TY - JOUR T1 - Perspectives from the IQ Induction Working Group on Factors Impacting Clinical DDI Due to Induction: Focus on CYP3A Substrates JF - Drug Metabolism and Disposition JO - Drug Metab Dispos DO - 10.1124/dmd.119.087270 SP - dmd.119.087270 AU - Diane Ramsden AU - Conrad Fung AU - Niresh Hariparsad AU - Jane R Kenny AU - Michael A Mohutsky AU - Neil Parrott AU - Sarah Robertson AU - Donald J. Tweedie Y1 - 2019/01/01 UR - http://dmd.aspetjournals.org/content/early/2019/08/22/dmd.119.087270.abstract N2 - A recent publication from the IQ induction working group collated a large clinical dataset with the goal to evaluate the accuracy of drug-drug interaction prediction from in vitro data. Somewhat surprisingly, there was appreciable variability in the magnitude of outcome when mean or median reported AUCR were compared across studies. This commentary explores possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression and number of subjects contribute. Since variability in perpetrator PK could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5 to 7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors/inactivators, based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in AUC over time is warranted. With selective CYP3A substrates the net effect was often inhibition whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction such as applying biomarkers and PBPK are also considered.SIGNIFICANCE STATEMENT The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions. ER -