PI-036 - POPULATION PHARMACOKINETIC MODELING OF SUNITINIB AND SU12662 IN PATIENTS WITH SOLID TUMORS

J. Piscitelli¹, R. Khosravan²; ¹Pfizer, Inc., San Diego, CA, USA, ²Arcus Biosciences, Hayward, CA, USA.

Background: Sunitinib is a multi-targeted tyrosine kinase inhibitor used in the treatment of advanced renal cell carcinoma, imatinib-resistant/intolerant gastrointestinal stromal tumors, and progressive, well-differentiated pancreatic neuroendocrine tumors. In addition to the cancer types in which sunitinib is approved for, the pharmacokinetics (PK) have also been evaluated in breast cancer, non-small cell lung cancer, prostate cancer, hepatocellular carcinoma, and gastric cancer. The objectives of this analysis were to describe the population pharmacokinetics (popPK) of sunitinib, and its active metabolite across all cancer types, and evaluate potential covariates that may be important predictors of sunitinib or SU12662 PK.

Methods: Data from 16 clinical studies and eight different tumor types were included in this analysis. the first-order conditional estimation method with interaction method was used (NONMEM v 7.5.0, Icon, Dublin Ireland) for the development of both models. Based upon pre-clinical observations, a conversion of 21% of the total parent to metabolite was assumed to bring the magnitude of the parameters to a more physiologically relevant level. For sunitinib, bioavailability was a function of fraction absorbed only, whereas for SU12662, bioavailability was a function of the fraction absorbed as well as the fraction of sunitinib metabolized to SU12662.

Results: A 2-compartment model with first order absorption and lag time described the pooled clinical PK data for sunitinib (8,712 concentrations from 1198 subjects) well. The same structural model was used for SU12662, however no lag time was implemented. For the sunitinib model, CL/F and V2/F were estimated to be 35.7 L/h and 2230 L, respectively. For the SU12662 model, CL/F and V2/F were estimated to be 18.3 L/h and 2310 L, respectively. The covariates found to have a statistically significant (α=0.001) effect on either CL/F or V2/F across both models included age, sex, body weight, race, and tumor type. However, none of these covariates was deemed to have a clinically significant impact.

Conclusion: These popPK models adequately described the plasma PK of sunitinib and SU12662 across all tumor types. The results of this analysis, suggest that disposition of sunitinib and its active metabolite is similar across multiple tumor types.