(S-079) Osimertinib optimal dosing through population pharmacokinetics in virtual patients with NSCLC
Sunday, October 19, 2025
7:00 AM - 5:00 PM MDT
Location: Colorado A
Minjung Chang, Associate professor – Department of Pharmacy – College of Pharmacy, Yonsei University, Republic of Korea; Hye eun Kim, M.S. – Graduate Program of Industrial Pharmaceutical Science – College of Pharmacy, Yonsei University, Republic of Korea; Kyongkuk Ryu, M.S. – Department of Pharmacy – College of Pharmacy, Yonsei University, Republic of Korea; Heungjo Kim, Ph.D candidate – Department of Pharmaceutical Medicine and Regulatory Sciences – College of Pharmacy, Yonsei University, Republic of Korea; Hongjae Lee, Ph.D candidate – Department of Pharmaceutical Medicine and Regulatory Sciences – College of Pharmacy, Yonsei University, Republic of Korea
Ph.D candidate College of Pharmacy, Yonsei University, Republic of Korea
Disclosure(s):
Jiwoo Lim: No financial relationships to disclose
Objectives: To delineate the pooled population pharmacokinetic profile of osimertinib in virtual patients with NSCLC and to evaluate the relevance of the pharmacokinetic model for patient characteristics and clinical status.
Methods: This is a model-based meta-analysis (MBMA) to investigate the population pharmacokinetics (popPK) of osimertinib in patients with non-small cell lung cancer (NSCLC). Using the final popPK model from each selected study, a virtual cohort of 1,000 patients per study was generated, resulting in a total virtual population of 4,000 individuals. Studies included diverse patient demographics and clinical conditions, with exclusion of those involving concomitant administration of agents from the same drug class to minimize confounding. Plasma concentration–time data were simulated using the mrgsolve R package. Demographic data were normalized, and virtual patients were randomly assigned to test (80%) and validation (20%) sets for internal validation. Simulations employed a two-compartment model structure with a once-daily 80 mg dosing for 19 days to achieve steady-state. Continuous covariates such as body weight and serum albumin were standardized using reported ranges, while sex proportions were retained as originally described. When only BMI was reported, weight was estimated using population-specific anthropometric data. The diverse characteristics of the virtual cohort support the model's applicability to real-world clinical scenarios.
Results: Ultimately, four studies were selected, two of which incorporated pharmacokinetic (PK) models that included both the parent compound and its metabolite, while the remaining two included models for the parent compound only. A two-compartment model best described the popPK of osimertinib, and higher body weight and lower serum albumin levels were associated with reduced drug exposure. Simulation results indicated that a once-daily dose of 80 mg osimertinib would effectively maintain plasma concentrations within the therapeutic range while minimizing exposure-related adverse effects, regardless of body weight or albumin level.
Conclusions: This study developed a robust popPK model of osimertinib in patients with NSCLC using a virtual patient cohort. The results showed comparable performance between the test and validation sets, suggesting minimal overfitting and adequate internal validation.
It reinforces the suitability of osimertinib as a first-line therapeutic option in NSCLC and underscores the relevance of body weight and serum albumin concentrations as significant covariates affecting its pharmacokinetics. The proposed model may facilitate the refinement of individualized dosing regimens and contribute to the advancement of precision therapeutic strategies for osimertinib. To ensure the generalizability and clinical utility of this approach, subsequent studies employing model-based meta-analyses (MBMA) across a broader spectrum of pharmacological agents and indications are encouraged.
Citations: [1]Brown K, Comisar C, Witjes H, et al. Population pharmacokinetics and exposure-response of osimertinib in patients with non-small cell lung cancer. Br J Clin Pharmacol. 2017;83(6):1216-1226. doi:10.1111/bcp.13223 [2]Rodier T, Puszkiel A, Cardoso E, et al. Exposure-Response Analysis of Osimertinib in Patients with Advanced Non-Small-Cell Lung Cancer. Pharmaceutics. 2022;14(9):1844. Published 2022 Sep 1. doi:10.3390/pharmaceutics14091844 [3]Agema BC, Veerman GDM, Steendam CMJ, et al. Improving the tolerability of osimertinib by identifying its toxic limit. Ther Adv Med Oncol. 2022;14:17588359221103212. Published 2022 Jun 3. doi:10.1177/17588359221103212 [4]Ishikawa E, Yokoyama Y, Chishima H, et al. Population Pharmacokinetics, Pharmacogenomics, and Adverse Events of Osimertinib and its Two Active Metabolites, AZ5104 and AZ7550, in Japanese Patients with Advanced Non-small Cell Lung Cancer: a Prospective Observational Study. Invest New Drugs. 2023;41(1):122-133. doi:10.1007/s10637-023-01328-9