Presentation Description: Metabolism by CYP3A is major route of clearance for Brigatinib. Co-administration with strong CYP3A inhibitor or strong CYP3A inducer produced a 2-fold increase and 80% decrease in brigatinib AUC, respectively. This resulted in recommendations to avoid co-administration with strong CYP3A inhibitors/inducers although the effects of moderate inhibitors/inducers was unknown. In lieu of conducting dedicated clinical DDI studies, physiologically-based pharmacokinetic (PBPK) modeling was used to inform dosing for patients requiring co-administration of moderate CYP3A inhibitors/inducers. Model-based simulations predicted increase in brigatinib AUC by 40% with moderate CYP3A inhibitors and decrease in brigatinib AUC by 50% with moderate CYP3A inducers. The PBPK analysis informed dosing guidance for patients requiring moderate CYP3A inhibitors (40% brigatinib dose reduction) or inducers (up to 100% increase in brigatinib dose) as reflected in the current brigatinib (ALUNBRIG) USPI. This case study highlights inclusion of PBPK model-informed dosing recommendations (including higher dose with inducers) in product labeling.
Understand how PBPK model can be used in lieu of a clinical study
Describe how in vitro metabolism data, clinical ADME study data and the results of DDI studies can be used to develop and qualify a PBPK model
Describe how PBPK modeling can be used to make dosing recommendations in product labeling