Pharmacokinetic and pharmacodynamic modeling of mizolastine in healthy volunteers with an indirect response model

2000 ◽  
Vol 68 (6) ◽  
pp. 647-657 ◽  
Author(s):  
C Deschamps
Keyword(s):  
Healthy Volunteers ◽  
Pharmacodynamic Modeling ◽  
Response Model ◽  
Indirect Response Model ◽  
Indirect Response

Pharmacokinetic-Pharmacodynamic Modeling of the Respiratory Depressant Effect of Alfentanil 

1999 ◽  
Vol 91 (1) ◽  
pp. 144-155 ◽  
Author(s):  
Thomas Bouillon ◽  
Christina Schmidt ◽  
Gudrun Garstka ◽  
Dirk Heimbach ◽  
Dieter Stafforst ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Respiratory Depression ◽  
Pharmacodynamic Modeling ◽  
Model Parameters ◽  
Pharmacokinetic Data ◽  
Indirect Response Models ◽  
Response Model ◽  
Indirect Response Model ◽  
Indirect Response ◽  
Arterial Blood

Background Although respiratory depression is the most well-known and dangerous side effect of opioids, no pharmacokinetic-pharmacodynamic model exists for its quantitative analysis. The development of such a model was the aim of this study. Methods After institutional approval approval and informed consent were obtained, 14 men (American Society of Anesthesiologists physical status I or II; median age, 42 yr [range, 20-71 yr]; median weight, 82.5 kg [range, 68-108 kg]) were studied before they underwent major urologic surgery. An intravenous infusion of alfentanil (2.3 microg x kg(-1) x min(-1)) was started while the patients were breathing oxygen-enriched air (fraction of inspired oxygen [FIO2 = 0.5) over a tightly fitting continuous positive airway pressure mask. The infusion was discontinued when a cumulative dose of 70 microg/kg had been administered, the end-expiratory partial pressure of carbon dioxide (PE(CO2) exceeded 65 mmHg, or apneic periods lasting more than 60 s occurred During and after the infusion, frequent arterial blood samples were drawn and analyzed for the concentration of alfentanil and the arterial carbon dioxide pressure (PaCO2). A mamillary two-compartment model was fitted to the pharmacokinetic data. The PaCO2 data were described by an indirect response model The model accounted for the respiratory stimulation resulting from increasing PaCO2. The model parameters were estimated using NONMEM. Simulations were performed to define the respiratory response at steady state to different alfentanil concentrations. Results The indirect response model adequately described the time course of the PaCO2. The following pharmacodynamic parameters were estimated (population means and interindividual variability): EC50, 60.3 microg/l (32%); the elimination rate constant of carbon dioxide (Kel), 0.088 min(-1) (44%); and the gain in the carbon dioxide response, 4(28%) (fixed according to literature values). Simulations revealed the pronounced role of PaCO2 in maintaining alveolar ventilation in the presence of opioid. Conclusions The model described the data for the entire opioid-PaCo2 response surface examined. Indirect response models appear to be a promising tool for the quantitative evaluation of drug-induced respiratory depression.

Population pharmacokinetic-pharmacodynamic model of oxfendazole in healthy adults in a multiple ascending dose and food effect study and target attainment analysis

2021 ◽  
Author(s):  
Thanh Bach ◽  
Gregory A. Deye ◽  
Ellen E. Codd ◽  
John Horton ◽  
Patricia Winokur ◽  
...  
Keyword(s):  
Safety Concern ◽  
Hemoglobin Concentration ◽  
Healthy Adults ◽  
Pharmacodynamic Modeling ◽  
Parasitic Infections ◽  
Population Pharmacokinetic ◽  
Phase I Clinical Trials ◽  
Target Attainment ◽  
Indirect Response Model ◽  
Indirect Response

Oxfendazole is a potent veterinary antiparasitic drug undergoing development for human use to treat multiple parasitic infections. Results from two recently completed Phase I clinical trials conducted in healthy adults showed that the pharmacokinetics of oxfendazole is nonlinear, affected by food, and, after the administration of repeated doses, appeared to mildly affect hemoglobin concentrations. To facilitate oxfendazole dose optimization for its use in patient populations, the relationship among oxfendazole dose, pharmacokinetics and hemoglobin concentration was quantitatively characterized using population pharmacokinetic-pharmacodynamic modeling. In fasting subjects, oxfendazole pharmacokinetics was well described by a one-compartment model with first-order absorption and elimination. The change in oxfendazole pharmacokinetics when administered following a fatty meal was captured by an absorption model with one transit compartment and increased bioavailability. The effect of oxfendazole exposure on hemoglobin concentration in healthy adults was characterized by a lifespan indirect response model in which oxfendazole has positive but minor inhibitory effect on red blood cell synthesis. Further simulation indicated that oxfendazole has a low risk of posing a safety concern regarding hemoglobin concentration, even at a high oxfendazole dose of 60 mg/kg once daily. The final model was further used to perform comprehensive target attainment simulations for whipworm infection and filariasis at various dose regimens and target attainment criteria. The results of our modeling work, when adopted appropriately, have the potential to greatly facilitate oxfendazole dose regimen optimization in patient populations with different types of parasitic infections.

scholarly journals Plasma and Intracellular Population Pharmacokinetic Analysis of Tenofovir in HIV-1-Infected Patients

2011 ◽  
Vol 55 (11) ◽  
pp. 5294-5299 ◽  
Author(s):  
Gautam Baheti ◽  
Jennifer J. Kiser ◽  
Peter L. Havens ◽  
Courtney V. Fletcher
Keyword(s):  
Rate Constant ◽  
Sequential Analysis ◽  
Plasma Concentrations ◽  
Elimination Rate ◽  
Distribution Volume ◽  
Pharmacokinetic Analysis ◽  
Population Pharmacokinetic ◽  
Response Model ◽  
Indirect Response Model ◽  
Indirect Response

ABSTRACTThe relationships among the dose of tenofovir disoproxil fumarate (TDF), tenofovir (TFV) plasma concentrations, and intracellular TFV diphosphate (TFV-DP) concentrations are poorly understood. Our objective was to characterize TFV and TFV-DP relationships. Data were pooled from two studies in HIV-infected persons (n= 55) on stable antiretroviral therapy. TFV and TFV-DP were measured with validated liquid chromatography/tandem mass spectrometry (LC/MS/MS) methods. Nonlinear mixed effects modeling (NONMEM 7) was used to develop the population model and explore the influence of covariates on TFV. A sequential analysis approach was utilized. A two-compartment model with first-order absorption best described TFV PK (FOCEI). An indirect stimulation of response model best described TFV-DP, where formation of TFV-DP was driven by plasma TFV concentration. Final plasma population estimates were as follows: absorption rate constant, 1.03 h−1; apparent clearance (CL/F), 42 liters/h (33.5% interindividual variability [IIV]); intercompartment clearance, 181 liters/h; apparent central distribution volume (Vc/F), 273 liters (64.8% IIV); and apparent peripheral distribution volume (Vp/F), 440 liters (46.5% IIV). Creatinine clearance was the most significant covariate on CL/F and Vc/F. The correlation between CL/F and Vc/F was 0.553. The indirect response model for TFV-DP resulted in estimates of the maximal intracellular concentration (Emax), the TFV concentration producing 50% ofEmax(EC50), and the intracellular elimination rate constant (kout) of 300 fmol/106cells (82% IIV), 100 ng/ml (106% IIV), and 0.008 h−1, respectively. The estimatedkoutgave an 87-h TFV-DP half-life. A predictive check assessment indicated satisfactory model performance. This model links formation of TFV-DP with plasma TFV concentrations and should facilitate more informed investigations of TFV clinical pharmacology.

scholarly journals An indirect response model of homocysteine suppression by betaine: optimising the dosage regimen of betaine in homocystinuria

2002 ◽  
Vol 54 (2) ◽  
pp. 140-146 ◽  
Author(s):  
Angela Matthews ◽  
Trevor N. Johnson ◽  
Amin Rostami-Hodjegan ◽  
Anupam Chakrapani ◽  
J. Edward Wraith ◽  
...  
Keyword(s):  
Dosage Regimen ◽  
Response Model ◽  
Indirect Response Model ◽  
Indirect Response
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