In Vitro to In Vivo Extrapolation of Transporter-Mediated Clearance of Drugs Using Quantitative Proteomics
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Prediction of in vivo drug clearance (CL) is an important aspect of drug discovery and development. Our ability to predict in vivo hepatic metabolic clearance and metabolic drug-drug interactions from in vitro studies using liver microsomes, cytosols, and hepatocytes has been relatively successful. However, prediction of transporter-mediated clearance remains a challenge. Even where primary cells like hepatocytes (suspended, plated and sandwich-cultured hepatocytes) are available, they do not predict well the in vivo transporter-mediated clearance of drugs for the following reasons. First, transporters are transmembrane proteins and functional only when present on the plasma membrane. Because purified protein standards for transporters are not available, methods need to be developed to not only quantify the total abundance of these proteins, but also the plasma membrane abundance (PMA) of these transporters. Second, it is not clear if transporter abundance (total or PMA) in primary cells (e.g. human hepatocytes) faithfully replicates that in human tissues. Third, primary cells (e.g. hepatocytes) are not readily available for all organs of interest (intestine, kidney, brain). Fourth, transporter-mediated clearance of drugs is a complex interplay between multiple transporters and metabolism. For example, hepatic or renal clearance of drugs can occur by multiple transporters located on different faces of the hepatocytes and kidney epithelial cells. Thus, the rate-determining steps in their clearance could be their uptake into the tissue (sinusoidal or kidney epithelial basal transporters), or metabolism, or efflux (canalicular or kidney epithelial apical transporters) from the tissue. Based on the above information, there is an urgent need to develop methods to predict in vivo transporter-mediated CL of drugs that are high-throughput, inexpensive and utilize in vitro tools. Therefore, we have hypothesized “In vivo renal/hepatic CL of drugs can be predicted by measurement of transporter protein abundance and activity in transporter-expressing cells as well as transporter protein abundance in kidney/hepatic tissues”. The focus of this dissertation was to address the above hypothesis with studies to predict the hepatic uptake and renal secretory CL of rosuvastatin (RSV) and metformin, respectively. To do so, we first developed a LC-MS/MS-based quantitative cell-surface biotinylation methodology to measure the plasma membrane abundance in various cells including hepatocytes. Second, the total and PMA of transporters were used to generate REF to scale in vitro CL of these drugs in transporter-expressing cells to that in vivo. The predicted metformin renal secretory CL (CLr,sec) using transporter-expressing cells was within the range of clinically observed CLr,sec of metformin. In contrast, the transporter-expressing cells underpredicted the in vivo hepatic uptake CL of RSV but well-predicted the uptake CL of RSV into hepatocytes. Though the reason for this underprediction is not known, it could be due to lower intrinsic uptake CL of RSV in transporter-expressing cells in the absence of plasma proteins. Nevertheless, the predicted hepatic CL of RSV by transporter-expressing cells was better than that predicted by any of the hepatocyte models. Additional studies are warranted to investigate the effect of plasma proteins on the transporter-mediated CL of a drug to bridge the gap between observed and predicted CL of RSV. Collectively, our data suggest that transporter-expressing cells better predict transporter-mediated CL of RSV than human hepatocytes.
- Pharmaceutics