Effect of plasma protein and tissue binding on the time course of drug concentration in plasma

1979 ◽  
Vol 7 (2) ◽  
pp. 195-206 ◽  
Author(s):  
Patrick J. McNamara ◽  
Gerhard Levy ◽  
Milo Gibaldi
Keyword(s):  
Plasma Protein ◽  
Drug Concentration ◽  
Time Course ◽  
Tissue Binding

How Well Do Lipophilicity Parameters, MEEKC Microemulsion Capacity Factor, and Plasma Protein Binding Predict CNS Tissue Binding?

2012 ◽  
Vol 101 (5) ◽  
pp. 1932-1940 ◽  
Author(s):  
Maciej J. Zamek-Gliszczynski ◽  
Karen E. Sprague ◽  
Alfonso Espada ◽  
Thomas J. Raub ◽  
Stuart M. Morton ◽  
...  
Keyword(s):  
Protein Binding ◽  
Plasma Protein Binding ◽  
Plasma Protein ◽  
Capacity Factor ◽  
Tissue Binding ◽  
Lipophilicity Parameters

Do We Need to Optimize Plasma Protein and Tissue Binding in Drug Discovery?

2011 ◽  
Vol 11 (4) ◽  
pp. 450-466 ◽  
Author(s):  
Xingrong Liu ◽  
Cuiping Chen ◽  
Cornelis E.C.A. Hop
Keyword(s):  
Drug Discovery ◽  
Plasma Protein ◽  
Tissue Binding

Transport and metabolism of 6-thioguanine and 6-mercaptopurine in mouse small intestine

1988 ◽  
Vol 74 (6) ◽  
pp. 629-638 ◽  
Author(s):  
J. R. Bronk ◽  
Norma Lister ◽  
M. I. Shaw
Keyword(s):  
Small Intestine ◽  
Xanthine Oxidase ◽  
Drug Concentration ◽  
Time Course ◽  
Oxidase Inhibitor ◽  
Unknown Compound ◽  
Xanthine Oxidase Inhibitor ◽  
Drug Concentrations ◽  
Xanthine Oxidase Inhibitors ◽  
Mouse Small Intestine

1. The transport of 6-thioguanine and 6-mercaptopurine has been studied with isolated jejunal loops of mouse small intestine. H.p.l.c. was used to identify and quantify the thiopurines and their metabolites in the serosal secretions. 2. When the lumen of the intestinal loops contained either 6-thioguanine or 6-mercaptopurine at a concentration of 1 mmol/l, the concentration of unmetabolized drug in the serosal secretions reached a maximum of 0.13 ± 0.02 mmol/l (mean ± sem). 3. Analysis of the serosal secretions from the perfusions with either of the drugs revealed the appearance of an unknown compound which had the characteristics of a thiopurine and the same time course of appearance as the unmetabolized drug. Thus 6-thioguanine and 6-mercaptopurine are significantly metabolized during absorption in mouse intestine. 4. The unknown compound was identified as 6-thiouric acid, and with 1 mmol/l 6-thioguanine or 6-mercaptopurine in the lumen the concentration of this metabolite in the serosal secretions rose to a maximum of 0.13 ± 0.01 and 0.18 ± 0.03 mmol/l, respectively. At luminal drug concentrations of 0.1 mmol/l, the metabolite accounted for approximately 90% of the serosal thiopurine. 5. After an initial lag period of 20 min, linear rates of appearance in the serosal secretions were obtained for both the unmetabolized drugs and 6-thiouric acid. 6. Addition of the xanthine oxidase inhibitor oxypurinol at a luminal concentration of 0.3 mmol/l prevented the formation of 6-thiouric acid from 6-thioguanine. However, the inhibitor reduced the rate of 6-thioguanine appearance in the serosal secretions by 50%. 7. The conversion of 6-mercaptopurine to 6-thiouric acid was prevented when allopurinol or oxypurinol were added to the lumen. At a luminal drug concentration of 1 mmol/l, allopurinol increased the rate at which 6-mercaptopurine appeared in the serosal secretions by 90% compared with an increase of only 50% with oxypurinol. 8. The transport of water and glucose by the mouse intestinal loops was unaffected by 6-thioguanine or the xanthine oxidase inhibitors. However, 6-mercaptopurine caused significant reductions in the rate of water transport (30%) and glucose transport (39%). These effects were observed at a luminal drug concentration of 0.1 mmol/l and there was no further increase at a drug concentration of 1 mmol/l.

Rational Use of Plasma Protein and Tissue Binding Data in Drug Design

2014 ◽  
Vol 57 (20) ◽  
pp. 8238-8248 ◽  
Author(s):  
Xingrong Liu ◽  
Matthew Wright ◽  
Cornelis E. C. A. Hop
Keyword(s):  
Drug Design ◽  
Plasma Protein ◽  
Tissue Binding ◽  
Rational Use ◽  
Binding Data

scholarly journals Pharmacokinetic/Pharmacodynamic (PK/PD) Indices of Antibiotics Predicted by a Semimechanistic PKPD Model: a Step toward Model-Based Dose Optimization

2011 ◽  
Vol 55 (10) ◽  
pp. 4619-4630 ◽  
Author(s):  
Elisabet I. Nielsen ◽  
Otto Cars ◽  
Lena E. Friberg
Keyword(s):  
Drug Concentration ◽  
Time Course ◽  
Drug Exposure ◽  
Full Time ◽  
Antibacterial Drugs ◽  
Model Based ◽  
Pkpd Model ◽  
Dosing Intervals ◽  
Time Kill

ABSTRACTA pharmacokinetic-pharmacodynamic (PKPD) model that characterizes the full time course ofin vitrotime-kill curve experiments of antibacterial drugs was here evaluated in its capacity to predict the previously determined PK/PD indices. Six drugs (benzylpenicillin, cefuroxime, erythromycin, gentamicin, moxifloxacin, and vancomycin), representing a broad selection of mechanisms of action and PK and PD characteristics, were investigated. For each drug, a dose fractionation study was simulated, using a wide range of total daily doses given as intermittent doses (dosing intervals of 4, 8, 12, or 24 h) or as a constant drug exposure. The time course of the drug concentration (PK model) as well as the bacterial response to drug exposure (in vitroPKPD model) was predicted. Nonlinear least-squares regression analyses determined the PK/PD index (the maximal unbound drug concentration [fCmax]/MIC, the area under the unbound drug concentration-time curve [fAUC]/MIC, or the percentage of a 24-h time period that the unbound drug concentration exceeds the MIC [fT>MIC]) that was most predictive of the effect. Thein silicopredictions based on thein vitroPKPD model identified the previously determined PK/PD indices, withfT>MICbeing the best predictor of the effect for β-lactams andfAUC/MIC being the best predictor for the four remaining evaluated drugs. The selection and magnitude of the PK/PD index were, however, shown to be sensitive to differences in PK in subpopulations, uncertainty in MICs, and investigated dosing intervals. In comparison with the use of the PK/PD indices, a model-based approach, where the full time course of effect can be predicted, has a lower sensitivity to study design and allows for PK differences in subpopulations to be considered directly. This study supports the use of PKPD models built fromin vitrotime-kill curves in the development of optimal dosing regimens for antibacterial drugs.

Effect of plasma protein and tissue binding on the biologic half-life of drugs

1978 ◽  
Vol 24 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Milo Gibaldi ◽  
Gerhard Levy ◽  
Patrick J. McNamara
Keyword(s):  
Plasma Protein ◽  
Half Life ◽  
Tissue Binding
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