The Promises of Quantitative Transporter Proteomics: IVIVE to Precision Medicine

Webinar was presented on September 3rd, 2015 by Dr. Bhagwat Prasad, Principal investigator in the Department of Pharmaceutics, University of Washington (UW), Seattle, WA, USA

Summary of the presentation

Transporters play critical roles in drug clearance and disposition. The in vitro approaches such as recombinant cell-lines/vesicles expressing transporters are crucial to identify individual transporters involved in cellular uptake/efflux clearance of drugs. However, since in vitro models do not represent physiological expression and inter-individual variability of transporters, it is important to normalize the in vitro data by the in vivo protein expression or activity. While the sandwich-cultured human hepatocyte data are currently used as representative of in vivo hepatic expression/activity, these data usually result inaccurate in vivo predictions. Moreover, the viable primary cell based transporter models are not available for tissues other than the liver.

Therefore, it is critical that alternate approaches are used to better translate in vitro data to in vivo disposition (IVIVE). One such approach is to use human tissue transporter expression as a surrogate to generate physiologically relevant scaling factors for IVIVE of transporter disposition. To quantify drug transporters, LC-MS/MS targeted proteomics has emerged as a novel and promising technique. The latter relies on the quantification of surrogate peptides generated from the non-membrane domain of transporters. The technique has unique advantages, like, i) ability to simultaneously quantify multiple proteins, ii) very high selectivity derived from MRM feature of LC-MS/MS, and iii) reproducibility and data quality derived from multiple endpoints (peptides/fragments).

The transporter expression based physiological modeling approach could also be used to predict tissue concentration, i.e., the site of efficacy or toxicity, which is otherwise not routinely determined. Similarly, transporter quantification in banked tissues from a diverse population could be utilized to predict effect of age/development (ontogeny), diseases, genetic and epigenetic factors on transporter mediated clearance. These data are critical toward precision medicine. In this webinar, the potential application of LC-MS/MS transporter expression data in the IVIVE and prediction of inter-individual variability will be discussed with some examples from our recent work at the University of Washington.