Simulation of the metabolism and enterohepatic circulation of endogenous chenodeoxycholic acid in man using a physiological pharmacokinetic model

Abstract

The metabolism and enterohepatic circulation of chenodeoxycholic acid (CDC), a major primary bile acid in man, has been stimulated using a multicompartmental physiological pharmacokinetic model which was previously reported and used to simulate the metabolism of cholic acid. The model features compartments and linear transfer coefficients. Compartments, which are defined as the pools of single chemical species in well defined anatomical volumes, are aggregated into nine 'spaces' based on anatomical and physiological considerations (liver, gall-bladder, bile ducts, duodeno-jejunum, ileum, colon, portal blood, sinusoidal blood, and general circulation). Each space contains several compartments which correspond to the compounds present in that space, for example, the compound in question and its biotransformation products. For CDC (as for cholic acid in the previous simulation) each space contains three compartments corresponding to the unconjugated bile acid, its glycine amidate, and its taurine amidate. Transfer coefficients, which denote the fractional amount of the compartment's contents exiting per unit time, are categorized according to function: flow, for example gall-bladder contraction (which involves transfer of all substances contained in the space at the same fractional rate); biotransformation (which transfers the substrate from one compartment to another within the same space); or transport (which denotes movements between contiguous compartments, belonging to different spaces across a diffusion membrane or a cellular barrier). The model is made time-dependent by incorporating meals which trigger gall-bladder emptying and modify intestinal flow. The transfer coefficients in the cholic acid model were modified for the CDC model since there is indirect evidence that CDC amidates (probably chenodeoxycholylglycine) are absorbed from the duodeno-jejunum and the first pass hepatic clearance of CDC species differs from that of cholyl species. The model was then used with all existing experimental data to simulate CDC metabolism in healthy humans over a 24-h period during which three meals were ingested. Satisfactory agreement was obtained between simulated and experimental data indicating that this model continues to be useful for describing the metabolism of bile acids and may also be of value for describing the metabolism of drugs whose metabolism is similar to that of bile acids.

Comparative potency of obeticholic acid and natural bile acids on FXR in hepatic and intestinal in vitro cell models

“…Intestinal concentrations of total OCA in daily OCA 10 mg group is approximately 40 μmol/L estimated by simulation (internal data). Molino et al estimated the physiological concentration of glyco‐CDCA in the intestine is approximately 35 μmol/L. The concentration ranges of glyco‐OCA and glyco‐CDCA tested in Caco‐2 cells are 0.1‐30 μmol/L and 1‐100 μmol/L, respectively.…”

Bile acids: Trying to understand their chemistry and biology with the hope of helping patients #

“…with Gianpaolo Molino, Mario Milanese, Gustavo Belforte, and their colleagues, I was able to develop physiological pharmacokinetic models of bile acid metabolism, and use these models to simulate bile acid metabolism in the healthy human [38][39][40] as well as in some disease conditions. 41 I was happy with this work, but it seems to have had little impact in the modeling field and has hardly been noticed by pharmacokineticists.…”

Model‐based data analysis of individual human postprandial plasma bile acid responses indicates a major role for the gallbladder and intestine

“…Several models of bile acid metabolism have been developed previously including the compartmental models developed by Hofmann et al (Hofmann, Molino, Milanese, & Belforte, ; ; Molino, Hofmann, Cravetto, Belforte, & Bona, ; Cravetto, Molino, Hofmann, Belforte, & Bona, ), the more recent exogenous UDCA (Zuo, Dobbins, O'Connor‐Semmes, & Young, ) and endogenous LCA (Woodhead et al, ) focused models, and an individual, data‐driven model of postprandial total bile acid responses (Guiastrennec et al, ). The latter is the most similar to the approach presented here.…”