Prediction of Transporter-mediated PK and DDIs using Mechanistic PBPK Models: Challenges and Opportunities | Dr. Bridget L. Morse
-
Register
- Non-member - $49
- Member - Free!
- Student - Free!
- Premier - Free!
Use of physiologically-based pharmacokinetic (PBPK) modeling for predicting the clearance and drug-drug interactions (DDIs) for transporter substrates addresses many disadvantages in using allometry or static models. These include species differences in transporter expression, expression of transporters at more than one physiological site, prediction of plasma/tissue concentration profiles over time, and potential to incorporate effects of extrinsic factors on transporter function.
For predicting human renal clearance, allometry has been demonstrated to predict rather well, regardless of the role of transporters in renal clearance. There are a few examples for prediction of renal clearance using PBPK modeling directly using in vitro transporter data, and these demonstrate generally acceptable predictivity particularly for organic anion transporters (OATs) 1/3. Similarly for the prediction of OAT-mediated DDIs, both static and PBPK modeling have been generally predictive using in vitro inhibition constants. Recent work has shown that modeling renal secretion by OCT2/MATEs and other transporters to be less straightforward.
Alternatively, for hepatic transport mediated by organic anion transporting polypeptides (OATPs), multiple efforts have shown that clearance is underpredicted using in vitro uptake clearances from primary hepatocytes in PBPK models. As such, when predicting human CL using PBPK modeling, scaling factors often have to be incorporated. Similarly, DDIs mediated by the OATPs tend to be underpredicted by PBPK models when in vitro inhibition constants are used directly. Regarding hepatic clearance mediated by organic cation transporter (OCT) 1, there has been little investigation on the use of PBPK modeling for predicting clearance of these substrates.
This webinar will address the current state of the science in using PBPK modeling for prediction of human pharmacokinetics and DDIs for transporter substrates, including strategies for addressing discrepancies in in vitro-to-in vivo extrapolation.
Bridget Morse
Prediction of Transporter-mediated PK and DDIs using Mechanistic PBPK Models: Challenges and Opportunities
Bridget L. Morse, Pharm.D., Ph.D. is currently a Principal Research Scientist in the Drug Disposition Department at Lilly Research Laboratories in Indianapolis, Indiana, which she joined in 2016. She received her Pharm.D. from Butler University in Indianapolis and her Ph.D. from the University at Buffalo, followed by a postdoctoral fellowship at the University of Western Ontario. She worked in the transporter group within the department of Metabolism and Pharmacokinetics at Bristol Myers-Squibb for 2 years prior to joining Eli Lilly. At Lilly, she serves as a subject matter expert in pharmacokinetics, transporters, and drug-drug interactions, particularly in the use PBPK modeling for hepatic transporter substrates and interspecies translation of hepatic disposition. She has published over 20 journal articles and a co-authors a recurring chapter on Membrane Drug Transporters in Foye's Principles of Medicinal Chemistry. She is currently Chair-elect of the AAPS Drug Transporter Community and sits on the Editorial Advisory Board for the AAPS Journal.
Key:
Complete
Next
Failed
Available
Locked