Background:  Understanding antiretroviral drug interactions is a complex challenge.  Phenotyping allows for a general signal of potentially important drug interactions. This is the first investigation to simultaneously evaluate tipranavir/ritonavir (TPV/r)’s effects on intestinal and hepatic CYP3A4/5 and P-glycoprotein (P-gp) under first-dose and steady-state conditions. 

Methods:  This open-label, cross-over study was performed in 16 healthy volunteers.  Subjects were studied at baseline, and 10 hours after a first-dose and a steady-state dose of TPV/r 500 mg/200 mg twice daily. At each visit, subjects received single doses of midazolam (CYP3A4/5) intravenously and by mouth, and digoxin (P-gp) intravenously and by mouth. Plasma samples were collected over 48 hours and analyzed by validated liquid chromatography/mass spectrometry (LC/MS) methods. Pharmacokinetic parameters were calculated using a non-compartmental approach (WinNonLinPro 4.0.1), and statistics were performed using SAS. Data are presented as the geometric mean ratio (90%CI) (GMR = pharmacokinetic parameter at first dose or steady state divided by pharmacokinetic parameter at baseline) or mean (±SD).

Results:  Baseline pharmacokinetic parameters for all subjects (10 male : 6 female, 13 white; 3 black, 26.6±7.7 years, 24.2±3.4 body mass index) were within expected values. Pharmacokinetic parameter comparisons are summarized in the table.

Conclusions:  After the first dose, TPV/r moderately inhibited hepatic CYP3A4/5 and intestinal P-gp, and potently inhibited intestinal CYP3A4/5. Over time, TPV/r induced CYP3A4/5 and P-gp activity. At steady-state, overall TPV/r effects were:  moderate inhibition of hepatic CYP3A4/5, potent inhibition of intestinal CYP3A4/5, and minimal effects on P-gp activity. These data demonstrate less of an inhibitory effect on CYP3A and P-pg activity than has been seen in the past with ritonavir and other protease inhibitors, and may form the basis for understanding the interaction between TPV/r and amprenavir, lopinavir, and saquinavir. These data specifically, and this approach generally, assists with the understanding and prediction of complex drug–drug interactions.