About the Webinar
Mechanistic static models have been used to predict rosuvastatin DDI’s for over a decade and with the advancement of time have evolved to incorporate more in vitro data with more relevant in vivo parameters. Each predictive model iteration has its own assumptions and limitations and this webinar explores how this predictive tool has helped to decipher the DDI mechanism perpetrated by atazanavir.
Utilising up to date methodologies, in vitro inhibitory parameters for atazanavir were determined for a range of transporters that contribute to the absorption (BCRP) and overall disposition (OATP1B1, OAT3, NTCP, OATP1B3) of rosuvastatin clinically. Atazanavir displayed more potent inhibition for several transporters than previously published and confirmed the critical pathways of rosuvastatin disposition to be BCRP and OATP1B1 transport. In addition, it demonstrated that other more minor transporter pathways such as OATP1B3 and NTCP also play a small contributing role in manifesting the overall DDI and are therefore required for more accurate predictions. Incorporating this new data set into the latest mechanistic static model better predicts the clinically observed DDI (2.84predicted vs. 3.1clinical AUCR) between atazanavir and rosuvastatin.
The Speaker
Katie Haughan | Associate Principal Scientist, Permeability & Transporters
Katie Haughan gained a degree in Biomedical Science from the University of the West of England and has gained DMPK experience over the last 10 years working within the pharmaceutical industry at both GlaxoSmithKline and AstraZeneca, with a focus on drug transporters. Katie joined the Cyprotex Permeability and Transporter Team in 2020. As an Associate Principal Scientist, she supports and mentors scientists performing drug transporter profiling assays that contribute towards drug-drug interaction assessments, and coordinates study workflow within the laboratory