Biomedical subjects

Davide Verotta

Publications and source records attributed to Davide Verotta.

17 recordsLinked to original sources

PubMed2007

Reversible jump Markov chain Monte Carlo for deconvolution.

To solve the problem of estimating an unknown input function to a linear time invariant system we propose an adaptive non-parametric method based on reversible jump Markov chain Monte Carlo (RJMCMC). We use piecewise polynomial functions (splines) to represent the input function. The RJMCMC algorithm allows the exploration of a large space of competing models, in our case the collection of splines corresponding to alternative positions of breakpoints, and it is based on the specification of transition probabilities between the models. RJMCMC determines: the number and the position of the breakpoints, and the coefficients determining the shape of the spline, as well as the corresponding posterior distribution of breakpoints, number of breakpoints, coefficients and arbitrary statistics of interest associated with the estimation problem. Simulation studies show that the RJMCMC method can obtain accurate reconstructions of complex input functions, and obtains better results compared with standard non-parametric deconvolution methods. Applications to real data are also reported.

Algorithms↗

PubMed2006

Improving data reliability using a non-compliance detection method versus using pharmacokinetic criteria.

Data from clinical trials present numerous problems for the data analyst. These include non-compliance with the prescribed dosing regimen and inaccurate recollection of dosing history by patients as well as mistakes in recording data. Several methods have been proposed to address these issues. One such technique by Lu et al. (Selecting reliable pharmacokinetic data for explanatory analyses of clinical trials in the presence of possible noncompliance. J. Pharmacokinet. Pharmacodyn. 28:343-362 (2001)) identifies occasions in pharmacokinetic (PK) data where the preceding dosing history is likely to be unreliable. We used this method, implemented in the software program NONMEM (beta) VI, to clean a dataset containing indinavir (IDV) plasma concentrations from HIV-1 infected patients. The data was also cleaned by inspection in Microsoft Excel using clinical PK criteria. A one-compartment model with first order absorption and elimination was fit to both sets of cleaned data. IDV population PK parameters obtained from these analyses were similar to those reported previously. It is established that IDV nephrotoxicity is related to high IDV exposure. However, no relationships were found between any PK parameters and nephrotoxicity in the "compliance cleaned" dataset. In the "PK cleaned" dataset, the oral clearance and apparent volume were lower by 9.1% and 6.6%, respectively in patients with any type of nephrotoxicity and the maximum IDV concentration (C(max)) was 12.1% higher. In patients suffering from nephrolithiasis in particular, C(max) was 15.5% higher. Accordingly, the use of the non-compliance detection method did not improve the reliability of our dataset over the usual method of applying clinical criteria. In fact, analyses on the compliance-cleaned dataset missed some exposure-toxicity relationships. Thus, automated methods must be tested rigorously with 'real life' datasets, used with caution, and always in conjunction with clinical reasoning to avoid overlooking a signal in noisy data.

Adult↗

PubMed2006

A non-linear mixed effect dynamic model incorporating prior exposure and adherence to treatment to describe long-term therapy outcome in HIV-patients.

Long term therapy with antiretroviral agents in HIV-infected patients often result in failure to suppress the virus load. Imperfect adherence to prescribed antiviral drugs is an important factor explaining the resurgence of virus. A better understanding of the factors responsible for the virological failure is important for the development of new treatment strategies. Many complex non-linear models have been developed to describe and simulate the dynamics of HIV-1 virus. Those complicated viral dynamic models have not been used in clinical trials to estimate HIV dynamics parameters, due to their complexity, until the recent development of simplification and approximation techniques. The estimation of the parameters associated with the dynamics from real data has been mostly limited to linearized models that can only explain the decay (suppression) of the virus following antiviral treatment. Moreover, no complete characterization of typical clinical data in terms of inter-subject variability and identification of important covariates effecting HIV-1 dynamics has been attempted. The objective of our paper was to develop a hierarchical non-linear mixed effect model characterizing inter-subject variability in the long-term response to treatment of HIV-1 RNA, and show how the model can be used to quantify the effect of important covariates, such as physiological variables, adherence to treatment or previous exposure to treatment, on the dynamics of HIV-1 RNA. As an example we report the analysis of AIDS clinical trial data from AACTG 398, which shows that patients with previous exposure to treatment show faster death rates for HIV-1, and that higher adherence to treatment is associated with lower reproductive ratio.

Algorithms↗

PubMed2006

Pharmacokinetic-pharmacodynamic modelling: history and perspectives.

A major goal in clinical pharmacology is the quantitative prediction of drug effects. The field of pharmacokinetic-pharmacodynamic (PK/PD) modelling has made many advances from the basic concept of the dose-response relationship to extended mechanism-based models. The purpose of this article is to review, from a historical perspective, the progression of the modelling of the concentration-response relationship from the first classic models developed in the mid-1960s to some of the more sophisticated current approaches. The emphasis is on general models describing key PD relationships, such as: simple models relating drug dose or concentration in plasma to effect, biophase distribution models and in particular effect compartment models, models for indirect mechanism of action that involve primarily the modulation of endogenous factors, models for cell trafficking and transduction systems. We show the evolution of tolerance and time-variant models, non- and semi-parametric models, and briefly discuss population PK/PD modelling, together with some example of more recent and complex pharmacodynamic models for control system and nonlinear HIV-1 dynamics. We also discuss some future possible directions for PK/PD modelling, report equations for general classes of novel semi-parametric models, as well as describing two new classes, additive or set-point, of regulatory, additive feedback models in their direct and indirect action variants.

Algorithms↗

PubMed2006

Population analyses of amlodipine in patients living in the community and patients living in nursing homes.

OBJECTIVE: Our objective was to determine the effects of age, sex, and morbidity on the apparent oral clearance (CL/F) of amlodipine. METHODS: Population pharmacokinetic analyses were performed on data from 211 patients receiving oral racemic amlodipine (dose of 7.2 +/- 3.6 mg/d [mean +/- SD]) on a long-term basis. Of the patients, 105 were men, with a mean age of 72 +/- 13 years and lean body weight (LBW) of 60.7 +/- 7.6 kg, and 106 were women, with a mean age of 79 +/- 11 years and LBW of 44.2 +/- 6.0 kg; 119 lived in the community, 20 in assisted living facilities, and 72 in nursing homes. Amlodipine was measured by liquid chromatography-tandem mass spectrometry. Population analyses were performed by use of NONMEM with sex, age, race, living site, alcohol intake, and concomitant medications considered as covariates. The significance of covariates was determined by likelihood ratio tests. RESULTS: Female sex and living in a nursing home were associated with a faster CL/F compared with men and community-dwelling patients, respectively. The mean CL/F was 7.83 +/- 0.50 mL.min(-1).kg(-1) (LBW) in women compared with 6.31 +/- 1.01 in men and 8.68 +/- 1.00 mL.min(-1).kg(-1) in nursing home residents compared with 6.32 +/- 1.17 in community-dwelling patients. Increasing age was associated with decreasing CL/F only in community-dwelling patients and residents of assisted living facilities. CONCLUSIONS: In middle-aged and very old (>80 years) patients, amlodipine CL/F was faster in women compared with men and was faster in nursing home residents compared with community-dwelling patients, with increasing age decreasing CL/F only in community-dwelling patients and residents of assisted-living facilities.

Aged↗

PubMed2005

The use of a sum of inverse Gaussian functions to describe the absorption profile of drugs exhibiting complex absorption.

PURPOSE: The aim of this study was to evaluate the utility of a parametric deconvolution method using a sum of inverse Gaussian functions (IG) to characterize the absorption and concentrations vs. time profile of drugs exhibiting complex absorption. METHODS: For a linear time-invariant system the response, Y(t), following an arbitrary input function I(t), is the convolution of I(t) with the disposition function, H(t), of the system: [Formula: see text]. The method proposed uses a sum of n inverse Gaussian functions to characterize I(t). The approach was compared with a standard nonparametric method using linear splines. Data were provided from previously published studies on two drugs (hydromorphone and veralipride) showing complex absorption and analyzed with NONMEM. RESULTS: A satisfactory fit for hydromorphone and veralipride data following oral administration was achieved by fitting a sum of two or three IG functions. The predictions of the input functions were very similar to those using linear splines. CONCLUSIONS: The use of a sum of IG as opposed to nonparametric functions, such as splines, offers a simpler implementation, a more intuitive interpretation of the results, a built-in extrapolation, and an easier implementation in a population context. Disadvantages are an apparent greater sensitivity to initial value estimates (when used with NONMEM).

Algorithms↗

PubMed2005

Mechanistic pharmacokinetic and pharmacodynamic modeling of CHF3381 (2-[(2,3-dihydro-1H-inden-2-yl)amino]acetamide monohydrochloride), a novel N-methyl-D-aspartate antagonist and monoamine oxidase-A inhibitor in healthy subjects.

CHF3381 (2-[(2,3-dihydro-1H-inden-2-yl)amino]acetamide monohydrochloride) is a new N-methyl-D-aspartate antagonist and reversible monoamine oxidase-A (MAO-A) inhibitor in development for the treatment of neuropathic pain. This study developed a mechanistic model to describe the pharmacokinetics of CHF3381 and of its two metabolites, the relationship with MAO-A activity and heart rate. Doses of 100, 200, and 400 mg twice daily for 2 weeks were administered orally to 36 subjects. MAO-A activity was estimated by measuring concentrations of 3,4-dihydroxyphenylglycol (DHPG), a stable metabolite of norepinephrine. A multicompartment model with time-dependent clearance was used to describe the kinetics of CHF3381 and metabolite concentrations. Estimated pharmacokinetic parameters were CL (41.2 to 27.4 l/h over the study), V (131 liters), Q (1.7 l/h), V(p) (36 liters), and k(a) (1.85 h(-1)). The relationship between CHF3381 and DHPG or heart rate was described using an indirect or a direct linear model, respectively. The production rate of DHPG (k(in)) was 2540 ng . h(-1), reduced by 63% at maximal CHF3381 concentrations. EC(50) was 1670 mug/l, not significantly different from the in vitro IC(50). The increase in heart rate due to CHF3381 was 0.0055 bpm/micro(g l-1). CHF3381 produces a concentration-dependent decrease in DHPG plasma concentrations, whose magnitude increased after multiple twice-a-day regimens for 14 days.

Adult↗

PubMed2005

Sample size computations for PK/PD population models.

We describe an accurate, yet simple and fast sample size computation method for hypothesis testing in population PK/PD studies. We use a first order approximation to the nonlinear mixed effects model and chi-square distributed Wald statistic to compute the minimum sample size to achieve given degree of power in rejecting a null hypothesis in population PK/PD studies. The method is an extension of Rochon's sample size computation method for repeated measurement experiments. We compute sample sizes for PK and PK/PD models with different conditions, and use Monte Carlo simulation to show that the computed sample size retrieves the required power. We also show the effect of different sampling strategies, such as minimal, i.e., as many observations per individual as parameters in the model, and intensive on sample size. The proposed sample size computation method can produce estimates of minimum sample size to achieve the desired power in hypothesis testing in a greatly reduced time than currently available simulation-based methods. The method is rapid and efficient for sample size computation in population PK/PD study using nonlinear mixed effect models. The method is general and can accommodate any type of hierarchical models. Simulation results suggest that intensive sampling allows the reduction of the number of patients enrolled in a clinical study.

Algorithms↗

PubMed2005

A predictive model for exemestane pharmacokinetics/pharmacodynamics incorporating the effect of food and formulation.

AIMS: Exemestane (Aromasin) is an irreversible aromatase inactivator used for the treatment of postmenopausal women with advanced breast cancer. The objective of this study was to evaluate the effect of formulation comparing a sugar-coated tablet (SCT) with a suspension and food on the pharmacokinetics (PK) and pharmacodynamics (PD) with respect to plasma estrone sulphate (E1S) concentrations of exemestane, using a PK/PD approach. METHODS: This was an open, three-period, randomized, crossover study. Twelve healthy postmenopausal women received single oral doses of 25 mg exemestane as a SCT after fasting or food and as a suspension after fasting. Exemestane and E1S concentrations were determined before and up to 14 days after drug administration. Population analysis was performed in two steps: (i) a compartmental PK model was selected incorporating the effect of food and formulation; (ii) conditional on the PK model, a PD model was developed employing indirect response models. Model selection was performed using standard statistical tests. Validation and assessment of the predictive capability of the selected model was performed using real test data sets obtained from the literature. RESULTS: A three-compartment model with first-order elimination rate best described exemestane disposition (k12 0.454, k21 0.158, k13 0.174, k31 0.016 and k 0.738 h(-1)). Absorption was described by a mono-exponential function [ka 2.3 (SCT after fasting), 1.1 (SCT after food) and 7.6 h(-1) (suspension); lag time 0.2 h]. The PD model assumed that E1S plasma concentrations are determined by a zero-order synthesis rate (6.5 pg ml(-1) h(-1)) and a first-order elimination constant (0.032 h(-1)). Exemestane inhibited E1S synthesis with a C50 value of 22.1 pg ml(-1). The mean population estimates were used to simulate the administration of different doses of the drug (0.5, 1, 2.5, 5 and 25 mg day(-1)). The model predictions were in agreement with historical data. CONCLUSIONS: Exemestane absorption is influenced by the formulation of the drug and by food, but its disposition is independent of both. PK differences do no translate into clinically important differences in the PD. The PK/PD model developed was able to predict successfully the response to different doses and administration schedules with respect to oestrogen suppression.

Administration, Oral↗

PubMed2004

A sample size computation method for non-linear mixed effects models with applications to pharmacokinetics models.

We propose a simple method to compute sample size for an arbitrary test hypothesis in population pharmacokinetics (PK) studies analysed with non-linear mixed effects models. Sample size procedures exist for linear mixed effects model, and have been recently extended by Rochon using the generalized estimating equation of Liang and Zeger. Thus, full model based inference in sample size computation has been possible. The method we propose extends the approach using a first-order linearization of the non-linear mixed effects model and use of the Wald chi(2) test statistic. The proposed method is general. It allows an arbitrary non-linear model as well as arbitrary distribution of random effects characterizing both inter- and intra-individual variability of the mixed effects model. To illustrate possible uses of the method we present tables of minimum sample sizes, in particular, with an illustration of the effect of sampling design on sample size. We demonstrate how (D-)optimal or frequent sampling requires fewer subjects in comparison to a sparse sampling design. We also present results from Monte Carlo simulations showing that the computed sample size can produce the desired power. The proposed method greatly reduces computing times compared with simulation-based methods of estimating sample sizes for population PK studies.

Black People↗

PubMed2004

CSF quinolinic acid levels are determined by local HIV infection: cross-sectional analysis and modelling of dynamics following antiretroviral therapy.

Quinolinic acid (QUIN) is a product of tryptophan metabolism that can act as an endogenous brain excitotoxin when released by activated macrophages. Previous studies have shown correlations between increased CSF QUIN levels and the presence of the AIDS dementia complex (ADC), a neurodegenerative condition complicating late-stage human immunodeficiency virus type 1 (HIV) infection in some patients. CSF QUIN is putatively one of the important molecular mediators of the brain injury in this clinical setting and, more generally, serves as a marker of local macrophage activation. This study was undertaken to examine the relationship of CSF QUIN concentrations to local HIV infection and to define the effects of antiretroviral drug treatment on CSF QUIN using two complementary approaches. The first was an exploratory cross-sectional analysis of a clinically heterogeneous sample of 62 HIV-infected subjects, examining correlations of CSF QUIN levels with CSF and plasma HIV RNA levels and other salient parameters of infection. The second involved longitudinal observations of a subset of 20 of these subjects who initiated new antiretroviral therapy regimens. In addition to descriptive analysis, we used kinetic modelling of QUIN decay in relation to that of HIV RNA to assess further the relationship between CSF QUIN and infection in the dynamic setting of treatment. The cross-sectional studies showed strong correlations of CSF QUIN with both CSF HIV RNA and blood QUIN levels, as well as with elevations in CSF white blood cells, CSF total protein and CSF:blood albumin ratio. In this group of subjects with a low incidence of active, untreated ADC, CSF QUIN did not correlate with ADC stage or measures of quantitative neurological performance. Antiviral treatment reduced the CSF QUIN levels in all the longitudinally followed, treated subjects. Kinetic modelling of CSF QUIN decay indicated that CSF QUIN levels were driven primarily by CSF HIV infection with a lesser contribution from blood QUIN levels. In three subjects with new-onset, untreated ADC, CSF QUIN decay paralleled both CSF HIV decrement and improvement in neurological performance. These studies show that CSF QUIN concentrations relate primarily to active CSF HIV infection and to a lesser extent to plasma QUIN. CSF QUIN serves as a marker of local infection with a wide dynamic range. The time course of therapy-induced changes links CSF QUIN to local infection and supports the action of antiviral therapy in ameliorating immunopathological brain injury and ADC.

AIDS Dementia Complex↗

PubMed2003

Volterra series in pharmacokinetics and pharmacodynamics.

Nonparametric black-box modeling has a long successful history of applications in pharmacokinetics (PK) (notably in deconvolution), but is rarely used in pharmacodynamics (PD). The main reason is associated with the fact that PK systems are often linear in respect to drug inputs, while the reverse is true for many PK/PD systems. In the PK/PD field existing non-parametric methods can deal with linear systems, but they cannot describe non-linear systems. Our purpose is to describe a novel implementation of a general nonparametric model which can represent non-linear systems, and in particular non-linear PK/PD systems, The model is based on a Volterra series, which is an integral series expansion of the response of a system in terms of its kernels and the inputs to the system. In PK we are familiar with the first term of the Volterra series, the convolution of the first kernel of the system (the so-called PK disposition function) with drug input rates. The main advantages of higher order Volterra representations is that they are general representations and can be used to describe and predict the response of an arbitrary (PK/ PD) system without any prior knowledge on the structure of the system. The main problem of the representation is that in a non-parametric representation of the kernels the number of parameters to be estimated grows geometrically with the order of the kernel. We developed a method to estimate the kernels in a Volterra-series which overcomes this problem. The method (i) is fully non-parametric (the kernels are represented using multivariate splines), (ii) is maximum-likelihood based, (iii) is adaptive (the order of the series and the dimensionality of each kernel is selected by the method), and (iv) allows for non-equispaced observations (thus allowing a reduction of the number of parameters in the representation, and the analysis of, e.g., PK/PD observations). The method is based on an adaptation of Friedmans's Multivariate Adaptive Regression Spline method. Examples demonstrate the possible application of the approach to the analysis of different PK/PD systems.

Algorithms↗

PubMed2003

Population analyses of sustained-release verapamil in patients: effects of sex, race, and smoking.

OBJECTIVE: Our objective was to determine the effects of age, sex, and sustained-release formulation on apparent oral clearance of sustained-release racemic verapamil in patient populations. METHODS: Population pharmacokinetic analyses were performed on data from 186 patients with hypertension, coronary artery disease, or supraventricular arrhythmias who were receiving long-term sustained-release oral racemic verapamil (Covera SR in 105 patients, Calan SR in 67 patients, and other formulations in 14 patients; mean +/- SD dose, 280 +/- 139 mg) for clinical care or as a part of phase III efficacy studies. Of those 186 patients, 135 were men (age, 63 +/- 12 years; ideal body weight, 70.7 +/- 6.6 kg) and 51 were women (age, 60 +/- 17 years; ideal body weight, 53.7 +/- 7.2 kg). Verapamil was measured by HPLC, and population analyses were performed by use of NONMEM software. Sex, age, and formulation were the covariates considered in the population model building. Subgroup analyses of race, smoking, and alcohol consumption were also performed. Significance of covariates was determined by likelihood ratio tests. RESULTS: Sex significantly affected steady-state clearance of oral sustained-release racemic verapamil. Apparent oral clearance of sustained-release verapamil was 23.8 +/- 2.3 mL/min per kilogram in women compared with 18.6 +/- 3.4 mL/min per kilogram in men. Clearance estimates were faster in black subjects compared with white subjects, as well as in smokers compared with nonsmokers. Effects of age, formulation, and alcohol consumption were not detected. CONCLUSIONS: In middle-aged and older patients, apparent oral clearance of sustained-release racemic verapamil was affected by sex (faster in women compared with men), race (faster in black subjects compared with white subjects), and smoking (faster in smokers compared with nonsmokers) but not by age, alcohol, or formulation.

Administration, Oral↗

PubMed2002

Non-linear dynamics models characterizing long-term virological data from AIDS clinical trials.

Human immunodeficiency virus (HIV) dynamics represent a complicated variant of the text-book case of non-linear dynamics: predator-prey interaction. The interaction can be described as naturally reproducing T-cells (prey) hunted and killed by virus (predator). Virus reproduce and increase in number as a consequence of successful predation; this is countered by the production of T-cells and the reaction of the immune system. Multi-drug anti-HIV therapy attempts to alter the natural dynamics of the predator-prey interaction by decreasing the reproductive capability of the virus and hence predation. These dynamics are further complicated by varying compliance to treatment and insurgence of resistance to treatment. When following the temporal progression of viral load in plasma during therapy one observes a short-term (1-12 weeks) decrease in viral load. In the long-term (more than 12 weeks from the beginning of therapy) the reduction in viral load is either sustained, or it is followed by a rebound, oscillations and a new (generally lower than at the beginning of therapy) viral load level. Biomathematicians have investigated these dynamics by means of simulations. However the estimation of the parameters associated with the dynamics from real data has been mostly limited to the case of simplified, in particular linearized, models. Linearized model can only describe the short-term changes of viral load during therapy and can only predict (apparent) suppression. In this paper we put forward relatively simple models to characterize long-term virus dynamics which can incorporate different factors associated with resurgence: (Fl) the intrinsic non-linear HIV-1 dynamics, (F2) drug exposure and in particular compliance to treatment, and (F3) insurgence of resistant HIV-1 strains. The main goal is to obtain models which are mathematically identifiable given only measurements of viral load, while retaining the most crucial features of HIV dynamics. For the purpose of illustration we demonstrate an application of the models using real AIDS clinical trial data involving patients treated with a combination of anti-retroviral agents using a model which incorporates compliance data.

Acquired Immunodeficiency Syndrome↗

PubMed2002

Influence of arterial vs. venous sampling site on nicotine tolerance model selection and parameter estimation.

In this modeling study we utilize previously published nicotine pharmacokinetic (PK) and pharmacodynamic (PD, heart rate) data to investigate the influence of PK sampling site (venous vs. arterial) on the selection of a specific PD tolerance model and estimation of its parameters. We describe a general model for tolerance which includes as special cases feedback (TF), and kinetic based tolerance (TK) models. A TK model has arterial plasma drug concentrations (Ca) driving (hypothetical) effect (Ce) and antagonist (Cm) site concentrations, which drive a non-feedback effect (Enf): tolerance depends on the relative rate of equilibration of Ce and Cm with Ca. The TF model adds feedback which makes tolerance depend on Enf, not just on drug kinetics for nicotine. The arterial-sampling-analysis (PKPDa) has Ca driving Ce and Cm. The venous-sampling-analysis (PKPDv) does the same but estimates Ca from venous data by means of deconvolution. A TF model (with Cm = Ce) was always selected in the PKPDa. According to this model tolerance developed rapidly with a median half-life of 6.6 min, and median decrease of effect due to tolerance of 31%. Different variants of the TF or TK models were selected in the PKPDv. Parameter estimates for PKPDv show higher variability, and, for the TF model, lower rate and extent of tolerance development and threefold increase in EC50. The study shows that (i) TF models are more appropriate than TK models to describe nicotine effect data, (ii) venous sampling may lead to incorrect model selection and inaccurate and imprecise parameter estimation in respect to arterial sampling, and (iii) arterial sampling should be preferred for accurate (non-steady-state) PD modeling.

Arteries↗

PubMed2002

Modeling nicotine arterial-venous differences to predict arterial concentrations and input based on venous measurements: application to smokeless tobacco and nicotine gum.

Significant arterio-venous differences in nicotine concentrations have been observed during and after cigarette smoking, nicotine nasal spray, and intravenous nicotine administration. In this paper we describe a novel mathematical method for estimating arterial blood levels from venous blood level data. The model allows to quantify: (i) the influence of the microcirculation in the hands and forearm on the distribution of nicotine, and (ii) the influence of disregarding the venous to arterial circulation in the estimate of systemic inputs. We also (iii) propose a general method to predict arterial concentrations and inputs given venous data. The basic model we adopt is based on the relationship Cv = T * Ca, where Cv and Ca are the concentration in the venous and arterial site, respectively, T is the arterio-venous transfer function and * indicates convolution. We use empirical data to estimate T. We then compare estimates of systemic inputs to the venous site obtained taking into account the transfer function or, as usually done, disregarding it. The relationship we use to compare estimated inputs are: Cv = T * ka * A (where Ka is the arterial disposition function and A the systemic input), and Cv = Kv * A (where Kv is the venous disposition function), respectively. Finally, the estimated transfer function allows to estimate (average) Ca or A given arbitrary venous data. (i) Our analysis suggests that a bi-exponential T is needed to describe observed arterial-venous differences. The estimated transfer function indicates that no elimination of nicotine is involved in the forearm. (ii) Disregarding T, as usually done, erroneously obtains too complex venous input functions (because these input functions incorporate T). (iii) Disregarding T erroneously estimates significantly higher total inputs. (iv) Using the proposed model and previously published venous nicotine level data we predict substantial arterial-venous differences in blood nicotine levels for smokeless tobacco and nicotine gum. The use of disposition functions obtained from venous data may lead to erroneous estimation of the rates of entry into the circulation and systemic bioavailability for many drugs.

Administration, Intranasal↗

PubMed2002

Input characteristics and bioavailability after administration of immediate and a new extended-release formulation of hydromorphone in healthy volunteers.

BACKGROUND: To compare the pharmacokinetics of intravenous, oral immediate-release (IR), and oral extended-release (OROS ) formulations of hydromorphone. METHODS: In this randomized, six-session, crossover-design study, 12 subjects received hydromorphone 8-mg intravenous, 8-mg IR oral, and 8-, 16-, and 32-mg OROS formulations or placebo orally followed by plasma sampling for hydromorphone determination. Pharmacokinetic analysis was performed using NONMEM. Using the disposition of hydromorphone from the intravenous administration, deconvolution was used to estimate the input rate function (release rate from the gut to the blood) for the IR and OROS formulations. A linear spline was used to describe the drug input rate function. RESULTS: The deconvolution using linear splines described the release characteristics of both the IR and OROS formulations. The mean absolute bioavailability for the 8-mg OROS formulation was significantly larger ( = 0.025) than for the 8-mg IR formulation: 0.24 (SD 0.059) versus 0.19 (SD 0.054), respectively. The bioavailability was the same for the three doses of the OROS formulation. Predicted degree of fluctuation of plasma concentrations would be expected to be 130% and 39% for the IR and OROS 8-mg doses, respectively. CONCLUSIONS: The OROS formulation of hydromorphone produced continued release of medication over 24 h, which should allow for once-daily oral dosing. The extended release of hydromorphone will produce less fluctuation of plasma concentrations compared with IR formulations, which should provide for more constant pain control. The in vivo release of hydromorphone from both IR and OROS formulations were adequately described using a linear spline deconvolution approach. The increased bioavailability from the OROS formulation may be related to decreased metabolism by a first-pass effect or enterohepatic recycling of hydromorphone.

Administration, Oral↗