In situ studies of regional absorption of lobucavir and ganciclovir from rabbit intestine and predictions of dose‐limited absorption and associated variability in humans

The regional absorption of lobucavir (LBV), an experimental antiviral agent, and ganciclovir (DHPG) was investigated in rabbit intestine using an in situ single‐pass perfusion technique. Duodenal, jejunal, and colonic segments in anesthetized rabbits were perfused with drug solutions in a hypotonic buffer at 0.2 mL/min. Effluent perfusate samples for drug analysis were collected every 10 min for 180 min. To account for water absorption during perfusion, an intestinal absorption model was developed to estimate the absorptive clearance (PeA): PeA = Qave × ln((Qin × Cin)/(Qout × Cout)), where Qave is a logarithmic average of the inflow (Qin) and outflow perfusion rate (Qout); Cin and Cout are drug inflow and outflow concentrations. The PeA of LBV in the duodenum and jejunum was 2.1 ± 0.77 and 1.7 ± 0.46 µL/min/cm (n = 3), respectively, 4.8‐ and 3.0‐fold higher than that of DHPG in the same animals. However, LBV PeA decreased significantly in the colon (0.47 ± 0.11 µL/min/cm) and was similar to that of DHPG which exhibited no regional differences in absorption. The interplay between PeA and solubility was studied using a compartmental absorption and transit model, and simulations were performed to investigate dose‐limited absorption and the sources of variability in absorption where two compounds differ significantly. The dose range where absorption started to decrease was predicted using the model, with LBV exhibiting the phenomenon at a lower dose than DHPG (450 vs. 750 mg). Furthermore, the intersubject variability in human absorption of both compounds was reproduced when the variability in both PeA and the small intestinal transit time was considered in the model. The variability in the ascending colonic transit time also contributed to the intersubject variability observed for DHPG. The results demonstrate value of integrating in situ studies and modeling in predicting these absorption characteristics.