Drug clearance by aldehyde oxidase: can we avoid clinical failure?
Creators: name: Toselli, Francesca
name: Golding, Melanie
name: Nicolaï, Johan
name: Gillent, Eric
name: Chanteux, Hugues
Publisher: name: Taylor & Francis
Year: 2022
Subjects: subject: Biochemistry
subject: Space Science
subject: Pharmacology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: FOS: Biological sciences
subject: 60506 Virology

description: Despite increased awareness of aldehyde oxidase (AO) as a major drug-metabolising enzyme, predicting the pharmacokinetics of its substrates remains challenging. Several drug candidates have been terminated due to high clearance, which were subsequently discovered to be AO substrates. Even retrospective extrapolation of human clearance, from models more sensitive to AO activity, often resulted in underprediction.The questions of the current work thus were: Is there an acceptable degree of <i>in vitro</i> AO metabolism that does not result in high <i>in vivo</i> human clearance? And, if so, how can this be predicted?We built an <i>in vitro/in vivo</i> correlation using known AO substrates, combining multiple <i>in vitro</i> parameters to calculate the blood metabolic clearance mediated by AO (CLb<sub>AO</sub>). This value was compared with observed blood clearance (CLb<sub>-obs</sub>), establishing cut-off CLb<sub>AO</sub> values, to discriminate between low and high CLb<sub>-obs</sub>. The model was validated using additional literature compounds, and CLb<sub>-obs</sub> was predicted in the correct category.This simple, categorical, semi-quantitative yet multi-factorial model is readily applicable in drug discovery. Further, it is valuable for high-clearance compounds, as it predicts the CLb group, rather than an exact CLb value, for the substrates of this poorly-characterised enzyme. Despite increased awareness of aldehyde oxidase (AO) as a major drug-metabolising enzyme, predicting the pharmacokinetics of its substrates remains challenging. Several drug candidates have been terminated due to high clearance, which were subsequently discovered to be AO substrates. Even retrospective extrapolation of human clearance, from models more sensitive to AO activity, often resulted in underprediction. The questions of the current work thus were: Is there an acceptable degree of <i>in vitro</i> AO metabolism that does not result in high <i>in vivo</i> human clearance? And, if so, how can this be predicted? We built an <i>in vitro/in vivo</i> correlation using known AO substrates, combining multiple <i>in vitro</i> parameters to calculate the blood metabolic clearance mediated by AO (CLb<sub>AO</sub>). This value was compared with observed blood clearance (CLb<sub>-obs</sub>), establishing cut-off CLb<sub>AO</sub> values, to discriminate between low and high CLb<sub>-obs</sub>. The model was validated using additional literature compounds, and CLb<sub>-obs</sub> was predicted in the correct category. This simple, categorical, semi-quantitative yet multi-factorial model is readily applicable in drug discovery. Further, it is valuable for high-clearance compounds, as it predicts the CLb group, rather than an exact CLb value, for the substrates of this poorly-characterised enzyme.