Quantifying Complex DDIs and Filling Gaps in AO-Mediated Clearance Predictions: Translational Applications of a Novel Hepatocyte Tri-Culture System

Abstract

Accurate prediction of metabolic clearance and drug-drug interactions (DDIs) of non-CYP3A4 substrates remains a persistent challenge in drug development. In this webinar, Diane Ramsden, Senior Director of DMPK and Toxicology at Korro Bio and Stephanie Piekos, PhD, Principal Scientist at Boehringer Ingelheim, will present complementary findings that address two key translational gaps using TruVivo®, LifeNet Health’s all-human 2D+ hepatic system.

Diane Ramsden will discuss new strategies for improving in vitro assessment of enzyme and transporter induction beyond CYP3A. She will also demonstrate how this system enables the evaluation of complex DDIs, including simultaneous induction and inhibition, allowing for better estimations of clinically relevant interactions.

Stephanie Piekos will highlight the model’s utility for intrinsic clearance prediction of substrates for aldehyde oxidase (AO). Through sustained enzyme activity over extended culture periods, the platform enables improved characterization of AO-mediated metabolism, which is often underpredicted in conventional systems. Together, the presentations offer a cohesive perspective on how hepatocyte cultures with extended-function can enhance both DDI evaluation and metabolic clearance prediction within a unified framework.

Key Takeaways

• Improved Induction Prediction Across Multiple Pathways: The 2D+ hepatic system demonstrated reproducible induction of key enzymes and transporters, including CYP2C8, CYP2C9, CYP2C19, UGT1A4, CYP3A4, and P-gp, offering broader DDI coverage than traditional hepatocyte monocultures, which often lack sensitivity outside the CYP3A pathway.
• Mechanistic Evaluation of Complex DDIs: The model effectively captured in situ interactions where compounds acted as both inducers and inhibitors. The net effect predictions closely aligned with clinical AUCR data, demonstrating translational value for assessing complex DDI scenarios when using clinically relevant concentrations.
• Quantitative Validation Against Clinical Outcomes: Induction parameters derived from the system enabled accurate in vitro to in vivo extrapolation (IVIVE), with the majority of predictions for CYPs, UGT1A4, and P-gp falling within accepted thresholds – supporting its utility for prospective DDI risk assessment.
• Improved Characterization of AO-Mediated Metabolism: Aldehyde oxidase, a key Phase I enzyme notoriously difficult to study in conventional in vitro or animal models, exhibited higher and more stable activity in TruVivo hepatic system,enabling improved extrapolation to metabolism in humans .
• Accurate Clearance Predictions for Low-Turnover AO Substrates: For compounds where AO contributes substantially to metabolism, data generated in TruVivo resulted in hepatic clearance estimates within ~2-fold of clinical values, providing an improved method for early prediction of human pharmacokinetics for drugs exhibiting AO-mediated metabolism.