Literature DB >> 21355107

The corrected traditional equations for calculation of hepatic clearance that account for the difference in drug ionization in extracellular and intracellular tissue water and the corresponding corrected PBPK equation.

Leonid M Berezhkovskiy1.   

Abstract

The estimation of hepatic clearance, Clh, using in vitro data on metabolic stability of compound, its protein binding and blood–plasma equilibrium concentration ratio is commonly performed using well-stirred, parallel tube or dispersion models. It appears that for ionizable drugs there is a difference of the steady-state concentrations in extracelluar and intracellular water (at hepatocytes), where metabolism takes place. This occurs due to the different pH of extra- and intracellular water (7.4 and 7.0, respectively). The account of this fact leads to the novel equations for Clh . These equations include the additional parameter named ionization factor, FI, which is the ratio of the unionized drug fractions in plasma and intracellular tissue water (or the ratio of the unbound drug concentrations in intracellular tissue water and plasma at equilibrium). For neutral drugs FI = 1 and the novel equations coincide with the traditional ones. It is shown that the account of this factor may yield the calculated Clh up to 6.3-fold greater than that obtained by the traditional equations for the strong diprotic basic compounds, and up to 6.3-fold smaller for the strong diprotic acidic compounds. For triprotic acids and bases the difference could be as much as 15-fold. The account of pH difference between extra- and intracellular water also results in the change of the term commonly used to describe drug metabolic elimination rate in physiologically based pharmacokinetic (PBPK) equation. This consequently may lead to a noticeable change of drug concentration-time profiles in plasma and tissues. The effect of ionization factor is especially pronounced for the low-extraction ratio drugs. The examples of significant improvement in the prediction of hepatic clearance due to the account of ionization factor are provided. A more general equation for hepatic clearance, which accounts for ionization factor and possible drug uptake and efflux, is obtained.

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Year:  2011        PMID: 21355107     DOI: 10.1002/jps.22324

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  6 in total

1.  On the maintenance of hepatocyte intracellular pH 7.0 in the in-vitro metabolic stability assay.

Authors:  Leonid M Berezhkovskiy; Susan Wong; Jason S Halladay
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-11-01       Impact factor: 2.745

Review 2.  Drug Concentration Asymmetry in Tissues and Plasma for Small Molecule-Related Therapeutic Modalities.

Authors:  Donglu Zhang; Cornelis E C A Hop; Gabriela Patilea-Vrana; Gautham Gampa; Herana Kamal Seneviratne; Jashvant D Unadkat; Jane R Kenny; Karthik Nagapudi; Li Di; Lian Zhou; Mark Zak; Matthew R Wright; Namandjé N Bumpus; Richard Zang; Xingrong Liu; Yurong Lai; S Cyrus Khojasteh
Journal:  Drug Metab Dispos       Date:  2019-07-02       Impact factor: 3.922

3.  Lysosomal sequestration (trapping) of lipophilic amine (cationic amphiphilic) drugs in immortalized human hepatocytes (Fa2N-4 cells).

Authors:  Faraz Kazmi; Tiffini Hensley; Chad Pope; Ryan S Funk; Greg J Loewen; David B Buckley; Andrew Parkinson
Journal:  Drug Metab Dispos       Date:  2013-02-01       Impact factor: 3.922

4.  A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

Authors:  Min Ye; Swati Nagar; Ken Korzekwa
Journal:  Biopharm Drug Dispos       Date:  2016-04       Impact factor: 1.627

Review 5.  Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization.

Authors:  Jasleen K Sodhi; Leslie Z Benet
Journal:  J Med Chem       Date:  2021-03-25       Impact factor: 7.446

6.  Recent developments in in vitro and in vivo models for improved translation of preclinical pharmacokinetics and pharmacodynamics data.

Authors:  Jaydeep Yadav; Mehdi El Hassani; Jasleen Sodhi; Volker M Lauschke; Jessica H Hartman; Laura E Russell
Journal:  Drug Metab Rev       Date:  2021-05-25       Impact factor: 6.984

  6 in total

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