Physiologically based pharmacokinetic model of two ALK inhibitors to inform drug and dosing regimens for brain metastasis patients.

OBJECTIVE: This study developed and verified population Physiologically based pharmacokinetic (PBPK) models for brigatinib (BRI)and lorlatinib (LOR)to predict plasma and cerebrospinal fluid (CSF) pharmacokinetics (PK), assess brain penetration, and optimize dosing for brain metastases (BM). METHODS: Population-based PBPK models were built by integrating in vitro and in vivo data, and verified against independent clinical datasets (plasma/CSF PK, ratio of unbound CSF to plasma concentrations [Kp,CSF], and drug-drug interactions [DDIs]). Sensitivity analysis identified key parameters affecting CSF PK. An ALK engagement ratio (AER) ≥3.0 was applied to assess ALK mutant inhibition across different dosing regimens. RESULTS: The PBPK models accurately predicted plasma concentration-time profiles and plasma/CSF PK parameters, with predicted-to-observed ratios for AUC0-τ,ss, Cmax,SS, and Cmin,SS within the 0.5- to 2.0-fold range. Predicted Kp,CSF and CYP3A4/CYP2C8-mediated DDI outcomes also closely matched clinical data, confirming model reliability. For standard-dose BRI, AER values remained below 3.0, with the exception of that against C1156Y and I1171T. In specific ALK mutations (EML4-ALK, C1156Y, G1269A, and I1171T), mean AER values exceeded the efficacy threshold of 3.0 (red dotted line) under dosing regimens of 240 mg QD or 180 mg BID. For LOR, under the three dosing regimens (50 mg QD, 50 mg BID, and 100 mg QD), the simulated mean AER values against eight mutations exceeded the threshold of 3.0, with the exception of L1196M, G1202R, and I1171N at 50 mg QD. CONCLUSION: These verified PBPK models provide a mechanistic framework for individualized dosing optimization against specific ALK mutations and support using CSF concentrations as a surrogate for brain exposure.