Contribution of Extrahepatic Aldehyde Oxidase Activity to Human Clearance

Kozminski, Kirk; Selimkhanov, Jangir; Heyward, Scott; Zientek, Michael

doi:10.1124/dmd.120.000313

Cited by 8 publications

(5 citation statements)

References 37 publications

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“…The loss of AO activity during the processes of tissue isolation, homogenization and storage has been frequently discussed as one of the probable reasons for poor IVIVE predictions (Kozminski et al, 2021;Zientek et al, 2010). Our study shows for the first time that AO enzyme degrades ~10 times faster in the presence of the substrate (carbazeran) which could be possibly triggered by certain catalytic events and an inability of the enzyme to regenerate its active state, as suggested elsewhere (Abbasi et al, 2019).…”

Section: Discussionsupporting

confidence: 70%

“…Though the content of AO in the extrahepatic tissues may be low, the content may not necessarily correlate with the activity and the combined contribution of these tissues towards CL of an AO substrate may be significant. However, for IVIVE predictions, the scaled in vitro CL int of carbazeran integrating data from kidney, lung, vasculature, and intestinal S9 fractions along with hepatic CL int did not show significant role of extrahepatic tissues in in vivo clearance (Kozminski et al, 2021). This discrepancy can be explained by the fact that the stability of AO in S9 fractions may be compromised leading to underprediction of AO mediated metabolism.…”

Section: Discussionmentioning

confidence: 90%

“…Thus, the conventional substrate depletion approach to scale in vitro intrinsic clearances for IVIVE, using longer incubation time, for example >10 min for carbazeran (Zientek et al, 2010, Hutzler et al, 2014, de Sousa Mendes et al, 2020 may not be ideal for AO substrates. A modified activity model which accounts for the loss of activity with time, is also recommended by others for estimating CL int for AO substrates (Abbasi et al, 2019, Kozminski et al, 2021.…”

Section: Discussionmentioning

confidence: 99%

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Dissecting Parameters Contributing to the Underprediction of Aldehyde Oxidase-Mediated Metabolic Clearance of Drugs

et al. 2023

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We investigated the effect of variability and instability in aldehyde oxidase (AO) content and activity on scaling of in vitro metabolism data. AO content and activity in human liver cytosol (HLC) and five recombinant human AO preparations (rAO) were determined using targeted proteomics and carbazeran oxidation assay, respectively. AO content was highly variable as indicated by the relative expression factor (REF, i.e., HLC to rAO content) ranging from 0.001-1.7 across different in vitro systems. The activity of AO in HLC degrades at a 10-fold higher rate in the presence of the substrate as compared to the activity performed after preincubation without substrate. To scale the metabolic activity from rAO to HLC, a protein-normalized activity factor (pnAF) was proposed wherein the activity was corrected by AO content, which revealed upto 6-fold higher AO activity in HLC versus rAO systems. A similar value of pnAF was observed for another substrate, ripasudil. Physiologically-based pharmacokinetic (PBPK) modeling revealed a significant additional clearance (CL; 66%), which allowed successful prediction of in vivo CL of four other substrates, i.e., O-benzyl guanine, BIBX1382, zaleplon and zoniporide. For carbazeran, the metabolite identification study showed that the direct glucuronidation may be contributing to around 12% elimination. Taken together, this study identified differential protein content, instability of in vitro activity, role of additional AO clearance and unaccounted metabolic pathways as plausible reasons for the underprediction of AO mediated drug metabolism. Consideration of these factors and integration of REF and pnAF in PBPK models will allow better prediction of AO metabolism.

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Section: Discussionsupporting

confidence: 70%

Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

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Dissecting Parameters Contributing to the Underprediction of Aldehyde Oxidase-Mediated Metabolic Clearance of Drugs

et al. 2023

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“…predicted from S9 fractions were to be <1% of the liver (Kozminski et al, 2021). For the compounds with CL H exceeding Q H , the cut-off CL H of 90% of Q H was applied (Cubitt et al, 2009) in the calculation of CL int,u via the well-stirred liver model.…”

Section: Database Analysismentioning

confidence: 99%

Challenges and Opportunities for In Vitro–In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation

Izat,

Bolleddula,

Abbasi

et al. 2023

Drug Metab Dispos

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Underestimation of AO-mediated clearance by current in vitro assays leads to uncertainty in human dose projections, thereby reducing the likelihood of success in drug development. In the present study we first evaluated the current drug development practices for AO substrates. Next, the overall predictive performance of in vitro-in vivo extrapolation (IVIVE) of unbound hepatic intrinsic clearance (CL int,u ) and unbound hepatic intrinsic clearance by AO (CL int,u,AO ) was assessed using a comprehensive literature database of in vitro (human cytosol/ S9/ hepatocytes) and in vivo (iv/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation (fu inc ) was done by experimental data or in silico predictions. The fraction metabolized by AO (fm AO ) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CL int,u (mL/min/kg) were 10.4 for human hepatocytes, 5.6 for human liver cytosols, and 5.0 for human liver S9, respectively. Application of these gmfe's as empirical scaling factors improved predictions (45-57% within 2-fold of observed) compared with no correction (11-27% within 2-fold), with the scaling factors qualified by leave-oneout cross-validation. A road map for quantitative translation was then proposed following a critical evaluation on the in vitro and clinical methodology to estimate in vivo fm AO . In conclusion, the study provides the most robust system-specific empirical scaling factors to-date as a pragmatic approach for the prediction of in vivo CL int,u,AO in the early stages of drug development.

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“…Taken together, the work reported by Abbasi et al (2019) along with the recent report by Garrido and Leimkühler (2021) provide important contributions to aid the development of improved strategies for estimating intrinsic clearance of AO substrates. Furthermore, as a recent report suggested that extrahepatic AO is unlikely to explain the in vitro -in vivo disconnect in AO-mediated clearance ( Kozminski et al 2021 ), the notion that the observed discrepancy is related to incomplete modeling of the enzyme’s kinetics and/or suboptimal assay conditions may now be taking the lead as the most likely explanation, in addition to interindividual variability, as highlighted by differing inactivation rates between the wild-type and L438V enzymes.…”

Section: Commentarymentioning

confidence: 99%

Bioactivation and reactivity research advances – 2021 year in review

Jackson

Argikar

Cho³

et al. 2022

Drug Metabolism Reviews

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This year’s review on bioactivation and reactivity began as a part of the annual review on biotransformation and bioactivation led by Cyrus Khojasteh (see references). Increased contributions from experts in the field led to the development of a stand alone edition for the first time this year focused specifically on bioactivation and reactivity. Our objective for this review is to highlight and share articles which we deem influential and significant regarding the development of covalent inhibitors, mechanisms of reactive metabolite formation, enzyme inactivation, and drug safety. Based on the selected articles, we created two sections: (1) reactivity and enzyme inactivation, and (2) bioactivation mechanisms and safety ( Table 1 ). Several biotransformation experts have contributed to this effort from academic and industry settings.

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Contribution of Extrahepatic Aldehyde Oxidase Activity to Human Clearance

Cited by 8 publications

References 37 publications

Dissecting Parameters Contributing to the Underprediction of Aldehyde Oxidase-Mediated Metabolic Clearance of Drugs

Dissecting Parameters Contributing to the Underprediction of Aldehyde Oxidase-Mediated Metabolic Clearance of Drugs

Challenges and Opportunities for In Vitro–In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation

Bioactivation and reactivity research advances – 2021 year in review

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