Successful Prediction of Positron Emission Tomography-Imaged Metformin Hepatic Uptake Clearance in Humans Using the Quantitative Proteomics-Informed Relative Expression Factor Approach.

Predicting transporter-mediated in vivo hepatic drug clearance (CL) from in vitro data (IVIVE) is important in drug development to estimate first-in-human dose and the impact of drug interactions and pharmacogenetics on hepatic drug CL. For IVIVE, one can use human hepatocytes and the traditional milligrams of protein content per gram of liver tissue (MGPGL) approach. However, this approach has been found to consistently underpredict the observed in vivo hepatic drug CL. Therefore, we hypothesized that using transporter-expressing cells and the relative expression factor (REF), determined using targeted quantitative proteomics, will accurately predict in vivo hepatic CL of drugs. We have successfully tested this hypothesis in rats with rosuvastatin, which is transported by hepatic Organic anion transporting polypeptides (OATPs). Here, we tested this hypothesis for another drug and another transporter; namely, organic cation transporter (OCT)1-mediated hepatic distributional CL of metformin. First, we estimated the in vivo metformin hepatic sinusoidal uptake CL (CL) of metformin by reanalysis of previously published human positron emission tomography imaging data. Next, using the REF approach, we predicted the in vivo metformin CL using OCT1-transporter-expressing HEK293 cells or plated human hepatocytes. Finally, we compared this REF-based prediction with that using the MGPGL approach. The REF approach accurately predicted the in vivo metformin hepatic CL, whereas the MGPGL approach considerably underpredicted the in vivo metformin CL Based on these and previously published data, the REF approach appears to be superior to the MGPGL approach for a diverse set of drugs transported by different transporters. SIGNIFICANCE STATEMENT: This study is the first to use organic cation transporter 1-expressing cells and plated hepatocytes to compare proteomics-informed REF approach with the traditional MGPGL approach to predict hepatic uptake CL of metformin in humans. The proteomics-informed REF approach, which corrected for plasma membrane abundance, accurately predicted the positron emission tomography-imaged metformin hepatic uptake CL, whereas the MGPGL approach consistently underpredicted this CL.