AZD-5672

Modeling the relationship between drug concentrations and heart rate corrected QT interval (QTc) change from baseline (C-∆QTc), based on Phase I single ascending dose (SAD) or multiple ascending dose (MAD) studies, has been proposed as an alternative to thorough QT studies (TQT), in assessing drug-induced QT prolongation risk. The present analysis used clinical SAD, MAD and TQT study data of an experimental compound, AZD5672, to evaluate the performance of: (i) three computational platforms (linear mixed-effects modeling implemented via PROC MIXED in SAS, as well as in R using LME4 package and linear quantile mixed models (LQMM) implemented via LQMM package; (ii) different model structures with and without treatment- or time-specific intercepts; and (iii) three methods for calculating the confidence interval (CI) of QTc prolongation (analytical and bootstrap methods with fixed or varied geometric mean concentrations). We show that treatment- and time-specific intercepts may need to be included into C-∆QTc modeling through PROC MIXED or LME4, regardless of their statistical significance. With the intersection union test (IUT) in the TQT study as a reference for comparison, inclusion of these intercepts increased the feasibility for C-∆QTc modelling of SAD or MAD to reach the same conclusion as the IUT analysis based on TQT study. Compared to PROC MIXED or LME4, the LQMM method is less dependent on inclusion of treatment- or time-specific intercepts, and the bootstrap CI calculation methods provided higher likelihood for C-∆QTc modeling of SAD and MAD studies to reach the same conclusion as the IUT based on the TQT study.

The oral dipeptidyl peptidase 1 (DPP1) inhibitor AZD5248 showed aortic binding in a rat quantitative whole-body autoradiography (QWBA) study, and its development was terminated prior to human dosing. A mechanistic hypothesis for this finding was established invoking reactivity with aldehydes involved in the cross-linking of elastin, a major component of aortic tissue. This was tested by developing a simple aldehyde chemical reactivity assay and a novel in vitro competitive covalent binding assay. Results obtained with AZD5248, literature compounds, and close analogues of AZD5248 support the mechanistic hypothesis and provide validation for the use of these assays in a two tier screening approach to support lead optimization. The strengths and limitations of these assays are discussed.