Identification of human cytochrome P(450)s that metabolise anti-parasitic drugs and predictions of in vivo drug hepatic clearance from in vitro data.

OBJECTIVE

Knowledge about the metabolism of anti-parasitic drugs (APDs) will be helpful in ongoing efforts to optimise dosage recommendations in clinical practise. This study was performed to further identify the cytochrome P(450) (CYP) enzymes that metabolise major APDs and evaluate the possibility of predicting in vivo drug clearances from in vitro data.

METHODS

In vitro systems, rat and human liver microsomes (RLM, HLM) and recombinant cytochrome P(450) (rCYP), were used to determine the intrinsic clearance (CL(int)) and identify responsible CYPs and their relative contribution in the metabolism of 15 commonly used APDs.

RESULTS AND DISCUSSION

CL(int) determined in RLM and HLM showed low (r(2)=0.50) but significant ( P<0.01) correlation. The CL(int) values were scaled to predict in vivo hepatic clearance (CL(H)) using the 'venous equilibrium model'. The number of compounds with in vivo human CL data after intravenous administration was low ( n=8), and the range of CL values covered by these compounds was not appropriate for a reasonable quantitative in vitro-in vivo correlation analysis. Using the CL(H) predicted from the in vitro data, the compounds could be classified into three different categories: high-clearance drugs (>70% liver blood flow; amodiaquine, praziquantel, albendazole, thiabendazole), low-clearance drugs (<30% liver blood flow; chloroquine, dapsone, diethylcarbamazine, pentamidine, primaquine, pyrantel, pyrimethamine, tinidazole) and intermediate clearance drugs (artemisinin, artesunate, quinine). With the exception of artemisinin, which is a high clearance drug in vivo, all other compounds were classified using in vitro data in agreement with in vivo observations. We identified hepatic CYP enzymes responsible for metabolism of some compounds (praziquantel-1A2, 2C19, 3A4; primaquine-1A2, 3A4; chloroquine-2C8, 2D6, 3A4; artesunate-2A6; pyrantel-2D6). For the other compounds, we confirmed the role of previously reported CYPs for their metabolism and identified other CYPs involved which had not been reported before.

CONCLUSION

Our results show that it is possible to make in vitro-in vivo predictions of high, intermediate and low CL(int) drug categories. The identified CYPs for some of the drugs provide a basis for how these drugs are expected to behave pharmacokinetically and help in predicting drug-drug interactions in vivo.