Leveraging In Vitro Data to Improve Prediction of Drug Clearance in Renally-impaired Populations

Renal Impairment (RI) is a major and growing health concern in the US and globally. It can occur alone or can accompany a number of disease states. RI affects the pharmacokinetics (PK) of many compounds due to a decrease in the glomerular filtration rate (GFR) with the decline of kidney function. In addition to these changes to GFR, changes in protein binding, drug transporter expression, and activity have been identified in RI. Many of these changes are mediated by elevated concentrations of uremic toxins in RI, which can cause toxin-drug interactions (TDIs).

These additional changes on the PK of compounds that are actively transported in the kidney carry both clinical and regulatory relevance. Patients with RI often require dose-adjustments for renally-cleared drugs. Also, the FDA currently recommends that drug developers conduct clinical trials in RI populations for investigational drugs where 30% or more of the drug is eliminated renally.

Physiologically-based pharmacokinetic (PBPK) modeling has been increasingly used to predict PK in specialized populations. The Simcyp Simulator PBPK modeling platform contains specialized virtual populations, including those for RI. The advantage of using a PBPK approach is that it can incorporate physiologically-relevant information about specialized populations such as organ size and function as well as information from in vitro studies.

This webinar focused on the impact of RI on substrates of organic cation transporter 2 (OCT2), one of the major renal transporters which has been shown to be affected—both in activity and expression—in RI in pre-clinical species and in vitro systems.

The objectives of this webinar were to demonstrate the following:

  • The impact of alterations in GFR, protein binding, and TDIs on PK predictions for the OCT2 model substrate, metformin
  • The utility of available in vitro data to improve predictions of renal clearance for OCT2 substrates in clinical RI populations.