Article

Pharmaceutical Research

, Volume 14, Issue 3, pp 337-344

First online:

Physiologically Based Pharmacokinetic Models of 2′,3′-Dideoxyinosine

  • Hyo-Jeong K. KangAffiliated withCollege of Pharmacy, The Ohio State University
  • , M. Guillaume WientjesAffiliated withCollege of Pharmacy, The Ohio State UniversityDivision of Urology, College of Medicine, The Ohio State UniversityComprehensive Cancer Center, The Ohio State University
  • , Jessie L.-S. AuAffiliated withDivision of Urology, College of Medicine, The Ohio State University

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Abstract

Purpose. The goal of this study was to develop physiologically based pharmacokinetic (PBPK) models for 2′,3′-dideoxyinosine (ddI) in rats when the drug was administered alone (ddI model) and with pentamidine (ddI + pentamidine model), and to use these models to evaluate the effect of our previously reported pentamidine-ddI interaction on tissue ddI exposure in humans.

Methods. The PBPK models consisted of pharmacologically relevant tissues (blood, brain, gut, spleen, pancreas, liver, kidney, lymph nodes, muscle) and used the assumptions of perfusion-rate limited tissue distribution and linear tissue binding of ddI. The required physiologic model parameters were obtained from the literature, whereas the pharmacokinetic parameters and the tissue-to-plasma partition coefficients were calculated using plasma and tissue data.

Results. The ddI model in rats yielded model-predicted concentration-time profiles that were in close agreement with the experimentally determined profiles after an intravenous ddI dose (5% deviation in plasma and 20% deviation in tissues). The ddI + pentamidine model incorporated the pentamidine-induced increases of ddI partition in pancreas and muscle. The two PBPK models were scaled-up to humans using human physiologic and pharmacokinetic parameters. A comparison of the model-predicted plasma concentration-time profiles with the observed profiles in AIDS patients who often received ddI with pentamidine showed that the ddI model underestimated the terminal half-life (t1/2,β) by 39% whereas the ddI + pentamidine model yielded identical t1/2,β and area-under-the-curve as the observed values (<1% deviation). Simulations of ddI concentration-time profiles in human tissues using the two models showed that pancreas and lymph nodes received about 2- to 30-fold higher ddI concentration than spleen and brain, and that coadministration of pentamidine increased the AUC of ddl in the pancreas by 20%.

Conclusions. Data of the present study indicate that the plasma ddI concentration-time profile in patients were better described by the ddI + pentamidine model than by the ddI model, suggesting that the pentamidine-induced changes in tissue distribution of ddI observed in rats may also occur in humans.

ddI physiologic pharmacokinetic model tissue concentration pentamidine rat human