(M-020) Assessment of Drug-Drug Interaction Effect of Gastric Acid Reducing Agents on Lazertinib Exposure in EGFR-Mutated Non-Small Cell Lung Cancer

Dandan Luo – Janssen Research & Development; Yaming Su – Janssen Research & Development; Jaydeep Mehta – Janssen Research & Development; Seong Bok Jang – Yuhan Corporation; Pamela Clemens – Janssen Research & Development; Nahor Haddish-Berhane – Janssen Research & Development; Mahesh Samtani – Janssen Research & Development

Objectives: Lazertinib is an oral epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that is approved in combination with amivantamab for first-line treatment of patients with EGFR-mutated non-small cell lung cancer (NSCLC) [1]. Lazertinib is a weak base and exhibits pH-dependent solubility across physiological pH range. Given lazertinib is available as orally administered tablets, it is requisite to understand whether co-administration of acid-reducing agents (ARAs) can alter the solubility of lazertinib in gastrointestinal tract, consequently changing pharmacokinetics (PK) of lazertinib. As an alternative to a dedicated clinical DDI study, the objective of this analysis was to evaluate the DDI effects of co-administration of ARAs on lazertinib PK using a population PK approach.

Methods: To assess the effect of ARAs on the PK of lazertinib, dosing records of proton pump inhibitors and/or H2 receptor antagonists co administered with lazertinib were obtained from Studies 73841937NSC3003, 61186372EDI1001, 73841937NSC1001, YH25448-201, and YH25448-301 in NSCLC participants. Since the acid reducing effect manifests several days post ARA administration and there could be non negligible inter subject variability for this delayed onset of medication, analyzing ARAs effect as a time-varying covariate in NONMEM® is challenging. Hence, the simulated lazertinib PK exposure (steady state AUC0-24h.ss and Cmax.ss at 240 mg once daily using the post-hoc individual PK parameters) was compared using multivariate regression analysis in subpopulations with different ARAs taken status (ie., ARAs taken throughout lazertinib PK follow-up period, and no ARA taken) with the potential impact from glutathione S-transferase mu 1 (GSTM1) status considered. Additionally, subjects with co-administration of ARAs throughout lazertinib PK follow-up period were matched to those without ARA use via propensity score matching aiming to obtain a balanced covariate distribution (weight, sex, and GSTM1 genotype) between the two groups. This propensity score matching method involved calculating the conditional probability of being in the treated group given a set of covariates, and the output of matching was two groups with fairly well balanced covariate distribution. Then the simulated lazertinib PK exposure was compared between the matched two groups using the standard regression analysis.


Results: Multivariate regression analysis showed that the geometric mean ratio and associated 90% confidence interval (GMR, 90% CI) of AUC0-24h.ss and Cmax,ss for subjects with ARAs taken throughout lazertinib PK follow-up period (n=191) versus no ARA taken (n=890) were 0.934 (0.884-0.987) and 0.888 (0.846-0.931), respectively. Using the propensity score matching approach, GMR (90% CI) of AUC0 24h.ss and Cmax,ss between matched groups (ARAs throughout lazertinib PK follow-up period versus no ARA) were 1.02 (0.873-1.19) and 0.963 (0.844-1.10), respectively.

Conclusions: Collectively, the current analyses demonstrated that the concomitant use of ARAs had no clinically meaningful effect on lazertinib PK. Propensity score matching approach confirmed the findings from the standard multivariate regression approach.

Citations: [1] FDA. FDA approves lazertinib with amivantamab-vmjw for non-small lung cancer. https://www.fda.gov/drugs/resources-information-approved-drugs/fda-approves-lazertinib-amivantamab-vmjw-non-small-lung-cancer

Keywords: Lazertinib, DDI, Propensity score matching