Population pharmacokinetics and exposure-response of osimertinib in patients with non-small cell lung cancer

Abstract

Aims: To develop a population (pop) pharmacokinetic (PK) model for osimertinib (AZD9291) and its metabolite (AZ5104) and investigate the exposure-response relationships for selected efficacy and safety parameters.

Methods: PK, safety and efficacy data were collected from two non-small cell lung cancer (NSCLC) patient studies (n = 748) and one healthy volunteer study (n = 32), after single or multiple once-daily dosing of 20-240 mg osimertinib. Nonlinear mixed effects modelling was used to characterise the popPK. Individual exposure values were used to investigate the relationship with response evaluation criteria in solid tumours (RECIST 1.1) efficacy parameters and key safety parameters (rash, diarrhoea, QTcF).

Results: A popPK model that adequately described osimertinib and its metabolite AZ5104 in a joint manner was developed. Body weight, serum albumin and ethnicity were identified as significant covariates on PK in the analysis, but were not found to have a clinically relevant impact on osimertinib exposure. No relationship was identified between exposure and efficacy over the dose range studied. A linear relationship was observed between exposure and the occurrence of rash or diarrhoea, and between concentration and QTcF, with a predicted mean (upper 90% confidence interval) increase of 14.2 (15.8) ms at the maximum concentration for an 80 mg once-daily dose at steady state.

Conclusions: PopPK and exposure-response models were developed for osimertinib and AZ5104. There was no relationship between exposure and efficacy but a linear relationship between exposure and safety endpoints (rash, diarrhoea and QTcF) was observed.

Keywords: Drug safety; Modelling and Simulation; Patient safety; Pharmacodynamics; Pharmacokinetics.

Figure 1

General goodness‐of‐fit for osimertinib from the final population pharmacokinetics model (LOESS smoothing line as solid line)

Figure 2

Observed response probabilities (with 95% confidence interval as vertical bars) and model prediction based on osimertinib AUC_ss. AUC_ss = area under the concentration–time curve at steady‐state conditions for a 24‐h dosing interval. Note: The points are observed response probabilities in categories of osimertinib AUC_ss, created from 8 quantiles of AUC_ss (with probability = 0.125); the continuous line is the model prediction. The right panel shows the model‐prediction including 95% confidence interval on the prediction as dashed lines. The vertical lines in both panels show the mean (5^th–95^th percentiles) for osimertinib AUC_ss in patients receiving 80‐mg osimertinib; 12 802 (5524–26 140) nmol l^–1. h

Figure 3

Observed probabilities and model prediction of rash (top panel) and diarrhoea (bottom panel). AUC_ss = area under the plasma concentration–time curve during any dosing interval at steady state; CI = confidence interval. Note: Categories of osimertinib AUC_ss were created from 8 quantiles of AUC_ss (with equal probability = 0.125); the continuous line is the model prediction. The right panel shows the model prediction including 90% CI (dashed lines) on the prediction. The vertical lines show the mean (5^th–95^th percentiles) of osimertinib AUC_ss in patients receiving 80 mg osimertinib: 12 802 (5524–26 140) nmol l^–1. h

Figure 4

Scatterplot of ΔQTcF vs. plasma concentration of osimertinib with the fitted regression line obtained with the linear mixed effects model