A discovery biotransformation strategy: combining in silico tools with high-resolution mass spectrometry and software-assisted data analysis for high-throughput metabolism.

Understanding compound metabolism in early drug discovery aids medicinal chemistry in designing molecules with improved safety and ADME properties. While advancements in metabolite prediction brings increased confidence, structural decisions require experimental data. In vitro metabolism studies using liquid chromatography and high-resolution mass spectrometry (LC-MS) are generally resource intensive and performed on very few compounds, limiting the chemical space that can be examined.Here, we describe a novel metabolism strategy increasing compound throughput using residual in vitro clearance samples conducted at drug concentrations of 0.5 µM. Analysis by robust ultra high-performance liquid chromatography separation and accurate-mass MS detection ensures major metabolites are identified from a single injection. In silico prediction (parent cLogD) tailors chromatographic conditions, with data-dependent tandem mass spectroscopy targeting predicted metabolites. Software-assisted data mining, structure elucidation and automatic reporting are used.Confidence in the globally aligned workflow is demonstrated with 16 marketed drugs. The approach is now implemented routinely across our laboratories. To date, the success rate for identification of at least one major metabolite is 85%. The utility of these data has been demonstrated across multiple projects, allowing earlier medicinal chemistry decisions to increase efficiency and impact of the design-make-test cycle thus improving the translatability of early in vitro metabolism data.

Disposition and metabolism of darapladib, a lipoprotein-associated phospholipase A2 inhibitor, in humans.

The absorption, metabolism, and excretion of darapladib, a novel inhibitor of lipoprotein-associated phospholipase A2, was investigated in healthy male subjects using [(14)C]-radiolabeled material in a bespoke study design. Disposition of darapladib was compared following single i.v. and both single and repeated oral administrations. The anticipated presence of low circulating concentrations of drug-related material required the use of accelerator mass spectrometry as a sensitive radiodetector. Blood, urine, and feces were collected up to 21 days post radioactive dose, and analyzed for drug-related material. The principal circulating drug-related component was unchanged darapladib. No notable metabolites were observed in plasma post-i.v. dosing; however, metabolites resulting from hydroxylation (M3) and N-deethylation (M4) were observed (at 4%-6% of plasma radioactivity) following oral dosing, indicative of some first-pass metabolism. In addition, an acid-catalyzed degradant (M10) resulting from presystemic hydrolysis was also detected in plasma at similar levels of ∼5% of radioactivity post oral dosing. Systemic exposure to radioactive material was reduced within the repeat dose regimen, consistent with the notion of time-dependent pharmacokinetics resulting from enhanced clearance or reduced absorption. Elimination of drug-related material occurred predominantly via the feces, with unchanged darapladib representing 43%-53% of the radioactive dose, and metabolites M3 and M4 also notably accounting for ∼9% and 19% of the dose, respectively. The enhanced study design has provided an increased understanding of the absorption, distribution, metabolism and excretion (ADME) properties of darapladib in humans, and substantially influenced future work on the compound.

Evaluation of a chimeric (uPA+/+)/SCID mouse model with a humanized liver for prediction of human metabolism.

A model that predicts human metabolism and disposition of drug candidates would be of value in early drug development. In this study, a chimeric (uPA+/+)/SCID mouse model was evaluated with three structurally distinct compounds (GW695634, a benzophenone, SB-406725, a tetrahydroisoquinoline and GW823093, a fluoropyrrolidine) for which human metabolism and disposition was characterized. Human metabolite profiles in plasma and/or urine were compared to those of chimeric (uPA+/+)/SCID and control CD-1 or (uPA+/+)/SCID) mice. GW695634 and SB-406725 exhibited primarily hepatic metabolism and were chosen as probes to assess which human metabolites would likely circulate systemically. GW823093 exhibited a combination of hepatic and extrahepatic metabolism such that renal excretion of drug-related material was ~2-fold greater in humans than in mice, and thus chosen as a probe to assess if the chimeric (uPA+/+)/SCID mouse would predict the urinary excretion of human metabolites. We observed that human metabolism and disposition was well represented for GW695634, somewhat represented for GW823093 and minimally represented for SB-406725. Collectively, the results of this and other studies suggest that while limitations for prediction of human metabolism and disposition exist, humanized chimeric mouse models can potentially represent informative new tools in drug discovery and development.