title: Combining Nonclinical Experiments with Translational PKPD Modeling to Differentiate Erlotinib and Gefitinib.
abstract: 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 pharmacologic and antitumor 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 with 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 a 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 PK 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. Mol Cancer Ther; 15(12); 3110-9. ©2016 AACR.
authors.affiliation: Roche Pharma Research and Early Development, Quantitative Systems Pharmacology, Pharmaceutical Sciences Roche Innovation Centre Basel, Hoffmann-La Roche Ltd., Basel, Switzerland. miro.eigenmann@roche.com.
authors.forename: Miro J
authors.initials: MJ
authors.lastname: Eigenmann
authors.affiliation: Roche Pharma Research and Early Development, Quantitative Systems Pharmacology, Pharmaceutical Sciences Roche Innovation Centre Basel, Hoffmann-La Roche Ltd., Basel, Switzerland.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Frances
authors.affiliation: Project Leaders and M&S, Pharmaceutical Sciences Roche Innovation Centre Basel, Hoffmann-La Roche Ltd., Basel, Switzerland.
authors.forename: Gerhard
authors.initials: G
authors.lastname: Hoffmann
authors.affiliation: Project Leaders and M&S, Pharmaceutical Sciences Roche Innovation Centre Basel, Hoffmann-La Roche Ltd., Basel, Switzerland.
authors.forename: Thierry
authors.initials: T
authors.lastname: Lavé
authors.affiliation: Roche Pharma Research and Early Development, Quantitative Systems Pharmacology, Pharmaceutical Sciences Roche Innovation Centre Basel, Hoffmann-La Roche Ltd., Basel, Switzerland.
authors.forename: Antje-Christine
authors.initials: AC
authors.lastname: Walz
mesh_terms: D000465:Algorithms; D000818:Animals; D000970:Antineoplastic Agents / Q000493:pharmacokinetics*; D015415:Biomarkers; D002453:Cell Cycle / Q000187:drug effects; D045744:Cell Line, Tumor; D049109:Cell Proliferation / Q000187:drug effects; D004195:Disease Models, Animal; D000069347:Erlotinib Hydrochloride / Q000493:pharmacokinetics*; D005260:Female; D000077156:Gefitinib; D006801:Humans; D051379:Mice; D008954:Models, Biological; D047428:Protein Kinase Inhibitors / Q000493:pharmacokinetics*; D011799:Quinazolines / Q000493:pharmacokinetics*; D023041:Xenograft Model Antitumor Assays
chemical_list: D000970:Antineoplastic Agents; D015415:Biomarkers; D047428:Protein Kinase Inhibitors; D011799:Quinazolines; D000069347:Erlotinib Hydrochloride; D000077156:Gefitinib