Prediction of Pharmacokinetic Drug–Drug Interactions Involving Anlotinib as a Victim by Using Physiologically Based Pharmacokinetic Modeling

Fengjiao Bu,1,2,* Yong-Soon Cho,3,4,* Qingfeng He,1 Xiaowen Wang,1 Saurav Howlader,3,4 Dong-Hyun Kim,3,4 Mingshe Zhu,5 Jae Gook Shin,3,4 Xiaoqiang Xiang1,6 1Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, People’s Republic of China; 2Department of Pharmacy, Eye and ENT Hospital, Fudan University, Shanghai, People’s Republic of China; 3Department of Pharmacology and Pharmacogenomics Research Center, Inje University College of Medicine, Busan, Republic of Korea; 4Center for Personalized Precision Medicine of Tuberculosis, Inje University College of Medicine, Busan, Republic of Korea; 5Department of DMPK, MassDefect Technologies, Princeton, NJ, USA; 6Department of Preclinical Evaluation, Quzhou Fudan Institute, Quzhou, Zhejiang Province, 324002, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jae Gook Shin; Xiaoqiang Xiang, Email [email protected]; [email protected]: Anlotinib was approved as a third line therapy for advanced non-small cell lung cancer in China. However, the impact of concurrent administration of various clinical drugs on the drug–drug interaction (DDI) potential of anlotinib remains undetermined. As such, this study aims to evaluate the DDI of anlotinib as a victim by establishing a physiologically based pharmacokinetic (PBPK) model.Methods: The PBPK model of anlotinib as a victim drug was constructed and validated in the Simcyp® incorporating parameters derived from in vitro studies, pre-clinical investigations, and clinical research encompassing patients with cancer. Subsequently, plasma exposure of anlotinib in cancer patients was predicted for single- and multi-dose co-administration with typical perpetrators mentioned in Food and Drug Administration (FDA) industrial guidance.Results: Based on predictions, the CYP3A potent inhibitor ketoconazole demonstrated the most significant DDI with anlotinib, regardless of whether anlotinib is administered as a single dose or multiple doses. Ketoconazole increased the area under the concentration-time curve (AUC) and maximum concentration (Cmax) of single-dose anlotinib to 1.41-fold and 1.08-fold, respectively. In contrast, rifampicin, a potent inducer of CYP3A enzymes, exhibited a relatively higher level of DDI, with AUCR and CmaxR values of 0.44 and 0.79, respectively.Conclusion: Based on the PBPK modeling, there is a low risk of DDI between anlotinib and potent CYP3A/1A2 inhibitors, but caution and enhanced monitoring for adverse reactions are advised. To mitigate the risk of anti-tumor treatment failure, it is recommended to avoid concurrent use of strong CYP3A inducers. In conclusion, our study enhances understanding of anlotinib’s interaction with medications, aiding scientists, prescribers, and drug labels in gauging the expected impact of CYP3A/1A2 modulators on anlotinib’s pharmacokinetics. Keywords: anlotinib, DDIs, CYP3A, CYP1A2, PBPK