In vitro characterization of axitinib interactions with human efflux and hepatic uptake transporters: implications for disposition and drug interactions.

Axitinib is an inhibitor of tyrosine kinase vascular endothelin growth factor receptors 1, 2, and 3. The ATP-binding cassette (ABC) and solute carrier (SLC) transport properties of axitinib were determined in selected cellular systems. Axitinib exhibited high passive permeability in all cell lines evaluated (Papp ≥ 6 × 10(-6) cm/s). Active efflux was observed in Caco-2 cells, and further evaluation in multidrug resistance gene 1 (MDR1) or breast cancer resistance protein (BCRP) transfected Madin-Darby canine kidney cells type 2 (MDCK) cells indicated that axitinib is at most only a weak substrate for P-glycoprotein (P-gp) but not BCRP. Axitinib showed incomplete inhibition of P-gp-mediated transport of digoxin in Caco-2 cells and BCRP transport of topotecan in BCRP-transfected MDCK cells with IC50 values of 3 µM and 4.4 µM, respectively. Axitinib (10 mg) did not pose a risk for systemic drug interactions with P-gp or BCRP per regulatory guidance. A potential risk for drug interactions through inhibition of P-gp and BCRP in the gastrointestinal tract was identified because an axitinib dose of 10 mg divided by 250 mL was greater than 10-fold the IC50 for each transporter. However, a GastroPlus simulation that considered the low solubility of axitinib resulted in lower intestinal concentrations and suggested a low potential for gastrointestinal interactions with P-gp and BCRP substrates. Organic anion transporting polypeptide 1B1 (OATP1B1) and OATP1B3 transfected human embryonic kidney 293 (HEK293) cells transported axitinib to a minor extent but uptake into suspended hepatocytes was not inhibited by rifamycin SV suggesting that high passive permeability predominates. Mouse whole-body autoradiography revealed that [(14)C]axitinib-equivalents showed rapid absorption and distribution to all tissues except the brain. This suggests that efflux transport of axitinib may occur at the mouse blood-brain barrier.

Identification of novel substrates for human cytochrome P450 2J2.

Several antihistamine drugs including terfenadine, ebastine, and astemizole have been identified as substrates for CYP2J2. The overall importance of this enzyme in drug metabolism has not been fully explored. In this study, 139 marketed therapeutic agents and compounds were screened as potential CYP2J2 substrates. Eight novel substrates were identified that vary in size and overall topology from relatively rigid structures (amiodarone) to larger complex structures (cyclosporine). The substrates displayed in vitro intrinsic clearance values ranging from 0.06 to 3.98 mul/min/pmol CYP2J2. Substrates identified for CYP2J2 are also metabolized by CYP3A4. Extracted ion chromatograms of metabolites observed for albendazole, amiodarone, astemizole, thioridazine, mesoridazine, and danazol showed marked differences in the regioselectivity of CYP2J2 and CYP3A4. CYP3A4 commonly metabolized compounds at multiple sites, whereas CYP2J2 metabolism was more restrictive and limited, in general, to a single site for large compounds. Although the CYP2J2 active site can accommodate large substrates, it may be more narrow than CYP3A4, limiting metabolism to moieties that can extend closer toward the active heme iron. For albendazole, CYP2J2 forms a unique metabolite compared with CYP3A4. Albendazole and amiodarone were evaluated in various in vitro systems including recombinant CYP2J2 and CYP3A4, pooled human liver microsomes (HLM), and human intestinal microsomes (HIM). The Michaelis-Menten-derived intrinsic clearance of N-desethyl amiodarone was 4.6 greater in HLM than in HIM and 17-fold greater in recombinant CYP3A4 than in recombinant CYP2J2. The resulting data suggest that CYP2J2 may be an unrecognized participant in first-pass metabolism, but its contribution is minor relative to that of CYP3A4.

Beyond pass/fail: a procedure for evaluating the effect of carryover in bioanalytical LC/MS/MS methods.

Eliminating carryover from bioanalytical methods can be a time and resource consuming process. While it is necessary to investigate root causes of the carryover and reduce problem areas, complete elimination of carryover may not be practical or even possible. The purpose of this paper is to suggest an avenue to investigate the effect of carryover within an analytical run rather than employ a simple pass/fail criterion. With more robust carryover information a risk threshold level can be established for individual injections based on the peak response of the previous injection. It is then possible to quickly evaluate the risk that any value in an analytical run has been adversely affected by a previous injection. Those samples which are identified as "at risk" can be reanalyzed to obtain a value that is not affected.