Combining nonclinical experiments with translational PKPD modeling to differentiate erlotinib and gefitinib

We quantitatively compare the efficacy of two approved EGFR tyrosine kinase inhibitors, erlotinib and gefitinib based on in vivo and in vitro data and show how a modeling approach can be used to scale from animal to humans. Gefitinib shows a higher tumor uptake in cancer patients and we explored the potential impact on pharmacological and anti-tumor activity in in vitro and in xenograft mice. Tumor growth inhibition was monitored and the pharmacokinetics (PK) in plasma and tumor, as well as temporal changes of phospho-Erk (pErk) signals were examined in patient-derived tumor xenograft mice. These data were integrated in a translational PKPD model, allowing us to project an efficacious human dose which we retrospectively compared to prescribed doses for cancer patients. In vitro experiments showed that cell cycle arrest was similar for erlotinib and gefitinib. Similar pERK biomarker responses were obtained despite 6.6-fold higher total tumor exposure for gefitinib. The PKPD model revealed a 3.7-fold higher in vivo potency for gefitinib which did not translate into a lower anticipated efficacious dose in humans. The model-based dose prediction matched the recommended clinical doses well. These results suggest that despite having lower total tumor to plasma ratios, active drug exposure at target site is higher for erlotinib. Considering the pharmacokinetic properties, this translates in a 50% lower recommended daily dose of erlotinib in cancer patients. In summary, total exposure at target site is not suitable to rank compounds, and an integrated modeling and experimental approach can assess efficacy more accurately.