Prediction of trough concentration and ALK occupancy in plasma and cerebrospinal fluid using physiologically based pharmacokinetic modeling of crizotinib, alectinib, and lorlatinib

• Published in: Frontiers in pharmacology Vol. 14; p. 1234262
• Main Authors: Li, Bole, Liu, Shan, Feng, Honglei, Du, Chunshuang, Wei, Liman, Zhang, Jie, Jia, Guangwei, Wu, Chunnuan
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 2023
• Subjects: ALK inhibitors; ALK occupancy; concentration prediction in cerebrospinal fluid; optimal dosing regimen; PBPK model; ALK inhibitors; concentration prediction in cerebrospinal fluid; ALK occupancy; PBPK model; optimal dosing regimen
• ISSN: 1663-9812; 1663-9812
• DOI: 10.3389/fphar.2023.1234262

Backgrounds: Brain metastases occur in approximately 30% of patients with non-small-cell lung cancer (NSCLC). Therefore, the free drug concentration in cerebrospinal fluid (CSF) is strongly associated with the clinical efficacy. Purpose: The present study aimed to develop physiologically based pharmacokinetic (PBPK) models that can predict the steady-state trough concentration (C trough ) in plasma and CSF, as well as anaplastic lymphoma kinase (ALK) occupancy (AO), for three inhibitors: crizotinib (CRI), alectinib (ALE), and lorlatinib (LOR). Methods: To achieve this, population PBPK models were successfully developed and validated using multiple clinical pharmacokinetics (PK) and drug–drug interaction (DDI) studies, both in healthy subjects and patients. Results: The prediction-to-observation ratios for plasma AUC, C max , and C trough in heathy subjects and patients ranged between 0.5 and 2.0. In addition, PK profiles of CRI, ALE, and LOR in CSF aligned well with observed data. Moreover, the AUC and C max ratios of the three inhibitors when co-administered with CYP3A4 inhibitors/inducers also matched with clinically observed values. Utilizing PK thresholds for effective plasma C trough and AO values on wild-type and four ALK mutations in plasma and CSF, PBPK models were then combined with the mean and 95% confidence interval to predict optimal dosing regimens. Conclusions: Overall, these PBPK models provide valuable insights into determining appropriate dosing regimens for the three ALK inhibitors, understanding their effectiveness in brain metastasis therapy, and analyzing the underlying mechanisms of on-target resistance.