Abstract

A model was developed for long term metformin tissue retention based upon temporally inclusive models of serum/plasma concentration ( C ) having power function tails called the gamma-Pareto type I convolution (GPC) model and was contrasted with biexponential (E2) and noncompartmental (NC) metformin models. GPC models of C have a peripheral venous first arrival of drug-times parameter, early C peaks and very slow washouts of C . The GPC, E2 and NC models were applied to a total of 148 serum samples drawn from 20 min to 72 h following bolus intravenous metformin in seven healthy mongrel dogs. The GPC model was used to calculate area under the curve (AUC), clearance ( CL ), and functions of time, f(t), for drug mass remaining (M), apparent volume of distribution (V_{d}), as well as t_{1/2} f(t) for C , M and V_{d}. The GPC models of C yielded metformin CL -values that were 84.8% of total renal plasma flow (RPF) as estimated from meta-analysis. The GPC CL -values were significantly less than the corresponding NC and E2 CL -values of 104.7% and 123.7% of RPF, respectively. The GPC plasma/serum only model predicted 78.9% drug M average urinary recovery at 72 h; similar to prior human urine drug M collection results. The GPC model t_{1/2} of M , C and V_d, were asymptotically proportional to elapsed time, with a constant limiting t_{1/2} ratio of M/C averaging 7.0 times, a result in keeping with prior simultaneous C and urine M collection studies and exhibiting a rate of apparent volume growth of V_d that achieved limiting constant values. A simulated constant average drug mass multidosing protocol exhibited increased V_d and t_{1/2} with elapsing time, effects that have been observed experimentally during same-dose multidosing. The GPC heavy-tailed models explained multiple documented phenomena that were unexplained with lighter-tailed models.

Highlights

  • Metformin (1,1-dimethylbiguanide), average molecular weight 129.164 g/mol, is a þ1 cation at physiological pH with apparent volumes of distribution [1] so large that it may be problematic to use classical pharmacokinetic methods to calculate those volumes

  • Niazi’s work was generalised by some of us for any density function supported on the time is 1⁄20; 1Þ interval having a varying apparent volume of drug distribution in time, VdðtÞ, with half-life expressions that vary in time [23]

  • A back extrapolated gamma-Pareto type I convolution (GPC) concentration model is shown in Fig. 2, with zero initial concentration that cannot be shown in the Fig. 1 log-log plots

Read more

Summary

Introduction

Metformin (1,1-dimethylbiguanide), average molecular weight 129.164 g/mol, is a þ1 cation at physiological pH with apparent volumes of distribution (dogs) [1] so large that it may be problematic to use classical pharmacokinetic methods to calculate those volumes. Metformin is used among numerous indications as the default first-line treatment for type II diabetes and for cancer chemotherapy in humans. Said ratios naturally arise in the context of variable apparent volume of distribution models, VdðtÞ. The first mathematically correct VdðtÞ models were proposed by Niazi for SET functions [40]. Those models were simultaneously compartmental models and variable volume models, but the interpretations of those different models are distinct. Niazi’s work was generalised by some of us for any density function supported on the time is 1⁄20; 1Þ interval having a varying apparent volume of drug distribution in time, VdðtÞ, with half-life expressions that vary in time [23]. For variable volume modelling VdðtÞ is a drug-ocentric volume of distribution in time. That apparent volume of distribution is the imaginary volume that the drug would occupy if it were everywhere at the same concentration as it was observed to be in plasma at that time, and CL eliminates drug mass from that single volume no matter how big that volume is

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call