Utility of Quantitative Proteomics for Enhancing the Predictive Ability of Physiologically Based Pharmacokinetic Models Across Disease States.

Disease states such as liver cirrhosis and chronic kidney disease can lead to altered pharmacokinetics (PK) of drugs by influencing drug absorption, blood flow to organs, plasma protein binding, apparent volume of distribution, and drug-metabolizing enzyme and transporter (DMET) abundance. Narrow therapeutic index drugs are particularly vulnerable to undesired pharmacodynamics (PD) because of the changes in drug PK in disease states. However, systematic clinical evaluation of disease effect on drug PK and PD is not always possible because of the complexity or the cost of clinical studies. Physiologically based PK (PBPK) modeling is emerging as an alternate method to extrapolate drug PK from the healthy population to disease states. These models require information on the effect of disease condition on the activity or tissue abundance of DMET proteins. Although immunoquantification-based abundance data were available in the literature for a limited number of DMET proteins, the emergence of mass spectrometry-based quantitative proteomics as a sensitive, robust, and high-throughput tool has allowed a rapid increase in data availability on tissue DMET abundance in healthy versus disease states, especially in liver tissue. Here, we summarize these data including the available immunoquantification or mRNA levels of DMET proteins (healthy vs disease states) in extrahepatic tissue and discuss the potential applications of DMET abundance data in enhancing the capability of PBPK modeling in predicting drug disposition across disease states. Successful examples of PBPK modeling that integrate differences in DMET proteins between healthy and disease states are discussed.

Metabolite identification studies on amiodarone in in vitro (rat liver microsomes, rat and human liver S9 fractions) and in vivo (rat feces, urine, plasma) matrices by using liquid chromatography with high-resolution mass spectrometry and multiple-stage mass spectrometry: characterization of the diquinone metabolite supposedly responsible for the drug's hepatotoxicity.

RATIONALE: Several mechanisms have been anticipated for the toxicity of amiodarone, such as oxidative stress, lipid peroxidation, phospholipidosis, free radical generation, etc. Amiodarone is structurally similar to benzbromarone, an uricosuric agent, which was withdrawn from European markets due to its idiosyncratic hepatotoxicity. A proposed reason behind the toxicity of benzbromarone was the production of a reactive ortho-diquinone metabolite, which was found to form adducts with glutathione. Therefore, taking a clue that a similar diquinone metabolite of amiodarone may be the reason for its hepatotoxicity, metabolite identification studies were carried out on the drug using liquid chromatography/mass spectrometry (LC/MS) tools. METHODS: The studies involved in vitro (rat liver microsomes, rat liver S9 fraction, human liver S9 fraction) and in vivo (rat feces, urine, plasma) models, wherein the samples were analyzed by employing LC/HRMS, LC/MS(n) and HDE-MS. RESULTS AND CONCLUSIONS: A total of 26 metabolites of amiodarone were detected in the investigated in vitro and in vivo matrices. The suspected ortho-diquinone metabolite was one of them. The formation of the same might be an added reason for the hepatotoxicity shown by the drug.