PBPK Modelling of PROTACs: Learnings from ARV-110 as a Case Example.

Area of Science:

• Pharmacology and Drug Development
• Computational Biology and Bioinformatics
• Translational Medicine

Background:

• Proteolysis Targeting Chimeras (PROTACs) represent a novel therapeutic modality.
• Physiologically-based pharmacokinetic (PBPK) modeling is crucial for predicting drug behavior in humans.
• Accurate prediction of PROTAC pharmacokinetics (PK) is essential for clinical translation.

Purpose of the Study:

• To develop and validate a PBPK model for predicting the human PK of ARV-110 (Bavdegalutamide), a PROTAC.
• To assess the accuracy of PBPK modeling in bridging in vitro-in vivo extrapolation (IVIVE) gaps for PROTACs.
• To establish a translational PBPK framework for oral PROTAC PK prediction.

Main Methods:

• A bottom-up PBPK modeling approach was initially used for ARV-110 in rodents.
• Middle-out PBPK modeling was employed to refine predictions by incorporating in vivo data, addressing IVIVE gaps.
• The developed PBPK model was extrapolated to humans and validated against clinical PK data from healthy volunteers and cancer patients.

Main Results:

• The refined PBPK model accurately captured ARV-110 plasma concentration-time profiles in preclinical and clinical studies.
• Human PK predictions were within acceptable ranges (within 5th-95th percentile of observed concentrations and two-fold of PK parameters).
• The model successfully predicted the impact of food and drug-drug interactions (itraconazole, esomeprazole) on ARV-110 PK.

Conclusions:

• A translational PBPK framework can effectively predict human oral PK for PROTACs like ARV-110.
• Refinement strategies, such as middle-out modeling, are necessary to overcome IVIVE challenges in PROTAC PBPK.
• Generating robust preclinical data is critical for enhancing the accuracy of PBPK predictions in PROTAC drug development.