“…Chemical structure of aldehyde oxidase substrate that have reported IV clearance. (Liu et al, 2005) 3 Renal clearance (L/h) 0.12 (Dolan et al, 1998;Tserng et al, 2003) 1.94 (Hutzler et al, 2012) 0 (Kaye et al, 1984) -1.65 (Micel i et al, 2005) 16. (Dalvie et et al, 2003(Dalvie et et al, ) et al, 2012(Dalvie et et al, ) al., 1984(Dalvie et et al, ) et al, 1999 al (Roy et al, 1995;Zientek et al, 2010) 860.7 (Hutzler et al, 2012) 446 (Zientek et al, 2010;Fu et al, 2013) 3.9 (Lake et al, 2002;Zientek et al, 2010) 410.3 (Obach et al, 2012) 41.2 (Dalvie et al, 2010;Zientek et al, 2010;Fu et al, 2013) Measured (this study) 10.9 1062 175 1.86 33.4 13.1…”
Aldehyde oxidase (AO) efficiently metabolizes a range of compounds with N-containing heterocyclic aromatic rings and/or aldehydes. The limited knowledge of AO activity and abundance (in vitro and in vivo) has led to poor prediction of in vivo systemic clearance (CL) using in vitro-to-in vivo extrapolation (IVIVE) approaches, which for drugs in development can lead to their discontinuation. We aimed to identify appropriate scaling factors (SF) to predict AO CL of future New Chemical Entities (NCE). The metabolism of six AO substrates was measured in human liver cytosol (HLC) and S9 fractions. Measured blood-to-plasma ratios and free fractions (in the in vitro system and in plasma) were used to develop physiologically-based pharmacokinetic (PBPK) models for each compound. The impact of extrahepatic metabolism was explored, and the intrinsic clearance required to recover in vivo profiles was estimated and compared to in vitro measurements. Using HLC data and assuming only hepatic metabolism, a systematic underprediction of clearance was observed (average fold under-prediction was 3.8). Adding extrahepatic metabolism improved the accuracy of the results (average fold error of 1.9). A workflow for predicting metabolism of an NCE by AO is proposed, an empirical (lab-specific) SF of 3 on the predicted CL IV allows a reasonable prediction of the available clinical data. Alternatively, considering also extrahepatic metabolism, a SF of 6.5 applied on the intrinsic clearance (CL int,AO) could be used. Future research should focus on the impact of the in vitro study designs and the contribution of extrahepatic metabolism to AO-mediated clearance to understand the mechanisms behind the systematic under-prediction. Significance Statement This works describes the development of scaling factors to allow in vitro-in vivo extrapolation of the clearance of compounds by aldehyde oxidase metabolism in humans. In addition, PBPK models were developed for each of the AO substrate compounds investigated.
“…Chemical structure of aldehyde oxidase substrate that have reported IV clearance. (Liu et al, 2005) 3 Renal clearance (L/h) 0.12 (Dolan et al, 1998;Tserng et al, 2003) 1.94 (Hutzler et al, 2012) 0 (Kaye et al, 1984) -1.65 (Micel i et al, 2005) 16. (Dalvie et et al, 2003(Dalvie et et al, ) et al, 2012(Dalvie et et al, ) al., 1984(Dalvie et et al, ) et al, 1999 al (Roy et al, 1995;Zientek et al, 2010) 860.7 (Hutzler et al, 2012) 446 (Zientek et al, 2010;Fu et al, 2013) 3.9 (Lake et al, 2002;Zientek et al, 2010) 410.3 (Obach et al, 2012) 41.2 (Dalvie et al, 2010;Zientek et al, 2010;Fu et al, 2013) Measured (this study) 10.9 1062 175 1.86 33.4 13.1…”
Aldehyde oxidase (AO) efficiently metabolizes a range of compounds with N-containing heterocyclic aromatic rings and/or aldehydes. The limited knowledge of AO activity and abundance (in vitro and in vivo) has led to poor prediction of in vivo systemic clearance (CL) using in vitro-to-in vivo extrapolation (IVIVE) approaches, which for drugs in development can lead to their discontinuation. We aimed to identify appropriate scaling factors (SF) to predict AO CL of future New Chemical Entities (NCE). The metabolism of six AO substrates was measured in human liver cytosol (HLC) and S9 fractions. Measured blood-to-plasma ratios and free fractions (in the in vitro system and in plasma) were used to develop physiologically-based pharmacokinetic (PBPK) models for each compound. The impact of extrahepatic metabolism was explored, and the intrinsic clearance required to recover in vivo profiles was estimated and compared to in vitro measurements. Using HLC data and assuming only hepatic metabolism, a systematic underprediction of clearance was observed (average fold under-prediction was 3.8). Adding extrahepatic metabolism improved the accuracy of the results (average fold error of 1.9). A workflow for predicting metabolism of an NCE by AO is proposed, an empirical (lab-specific) SF of 3 on the predicted CL IV allows a reasonable prediction of the available clinical data. Alternatively, considering also extrahepatic metabolism, a SF of 6.5 applied on the intrinsic clearance (CL int,AO) could be used. Future research should focus on the impact of the in vitro study designs and the contribution of extrahepatic metabolism to AO-mediated clearance to understand the mechanisms behind the systematic under-prediction. Significance Statement This works describes the development of scaling factors to allow in vitro-in vivo extrapolation of the clearance of compounds by aldehyde oxidase metabolism in humans. In addition, PBPK models were developed for each of the AO substrate compounds investigated.
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