Speaker Spotlight: Addressing the Gaps in Human PK and DDI Prediction

Tuesday, October 18, 2022

2:30 PM – 3:30 PM ET

Location:Spotlight Stage 1, Exhibit Hall A&B

Spotlight Speaker(s)

Li Di, PhD

Research Fellow
Pfizer Inc
East Lyme, Connecticut

Handouts

Moderator(s)

Naveen Thakral, PhD

Director, Pharmaceutical Sciences
Schrodinger, Inc. USA
New York, New York

Significant progress has been made in human PK and DDI prediction over several decades. However, a number of DMPK areas remain challenging in drug discovery and development. These include: (1) Measurement of clearance and fraction metabolized (fm) of low clearance compounds, (2) Impacts of enzyme-transporter-passive permeability interplay and albumin effects on clearance and tissue Kpuu, (3) Translation of permeability-limited metabolism from in vitro hepatocytes to in vivo human clearance, (4) Prediction of human biliary clearance using in vitro and in vivo animal models, (5) Accuracy of plasma protein binding measurement for highly bound compounds to enable reliable DDI prediction, and (6) Vss prediction accuracy. This presentation will highlight the progresses made in addressing the gaps in human PK and DDI prediction.

Learning Objectives:

Upon completion, participants will be able to understand the current gaps in human PK and DDI predictions, and learn the accuracy of contemporary in silico, in vitro and in vivo methods in prediction of human Vss.
Upon completion, participants will be able to learn permeability-limited metabolism and DDI in hepatocytes as well as how to predict human clearance and DDI when there is a disconnect between liver microsomes and hepatocytes.
Upon completion, participants will be able to understand the importance of tissue Kpuu and how that impacts clearance/PK and dose prediction, as well as learn the extended clearance concept and enzyme-transporter-passive permeability interplay, and albumin effect.
Upon completion, participants will be able to learn the new in vitro tools for low clearance compounds to overcome the challenges for human PK prediction and reaction phenotyping to estimate fraction metabolized (fm) in the space of slowly turnover compounds.
Upon completion, participants will be able to learn state-of-the-art methods of plasma protein binding for highly bound compounds and how that influence DDI prediction.