Physiologically-based pharmacokinetic (PBPK) modeling is a helpful tool for exploring scenarios that would be difficult or unfeasible to investigate through traditional clinical trials. In this webinar, we highlight how a PBPK model for adagrasib, a covalent inhibitor of the G12C-mutated KRAS protein used to treat non-small cell lung cancer in adults, predicted potential drug-drug interactions (DDIs), provided dosing recommendations, and influenced the adagrasib program and labeling.
Adagrasib is both a substrate and a potent mechanism-based inhibitor (MBI) of cytochrome P450 (CYP) 3A4. As it is subject to auto-inhibition, it’s DDI liability is complex. A PBPK model for adagrasib was developed using Simcyp to capture the available clinical pharmacokinetic (PK) and DDI data in healthy volunteers and patients. The model was then used to predict untested DDI scenarios for the therapeutic dose at steady-state in patients.
The model was also used successfully to predict perpetrator DDI risks and the effects of hepatic impairment on drug exposure.
Key takeaways:
- Value of PBPK Modeling: This example highlights the importance of PBPK modeling to explore untested scenarios, bridge clinical trial data without the need for additional studies, predict potential DDIs, provide dosing recommendations, and ultimately enable adagrasib to reach a larger population of patients.
- Regulatory Impact: The PBPK modeling influenced the adagrasib program and labeling, with the FDA and MHRA accepting the modeling results.
- Model Reusability: Once a PBPK model is developed, it becomes a versatile tool for predicting various scenarios. The adagrasib PBPK model was repurposed to provide insights on the effects of hepatic impairment.
講演者
- Cornelius Cilliers, PhD, Director, Clinical Pharmacology, ORIC Pharmaceuticals
- Hannah Jones, PhD, SVP, Head of Simcyp PBPK Modeling Services, Certara
- Eleanor Howgate, PhD, Director, PBPK Consultancy, Certara
