Pharmacokinetic Modelling of the Plasma Protein Binding of Mycophenolic Acid in Renal Transplant Recipients
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  • 作者:Dr Reinier M. van Hest (1)
    Teun van Gelder (1) (2)
    Arnold G. Vulto (1)
    Leslie M. Shaw (3)
    Ron A. A. Mathot (1)
  • 刊名:Clinical Pharmacokinetics
  • 出版年:2009
  • 出版时间:July 2009
  • 年:2009
  • 卷:48
  • 期:7
  • 页码:463-476
  • 全文大小:832KB
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  • 作者单位:Dr Reinier M. van Hest (1)
    Teun van Gelder (1) (2)
    Arnold G. Vulto (1)
    Leslie M. Shaw (3)
    Ron A. A. Mathot (1)

    1. Department of Hospital Pharmacy, Erasmus Medical Centre, Rotterdam, The Netherlands
    2. Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
    3. Department of Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  • ISSN:1179-1926
文摘
Background and Objectives Renal function and the plasma albumin concentration have been shown to correlate with clearance of total mycophenolic acid (MPA). The hypothesis for the underlying mechanism is that low plasma albumin concentrations and accumulation of the glucuronide metabolite of MPA (MPAG) decrease the binding of MPA to albumin. The subsequent increase in the unbound fraction (fu) of MPA (MPAu) produces an increase in total MPA (MPAt) clearance. This study aimed to develop an empirical population pharmacokinetic model to describe the relationships between renal function and albumin concentration and MPAG, MPAu and MPAt, in order to provide insight into the mechanism by which renal function and plasma albumin affect the disposition of MPA. Methods 774 MPAt, 479 MPAu and 772 total MPAG (MPAGt) plasma concentrations were available from 88 renal transplant recipients on days 11 and 140 after transplantation. Data were analysed using non-linear mixed-effects modelling. Results Time profiles of MPAu and MPAGt concentrations were adequately described by two 2-compartment pharmacokinetic models with a link between the central compartments, representing the glucuronidation of MPAu to form MPAG. MPAt concentrations were modelled using: [MPAt = [MPAu] + [MPAu] · θpb, with [MPAJ · θpb representing the bound MPA concentration, where [MPAt], [MPAu] and θpb represent MPAt concentration, MPAu concentration and a factor that correlates to the total number of protein binding places, respectively. According to this equation, fu= [MPAu]/[MPAt] = 1/(1 +θpb) · θpb, and therefore [MPAt], was significantly and independently correlated with Creatinine clearance (CLCR), the plasma albumin concentration and the MPAGt concentration (all p < 0.001). A reduction in CLCR from 60 to 25 mL/min correlated with an increase in fu from 2.7% to 3.5%, accumulation of MPAGt concentrations from 50 to 150 mg/L correlated with an increase in fu from 2.8% to 3.7%, and a decrease in plasma albumin concentration from 40 to 30g/L correlated with an increase in fu from 2.6% to 3.5%. No significant correlations were detected between MPAu clearance and the plasma albumin concentration or CLCR. Conclusion The model shows that low CLCR, low plasma albumin concentrations and high MPAG concentrations decrease MPAt exposure by affecting MPA binding to albumin.

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