Using PBPK Modeling to Predict Drug Exposure and Support Dosage Adjustments in Patients With Renal Impairment: An Example with Lamivudine

Abstract

Lamivudine is a nucleoside reverse transcriptase inhibitor used to treat HIV and hepatitis B. It is primarily cleared by the kidney with renal secretion mediated by OCT2 and MATE. To use PBPK modeling to assess the impact of renal impairment on lamivudine pharmacokinetics using the Simcyp® Simulator. The model incorporated the Simcyp® Mechanistic Kidney Model option to predict renal disposition. The model was initially verified using the Simcyp® Healthy Volunteer population. Two discrete patient populations were then created for moderate (GFR 10-40 mL/min) and severe (GFR < 10 mL/min) renal failure (RF), and model simulations were compared to published data. The developed model was then utilized in a clinical study evaluating the clinical experience and plasma exposure of lamivudine when administered at higher than recommended doses to HIV-infected patients with varying degrees of renal impairment. Predicted systemic exposure metrics (Cmax, AUC) compared favorably to published clinical data for each population, with the following fold errors (FE, ratio of predicted and observed data) for Cmax/AUC: Healthy Volunteers 1.04/1.04, Moderate RF 1.03/0.78, Severe RF 0.89/0.79. The model captured lamivudine plasma concentrations measured pre- and post-dose (0.5-1.5hr) in study participants (n = 34). Model simulations demonstrated comparable systemic profiles across patient cohorts, supporting the proposed dosage adjustment scheme. This study illustrates how PBPK modeling can help verify dosing guidelines for patients with varying levels of renal impairment. This approach may also be useful for predicting potential changes in exposure during renal insufficiency for compounds undergoing clinical development.