PKPD Modeling of VEGF, sVEGFR-2, sVEGFR-3, and sKIT as Predictors of Tumor Dynamics and Overall Survival Following Sunitinib Treatment in GIST

The predictive value of longitudinal biomarker data (vascular endothelial growth factor (VEGF), soluble VEGF receptor (sVEGFR)-2, sVEGFR-3, and soluble stem cell factor receptor (sKIT)) for tumor response and survival was assessed based on data from 303 patients with imatinib-resistant gastrointestinal stromal tumors (GIST) receiving sunitinib and/or placebo treatment. The longitudinal tumor size data were well characterized by a tumor growth inhibition model, which included, as significant descriptors of tumor size change, the model-predicted relative changes from baseline over time for sKIT (most significant) and sVEGFR-3, in addition to sunitinib exposure. Survival time was best described by a parametric time-to-event model with baseline tumor size and relative change in sVEGFR-3 over time as predictive factors. Based on the proposed modeling framework to link longitudinal biomarker data with overall survival using pharmacokinetic-pharmacodynamic models, sVEGFR-3 demonstrated the greatest predictive potential for overall survival following sunitinib treatment in GIST.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e84; doi:10.1038/psp.2013.61; advance online publication 20 November 2013.

Exposure-response of sunitinib in metastatic renal cell carcinoma (mRCC): A population pharmacokinetic/pharmacodynamic (PKPD) approach

5027

Background: Sunitinib malate (SU) is an oral, multitargeted tyrosine kinase inhibitor of VEGFRs and PDGFRs, and has shown substantial antitumor activity in mRCC (Motzer et al, JAMA 2006 and ASCO 2006). This analysis describes SU, and total drug (TD; SU+SU12662 [active metabolite]) exposure-response relationships in mRCC using a population PKPD approach. Methods: PK and efficacy data from 3 studies (phase II and III) of SU (25–62.5 mg/day; 4 wks dosing followed by 2 wks off) in treatment-naïve (N=44) and cytokine-refractory mRCC pts (N=148) were analyzed. SU and SU12662 concentrations were fitted to a population PK model (a 2- compartment model for both parent and metabolite). Estimates of pt PK were used to calculate steady-state Area Under the Curve (AUCss) for SU, SU12662 and TD, which were used as the exposure measure in a PKPD analysis of partial response (PR) rates, time to tumor progression (TTP), overall survival (OS), and tumor volume changes. Results: The probability of a PR for cytokine-refractory pts increased with increasing AUCss for SU and TD. The odds-ratio suggested a 2.6-fold increase in PR frequency for each unit increase in AUCss. Longer TTP and OS were also noted in pts with high SU and TD AUCss. In treatment-naïve pts on SU, there was very little observed tumor progression or death (only 5 pts progressed and only 1 death) limiting the ability to analyze exposure-response. A tumor growth dynamics model (developed to describe changes in tumor volume [by CT or MRI] in response to treatment, as a function of AUCss) provided a good description of tumor volume changes with SU for both treatment-naïve and cytokine-refractory pts. Efficacy was not related to baseline tumor volume, gender, or race. Based on this model, clinical trial simulations assuming perfect pt compliance predict that 62% of pts would achieve a PR with SU 50 mg/day. Conclusions: SU and TD AUCss correlated significantly with the probability of a PR in cytokine- refractory pts, and longer TTP and OS. Limited data were available for treatment-naïve pts. The tumor growth dynamics model provided a good description of tumor volume changes with SU for both populations. This exposure-response analysis indicates that increased exposure to SU is associated with clinical benefit.

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Pharmacokinetics (PK) and efficacy of sunitinib in patients with metastatic renal cell carcinoma (mRCC)

4531

Background: Sunitinib malate (SU11248) is an oral, multi-targeted tyrosine kinase inhibitor of VEGFR, PDGFR, KIT, FLT3, and RET. Clinical studies have demonstrated efficacy of sunitinib in patients with multiple tumor types including two phase II studies in mRCC, where second-line monotherapy with sunitinib showed a response rate of greater than 40% by RECIST, with an additional ≥25% of pts exhibiting prolonged stable disease. A population PK analysis was performed to assess the exposure-response relationship between PK and tumor volume changes, clinical response, and time to tumor progression (TTP) in these two mRCC studies. Methods: In these two studies, 169 patients with mRCC were treated with sunitinib 50 mg/day for 4 weeks, followed by a 2-week off period (Schedule 4/2). Response to treatment was assessed by measuring tumor volume. Clinical response was assessed using RECIST and TTP using logistic regression and Kaplan-Meier survival analysis. A previously described population PK model of sunitinib and its primary active metabolite SU12662 was updated using additional data from three trials, including the two RCC trials. Using the model and trough plasma concentrations, steady-state AUCs of sunitinib plus SU12662 were estimated for each mRCC patient and tested as a predictor of response. Results: PK profiles were evaluable for 149 patients in the two mRCC trials. Plasma clearance (CL) decreased by an average of 28% in mRCC patients relative to healthy volunteers. Covariates, such as gender, age, and ECOG score also affected CL, however all of these changes were less than the estimated inter-individual variability in CL of 43%. Improved clinical response and longer TTPs were associated with greater AUCs. Within 12 weeks of treatment, mean tumor volume decreased by 24–32% in each trial. Conclusions: Individual patient exposures to sunitinib and SU12662 can be predicted with sparse concentration measurements using population PK analysis, and an exposure-response relationship is evident in mRCC. Dose adjustment is not warranted based upon any evaluated covariate. Over the first 12 weeks of treatment at 50 mg daily on Schedule 4/2, increased exposure was associated with improved clinical response and decreased tumor volumes.

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Pharmacokinetics of plasmid DNA in the rat

PURPOSE

The pharmacokinetics of plasmid DNA after IV bolus administration in the rat by following supercoiled (SC), open circular (OC), and linear (L) pDNA forms of the plasmid.

METHODS

SC, OC, and L pDNA were injected at 2,500, 500, 333, and 250 microg doses. The concentrations in the bloodstream of OC and L pDNA were monitored.

RESULTS

SC pDNA was detectable in the bloodstream only after a 2,500 microg dose, and had a clearance of 390(+/-50) ml/min and Vd of 81(+/-8) ml. The pharmacokinetics of OC pDNA exhibited non-linear characteristics with clearance ranging from 8.3(+/-0.8) to 1.3(+/-0.2) ml/min and a Vd of 39(+/-19) ml. L pDNA was cleared at 7.6(+/-2.3) ml/min and had a Vd of 37(+/-17) ml. AUC analysis revealed that 60(+/-10) % of the SC was converted to the OC form, and nearly complete conversion of the OC pDNA to L pDNA. Clearance of SC pDNA was decreased after liposome complexation to 87(+/-30) ml/min. However the clearance of OC and L pDNA was increased relative to naked pDNA at an equivalent dose to 37(+/-9) ml/min and 95(+/-37) ml/min respectively.

CONCLUSIONS

SC pDNA is rapidly metabolized and cleared from the circulation. OC pDNA displays non-linear pharmacokinetics. Linear pDNA exhibits first order kinetics. Liposome complexation protects the SC topoform, but the complexes are more rapidly cleared than the naked pDNA.