking into account the large spatial variations of the turbulent kinetic energy and its dissipation rate in the vessel. The two-compartment model comprised two mixing zones, namely an impeller zone of high local energy dissipation rates and a circulation zone of low kinetic energy. Computational fluid dynamics (CFD) was employed for generating the spatial distribution of energy dissipation rates within an unbaffled mixing vessel agitated by a flat two-blade impeller. A general methodology was developed for extracting, from the results of the CFD simulations, the volume ratio of the impeller over the circulation zone, the ratio of the average turbulent dissipation rates in the two zones, and the exchange flow rate between the two compartments. The effect of agitation rate, continuous phase viscosity, impeller diameter, and mixing vessel scale on the two-compartment model parameters was elucidated. The two-compartment model was then applied to a non-homogeneous liquid–liquid dispersion process to calculate the time evolution of the droplet size distribution in the mixing vessel. An excellent agreement was obtained between theoretical and experimental results on droplet size distributions obtained from a laboratory-scale reactor operated over a wide range of experimental conditions.

Peripheral limitations to exercise

We present a computer simulation of a two-compartment model of the systemic circulation which demonstrates how this model can be used to understand the mechanism(s) for the maximal exercise cardiac output (Q). The model consists of two parallel vascular channels, the splanchnic channel (all blood draining through the hepatic veins) and the peripheral channel (all other vascular beds). The distinguishing characteristic of each channel is the product of its venous compliance and venous resistance. Model parameters for the human circulation were estimated from similar parameters obtained directly from animal experiments. "Exercise" was achieved by decreasing the compliance of both channels to 40% of their initial value and by redistributing the Q such that the fraction of Q perfusing the splanchnic channel fell from 38 to 5%, while that perfusing the peripheral channel (skeletal muscles) increased from 62 to 95%. These combined changes increased Q from 4.4 to 22.0 l X min-1 and suggest that maximal adjustments of the two-compartment model parameters lead to a prediction of a maximal Q that approaches the maximal Q usually obtained by humans during exercise.

An incremental method for the study of the absorption of drugs whose kinetics are described by a two-compartment model: estimation of the microscopic rate constants.

A method is proposed for estimating the overall absorption kinetics of drugs (expressed as percent of total amount absorbed versus time) from plasma data. It is applicable to the study of drugs whose kinetics can be described by linear one- or two-compartment models. Use is made of an iterative process based on the differential equations of the model and on linear interpolation of plasma data. The method does not require that the overall absorption kinetics should be apparent first-order and/or that the model parameters should be estimated from a previous experiment. It was tested for the influence of data scatter: added noise (CV = 10%) resulted in a variability of percent absorbed versus time of the same order of magnitude. During the calculations, the microscopic rate constants are estimated and optimalized. Data scatter resulted in wide variations in the estimates of the two-compartment model parameters. However, when a sufficiently large number of plasma concentration-time curves were studied, an average model could be determined with a reasonable precision. Model kinetics calculated from the related parameter estimates were in agreement with the theory. The method permits the exploitation of the various plasma concentration-time curves which are available after the development of an orally administered drug.