Biomedical subjects

Joost DeJongh

Publications and source records attributed to Joost DeJongh.

6 recordsLinked to original sources

PubMed2006

Application of the convection-dispersion equation to modelling oral drug absorption.

Models of systemic drug absorption after oral administration are frequently based on a direct or a delayed first-order rate process. In practice, the use of the first-order approach to predict drug concentrations in blood plasma frequently yields a considerable mismatch between predicted and measured concentration profiles. This is particularly true for the upswing of the plasma concentration after oral administration. The current investigation explores an alternative model to describe the absorption rate based on the convection-dispersion equation describing the transport of chemicals through the GI tract. This equation is governed by two parameters, transport velocity and dispersion coefficient. One solution of this equation for a specific set of initial and boundary conditions was used to model absorption of paracetamol in a 22-year-old man after oral administration. The GI-tract passage rate in this subject was influenced by co-administration of drugs that stimulate or delay gastric emptying. The transport-limited absorption function is more accurate in describing the plasma concentration versus time curve after oral administration than the first-order model. Additionally, it provides a mechanistic explanation for the observed curve through the differences in GI-tract passage rate.

Acetaminophen↗

PubMed2006

A mechanism-based disease progression model for comparison of long-term effects of pioglitazone, metformin and gliclazide on disease processes underlying Type 2 Diabetes Mellitus.

Effective long-term treatment of Type 2 Diabetes Mellitus (T2DM) implies modification of the disease processes that cause this progressive disorder. This paper proposes a mechanism-based approach to disease progression modeling of T2DM that aims to provide the ability to describe and quantify the effects of treatment on the time-course of the progressive loss of beta-cell function and insulin-sensitivity underlying T2DM. It develops a population pharmacodynamic model that incorporates mechanism-based representations of the homeostatic feedback relationships between fasting levels of plasma glucose (FPG) and fasting serum insulin (FSI), and the physiological feed-forward relationship between FPG and glycosylated hemoglobin A1c (HbA1c). This model was developed on data from two parallel one-year studies comparing the effects of pioglitazone relative to metformin or sulfonylurea treatment in 2,408 treatment-naïve T2DM patients. It was found that the model provided accurate descriptions of the time-courses of FPG and HbA1c for different treatment arms. It allowed the identification of the long-term effects of different treatments on loss of beta-cell function and insulin-sensitivity, independently from their immediate anti-hyperglycemic effects modeled at their specific sites of action. Hence it avoided the confounding of these effects that is inherent in point estimates of beta-cell function and insulin-sensitivity such as the widely used HOMA-%B and HOMA-%S. It was also found that metformin therapy did not result in a reduction in FSI levels in conjunction with reduced FPG levels, as expected for an insulin-sensitizer, whereas pioglitazone therapy did. It is concluded that, although its current implementation leaves room for further improvement, the mechanism-based approach presented here constitutes a promising conceptual advance in the study of T2DM disease progression and disease modification.

Adult↗

PubMed2006

Propofol pharmacokinetics and pharmacodynamics for depth of sedation in nonventilated infants after major craniofacial surgery.

BACKGROUND: To support safe and effective use of propofol in nonventilated children after major surgery, a model for propofol pharmacokinetics and pharmacodynamics is described. METHODS: After craniofacial surgery, 22 of the 44 evaluated infants (aged 3-17 months) in the pediatric intensive care unit received propofol (2-4 mg . kg-1 . h-1) during a median of 12.5 h, based on the COMFORT-Behavior score. COMFORT-Behavior scores and Bispectral Index values were recorded simultaneously. Population pharmacokinetic and pharmacodynamic modeling was performed using NONMEM V (GloboMax LLC, Hanover, MD). RESULTS: In the two-compartment model, body weight (median, 8.9 kg) was a significant covariate. Typical values were Cl = 0.70 . (BW/8.9)0.61 l/min, Vc = 18.8 l, Q = 0.35 l/min, and Vss = 146 l. In infants who received no sedative, depth of sedation was a function of baseline, postanesthesia effect (Emax model), and circadian night rhythm. In agitated infants, depth of sedation was best described by baseline, postanesthesia effect, and propofol effect (Emax model). The propofol concentration at half maximum effect was 1.76 mg/l (coefficient of variation = 47%) for the COMFORT-Behavior scale and 3.71 mg/l (coefficient of variation = 145%) for the Bispectral Index. CONCLUSIONS: Propofol clearance is two times higher in nonventilated healthy children than reported in the literature for ventilated children and adults. Based on the model, the authors advise a propofol dose of 30 mg/h in a 10-kg infant to achieve values of 12-14 on the COMFORT-Behavior scale and 70-75 on the Bispectral Index during the night. Wide pharmacodynamic variability emphasizes the importance of dose titration.

Craniosynostoses↗

PubMed2005

Disease system analysis: basic disease progression models in degenerative disease.

PURPOSE: To describe the disease status of degenerative diseases (i.e., type 2 diabetes mellitus, Parkinson's disease) as function of disease process and treatment effects, a family of disease progression models is introduced. METHODS: Disease progression is described using a progression rate (Rdp) acting on the synthesis or elimination parameters of the indirect response model. Symptomatic effects act as disease-dependent or -independent effects on the synthesis or elimination parameters. Protective drug effects act as disease dependent or -independent effects on Rdp. RESULTS: Simulations with the ten disease models show distinctly different signature profiles of treatment effects on disease status. Symptomatic effects result in improvement of disease status with a subsequent deterioration. Treatment cessation results in a disease status equal to the situation where treatment had not been applied. Protective effects result in a lasting reduction, or even reversal, of the disease progression rate and the resulting disease status during the treatment period. After cessation of treatment the natural disease course will continue from the disease status at that point. CONCLUSION: Disease system analysis constitutes a scientific basis for the distinction between symptomatic versus protective drug effects in relation to specific disease processes as well as the identification of the exposure-response relationship during the time-course of disease.

Biomarkers↗

PubMed2005

Pharmacokinetic/pharmacodynamic modelling of the anti-hyperalgesic and anti-nociceptive effect of adenosine A1 receptor partial agonists in neuropathic pain.

The objective of this investigation was to characterise the pharmacokinetic-pharmacodynamic correlation of adenosine A1 receptor partial agonists in the chronic constriction injury model of neuropathic pain. Following intravenous administration of 8-methylamino-N6-cyclopentyl-adenosine (MCPA; 10 mg/kg) and 2'deoxyribose-N6-cyclopentyl-adenosine (2'dCPA; 20 mg/kg), the time course of the effect on the mechanical paw pressure threshold was determined in conjunction with plasma concentrations. Population pharmacokinetic/pharmacodynamic analysis was applied to derive individual concentration-effect relationships. A composite model consisting of an E(max) model for the anti-hyperalgesic effect in combination with a linear model for the anti-nociceptive effect accurately described the concentration-effect relationship. For both compounds, a full anti-hyperalgesic effect was observed. The values of the EC50 for the anti-hyperalgesic effect were (mean+/-S.D.): 3170+/-1460 and 2660+/-1200 ng/ml for MCPA and 2'dCPA versus 178+/-51 ng/ml for the reference full agonist 5'deoxyribose-N6-cyclopentyl-adenosine (5'dCPA). The values of the slope for the anti-nociceptive effect were 1.9+/-0.30 and 1.2+/-0.20 g.microl/ng, respectively, versus 55+/-8 g microl/ng for 5'dCPA. Adenosine A1 receptor partial agonists behave as full agonists with regard to the anti-hyperalgesic effect in neuropathic pain, but the anti-nociceptive effect is diminished.

Adenosine↗

PubMed2002

Population pharmacokinetic and pharmacodynamic modeling of propofol for long-term sedation in critically ill patients: a comparison between propofol 6% and propofol 1%.

OBJECTIVES: A population pharmacokinetic and pharmacodynamic model of propofol for long-term sedation in critically ill patients is described, because limited information is available in these patients. In the models the influence of time-independent covariates, in particular, the propofol formulation (propofol 6% versus propofol 1%), and of time-dependent covariates was investigated. METHODS: Twenty critically ill, mechanically ventilated patients received propofol formulated as propofol 6% (n = 10) or propofol 1% (n = 10) during a 2- to 5-day period. The level of sedation was assessed with the Ramsay 6-point scale. The data from a short-term sedation study in 24 patients after cardiac surgery were included. Population pharmacokinetic and pharmacodynamic modeling was performed with NONMEM. RESULTS: The pharmacokinetics was adequately described by a 2-compartment model. The propofol formulation was not a significant covariate for the pharmacokinetics, whereas serum triglyceride concentration (TG) and relative body temperature (T(c)) were significant covariates for elimination clearance (CL). The population pharmacokinetic parameters were as follows: CL = 2.2 + 0.27 x T(c) - 0.049 x TG (mean, 2.1 L/min); volume of central compartment, 22.2 L; CL (distribution), 1.5 L/min; and volume of peripheral compartment, 168 L. The addition of other time-independent covariates (long-term versus short-term sedation study, as well as physiologic characteristics) or time-dependent covariates (duration of propofol infusion, additional midazolam rates, and hemodynamic parameters) to the model did not improve the quality of fit. For the pharmacodynamics, the probability that the sedation level was equal to, or more than, a specific score was described with the use of a sigmoid inverse logit of the maximal achievable probability model. The values for the inverse logit of the concentration causing half of the maximal effect for Ramsay sedation scores of 2 through 6 were 0.13 +/- 0.09, 0.31 +/- 0.17, 0.56 +/- 0.24, 0.79 +/- 0.31, and 1.78 +/- 0.65 mg/L, respectively (population mean +/- SE). Interindividual variability was high, with a coefficient of variation of 119% in the 50% effective concentration values. No covariates were identified. CONCLUSIONS: The population models in critically ill patients showed no differences in pharmacokinetics or pharmacodynamics between propofol 6% and propofol 1%. TG and T(c) appeared to be significant covariates for elimination clearance. For the pharmacodynamics, when propofol concentrations were between 0.75 and 1.5 mg/L, Ramsay sedation score 6 was most probable (40%-75%) and the probability for Ramsay sedation score 5 was 20% to 40%. Large pharmacodynamic variabilities were observed.

APACHE↗