A novel approach for modeling in vivo enzyme turnover in the presence of a suicide inhibitor drug: A proof-of-concept brain PET study on MAG lipase

Abstract

PET imaging allows the study of enzyme concentration and activity in vivo. The enzyme natural turnover $\alpha$ , relevant for drug development, can be estimated if a suicide inhibitor drug is used. The main aim of this study was to develop a model for estimating $\alpha$ by accounting for the presence of residual inhibitor. We analyzed nonhuman primate PET data with monoacyglycerol lipase (MAGL) tracer [¹¹C]PF-06809247, and suicide inhibitor PF-06818883 (0.03–1.27 mg/kg, active compound PF-06807893). As [¹¹C]PF-06809247 is an irreversible tracer, we used simulations to evaluate the impact of flow limitation on identifiability of kinetic parameters. Based on this, MAGL activity estimates were obtained from three outcome parameters: K_i, k₃, ${\tilde{K}}_3$ (= $\frac{K_1{K}_{\mathrm{i}}}{K_1{-K}_{\mathrm{i}}}$ ). A new model, which links enzyme activity to the inhibitor drug’s plasma concentration, was used to estimate $\alpha$ . Using a conservative statistical cut-off, MAGL turnover half-lives were estimated (K_i: 3.9 h; k₃: 4.6 h; ${\tilde{K}}_3$ : 6.1 h) – with faster turnover for K_i (flow-limited). Serial PET experiments and measuring the drug’s plasma concentration allowed to estimate $\alpha$ correcting for residual suicide inhibition. This approach can be extended to other PET enzyme targets, improving our understanding of enzyme pathological alterations and suicide inhibitor-based therapies.