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

Underestimation of aldehyde oxidase (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 of unbound hepatic intrinsic clearance (CLint,u) and unbound hepatic intrinsic clearance by AO (CLint,u,AO) was assessed using a comprehensive literature database of in vitro (human cytosol/S9/hepatocytes) and in vivo (intravenous/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation was done by experimental data or in silico predictions. The fraction metabolized by AO (fmAO) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CLint,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 twofold of observed) compared with no correction (11%-27% within twofold), with the scaling factors qualified by leave-one-out 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 fmAO 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 CLint,u,AO in the early stages of drug development. SIGNIFICANCE STATEMENT: Confidence remains low when predicting in vivo clearance of AO substrates using in vitro systems, leading to de-prioritization of AO substrates from the drug development pipeline to mitigate risk of unexpected and costly in vivo impact. The current study establishes a set of empirical scaling factors as a pragmatic tool to improve predictability of in vivo AO clearance. Developing clinical pharmacology strategies for AO substrates by utilizing mass balance/clinical drug-drug interaction data will help build confidence in fmAO.

Validation of a total IC50 method which enables in vitro assessment of transporter inhibition under semi-physiological conditions.

1. Accurate predictions of clinical transporter-mediated drug-drug interactions (DDI) from in vitro data can be challenging when compounds have poor solubility and/or high nonspecific binding. Additionally, current DDI predictions for compounds with high plasma-protein binding assume that the unbound fraction in plasma is 0.01, if the experimental value is less than 0.01 or cannot be determined. This approach may result in an overestimation of DDI risk. To overcome these challenges, it may be beneficial to conduct inhibition studies under physiologically relevant conditions. 2. Here, IC50 values, determined in the presence of 4% bovine serum albumin approximating human plasma albumin concentrations, were successfully used to predict DDI for uptake transporters, OATP1B1/1B3, OCT1/2, OAT1/3 and MATE1/2K. 3. The IC50 values of reference inhibitors with 4% bovine serum albumin, considered total IC50, were comparable to the predicted values based on nominal IC50 values determined under protein-free conditions and unbound fraction in plasma. Calculation of R-total and Cmax/IC50,total values using total plasma exposure and total IC50 values explained the clinical DDI or absence of it for these inhibitors. 4. These results suggest that IC50 determinations in the presence of 4% albumin can be used, in the context of clinical total exposure, to predict DDI involving uptake transporters.

Limited influence of UGT1A1*28 and no effect of UGT2B7*2 polymorphisms on UGT1A1 or UGT2B7 activities and protein expression in human liver microsomes.

AIMS: UGT1A1 and UGT2B7 are enzymes that commonly contribute to drug glucuronidation. Since genetic factors have been suggested to contribute to variability in activities and expression levels of these enzymes, a quantitative assessment of the influence of the major genotypes (UGT1A1*28 or UGT2B7*2) on enzyme activities was conducted. METHODS: Using a bank of microsomal samples from 59 human livers, the effect of UGT1A1*28 or UGT2B7*2 polymorphisms were investigated on rates of estradiol 3-glucuronidation (a marker of UGT1A1 enzyme activity) or zidovudine glucuronidation (a marker of UGT2B7 enzyme activity) and levels of immunoreactive protein for each enzyme. Glucuronidation rates for both enzymes were measured at K(m)/S(50) and 10 times K(m)/S(50) concentrations. RESULTS: UGT1A1 and UGT2B7 enzyme activities varied up to 16-fold and sixfold, respectively. Rates at K(m)/S(50) concentration closely correlated with rates at 10 times K(m)/S(50) concentration for both enzymes (but not at 1/10th K(m) for UGT2B7). Enzyme activities correlated with relative levels of immunoreactive protein for UGT1A1 and UGT2B7. Furthermore, rates of zidovudine glucuronidation correlated well with rates of glucuronidation of the UGT2B7 substrate gemcabene, but did not correlate with UGT1A1 enzyme activities. For the UGT1A1*28 polymorphism, consistent with levels of UGT1A1 immunoreactive protein, mean UGT1A1 activity was 2.5- and 3.2-fold lower for TA(6)/TA(7) (P < 0.05) and TA(7)/TA(7) (P < 0.001) genotypes in comparison with the TA(6)/TA(6) genotype. CONCLUSIONS: Relative to the observed 16-fold variability in UGT1A1 activity, these data indicate only a partial (approximately 40%) contribution of the UGT1A1*28 polymorphism to variability of interindividual differences in UGT1A1 enzyme activity. For the UGT2B7*2 polymorphism, genotype had no influence on immunoreactive UGT2B7 protein or the rate of 3'-azido-3'-deoxythymidine glucuronidation.