Quantitative Characterization of Clinically Relevant Drug-Metabolizing Enzymes and Transporters in Rat Liver and Intestinal Segments for Applications in PBPK Modeling

Abstract

Rats are extensively used as a preclinical model for assessing drug pharmacokinetics (PK) and tissue distribution; however, successful translation of the rat data requires information on the differences in drug metabolism and transport mechanisms between rats and humans. To partly fill this knowledge gap, we quantified clinically relevant drug-metabolizing enzymes and transporters (DMETs) in the liver and different intestinal segments of Sprague-Dawley rats. The levels of DMET proteins in rats were quantified using the global proteomics-based total protein approach (TPA) and targeted proteomics. The abundance of the major DMET proteins was largely comparable using quantitative global and targeted proteomics. However, global proteomics-based TPA was able to detect and quantify a comprehensive list of 66 DMET proteins in the liver and 37 DMET proteins in the intestinal segments of SD rats without the need for peptide standards. Cytochrome P450 (Cyp) and UDP-glycosyltransferase (Ugt) enzymes were mainly detected in the liver with the abundance ranging from 8 to 6502 and 74 to 2558 pmol/g tissue. P-gp abundance was higher in the intestine (124.1 pmol/g) as compared to that in the liver (26.6 pmol/g) using the targeted analysis. Breast cancer resistance protein (Bcrp) was most abundant in the intestinal segments, whereas organic anion transporting polypeptides (Oatp) 1a1, 1a4, 1b2, and 2a1 and multidrug resistance proteins (Mrp) 2 and 6 were predominantly detected in the liver. To demonstrate the utility of these data, we modeled digoxin PK by integrating protein abundance of P-gp and Cyp3a2 into a physiologically based PK (PBPK) model constructed using PK-Sim software. The model was able to reliably predict the systemic as well as tissue concentrations of digoxin in rats. These findings suggest that proteomics-informed PBPK models in preclinical species can allow mechanistic PK predictions in animal models including tissue drug concentrations.

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook

“…Similarly, understanding of interspecies differences is critical for interpreting drug toxicology data and allometric scaling of drug pharmacokinetics. Quantitative proteomics has been leveraged to identify interspecies differences in transport and metabolism, such as renal and hepatic transporters and enzymes (Wang et al, 2014;Basit et al, 2019;Sharma et al, 2023). For example, quantitative proteomics data confirmed the absence of BCRP and OCT1 proteins in human kidneys as compared with rodents (Basit et al, 2019).…”

Effects of alcohol consumption and tobacco smoking on the composition of the ensemble of drug metabolizing enzymes and transporters in human liver

“…HLM were analyzed for protein con tent using a BCA kit via standard vendor protocols and then digested by an optimized trypsin digestion protocol described previously (Sharma et al, 2023). Briefly, 1 mg/ml protein samples (80 µg) in 100 mM ammonium bicarbonate, pH 7.8, were reduced and denatured by the addition of 250 mM dithiothreitol and incubation a t 95°C for 10 min under gen tle shaking.…”

In silico modeling and simulation of organ‐on‐a‐chip systems to support data analysis and a priori experimental design

“…1 Data from these assays are then included in physiologically-based pharmacokinetic (PBPK) models to simulate the in vivo PK profile of a drug in plasma and organs of interest. [2][3][4][5][6] Many in vitro systems do not fully recapitulate the in vivo features of a given tissue and therefore the extrapolation may not accurately predict the in vivo outcome. [7][8][9][10] In addition, current in vitro systems have the drawback of a limited longevity of cell phenotype which constrains their application for certain scenarios, such as low clearance drugs.…”

“…Many independent in vitro assays have been established to measure various absorption, distribution, metabolism, and excretion (ADME) properties which allow IVIVE using relevant physiologically‐based scaling factors 1 . Data from these assays are then included in physiologically‐based pharmacokinetic (PBPK) models to simulate the in vivo PK profile of a drug in plasma and organs of interest 2–6 …”

“… 1 Data from these assays are then included in physiologically‐based pharmacokinetic (PBPK) models to simulate the in vivo PK profile of a drug in plasma and organs of interest. 2 , 3 , 4 , 5 , 6 …”