Abstract A140: A physiologically based pharmacokinetic modeling approach for predicting the exposure of irinotecan and its active metabolite (SN-38) in cancer patients

Abstract

Abstract Introduction: Irinotecan is an inhibitor of the topoisomerase I enzyme that is essential in DNA transcription, replication, and repair. It is considered a “backbone” regime in colorectal cancer in adults and in pediatric gliomas to which other antineoplastic agents are added to improve the outcome. It is used as well in the treatment of many other types of adult and pediatric cancers. Irinotecan acts as a prodrug of SN-38 which has approximately 100-1000-fold greater cytotoxic activity. The metabolic and pharmacokinetic behavior of irinotecan is very complex and currently not completely elucidated. Clinical data have shown high variability in treated patients in the efficacy, toxicity, and pharmacokinetic profile of the drug. To increase safety and efficacy, a physiologically based pharmacokinetic modeling (PBPK) approach was used to predict the optimal dose for treatment initiation. Methods: Clinical data were used in combination with measured physicochemical and blood-binding data to inform the model. Hence a middle-out approach was used to build the parent model for a population of adult cancer patients. While the default Sim-Cancer population available within the Simcyp Simulator (v21) was used, the unbound fraction in plasma for the healthy population was incorporated into the PBPK model. By using the reverse translational tool and a retrograde approach, the irinotecan metabolism was described by incorporating CYP3A (Km 14.4±1.6 μM, Vmax 14.7± 0.6 pmol/min/mg protein) and an additional clearance. This additional clearance was then explained by scaled esterases (CES1 and CES2) enzyme kinetic from in vitro data. Besides the clinical study that was used to build the model, other independent intravenously administered irinotecan studies were used for verification. Results: The model predicted the plasma concentration of the parent drug and its metabolite (SN-38) in good agreement with observed data from the clinical study that was used to build the model, as well as from several clinical studies that were not used to build the initial model, covering a dose range of 50-750 mg/m2. Conclusion: We developed a PBPK model that accurately predicts the pharmacokinetic behavior of irinotecan and its metabolite (SN-38) in an adult cancer population. Future directions involve the adaption of the model to the pediatric cancer population to predict the optimal dose for initiation of first-in-human Phase I studies and to identify potential drug interactions and unanticipated toxicities when this “backbone” regimen is combined with other investigated anticancer agents. This will then lead to an increase in individualized treatment. Citation Format: Kristina Zoran Denic, Sibylle Neuhoff, Joel Reid, Rachel Kudget. A physiologically based pharmacokinetic modeling approach for predicting the exposure of irinotecan and its active metabolite (SN-38) in cancer patients [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A140.