Pharmacokinetic-Pharmacodynamic Modeling of Biomarker Response and Tumor Growth Inhibition to an Orally Available Heat Shock Protein 90 Inhibitor in a Human Tumor Xenograft Mouse Model

Abstract

PF04942847 [2-amino-4-{4-chloro-2-[2-(4-fluoro-1H-pyrazol-1-yl)ethoxy]-6-methylphenyl}-N-(2,2-difluoropropyl)-5,7-dihydro-6H-pyrrolo [3,4-d]pyrimidine-6-carboxamide] was identified as an orally available, ATP-competitive, smallmolecule inhibitor of heat shock protein 90 (HSP90). The objectives of the present study were: 1) to characterize the pharmacokinetic-pharmacodynamic relationship of the plasma concentrations of PF04942847 to the inhibition of HSP90-dependent protein kinase, AKT, as a biomarker and 2) to characterize the relationship of AKT degradation to tumor growth inhibition as a pharmacological response (antitumor efficacy). Athymic mice implanted with MDA-MB-231 human breast cancer cells were treated with PF04942847 once daily at doses selected to encompass ED 50 values. Plasma concentrations of PF04942847 were adequately described by a two-compartment pharmacokinetic model. A time delay (hysteresis) was observed between the plasma concentrations of PF04942847 and AKT degradation; therefore, a link model was used to account for the hysteresis. The model reasonably fit the time courses of AKT degradation with the estimated EC 50 of 18 ng/ml. For tumor growth inhibition, the signal transduction model reasonably fit the inhibition of individual tumor growth curves with the estimated EC 50 of 7.3 ng/ml. Thus, the EC 50 for AKT degradation approximately corresponded to the EC 50 to EC 80 for tumor growth inhibition, suggesting that 50% AKT degradation was required for significant antitumor efficacy (50 -80%). The consistent relationship between AKT degradation and antitumor efficacy was also demonstrated by applying an integrated signal transduction model for linking AKT degradation to tumor growth inhibition. The present results will be helpful in determining the appropriate dosing regimen and guiding dose escalation to achieve efficacious systemic exposure in the clinic.

Pharmacokinetic-pharmacodynamic modeling of the anticancer effect of erlotinib in a human non-small cell lung cancer xenograft mouse model

“…The IDR model used here assumes that the rate of the onset and offset of the pEGFR levels is governed by the indirect mechanism of action, ie, inhibition of formation (K in ), because erlotinib blocks the formation of pEGFR. The model reasonably described the PK/PD relationship of the plasma concentration and pEGFR inhibition as well as provided the best fit to the observed biomarker data other than the effect compartment model (data not shown), the latter model is usually used to describe the delayed response due to delayed drug distribution [13,27] .…”

“…A similar study on PF04942847, an HSP90 inhibitor, that used Akt as a biomarker showed that 30% inhibition of Akt is required for 50% tumor growth inhibition [27] . Thus the comparison of the PD parameters estimated from different models could be a reasonable approach to predict a clinical response.…”

“…First, the linear link of pEGFR inhibition 1435 www.chinaphar.com Wu Q et al Acta Pharmacologica Sinica npg to tumor volume can not explain the occurrence of nonlinearities caused by drug resistance and either active or saturable processed in the systems. Yamazaki et al provided an E max model to describe the quantitative relationship between PD biomarkers and tumor growth and to investigate this complex PK/PD relationship, more study designs are required to explain the nonlinear aspect of the relationship [27] . Second, the pEGFR inhibitor erlotinib might inhibit tumor growth through a variety of additional biomarker responses.…”

“…Therefore, it has been proposed that the growth of the tumor was slowed at the rate of X 1 /VOL [26] , and a constant parameter K bio proportional to E·X 1 was applied to describe the antitumor effect of pEGFR. Here, a pEGFR "inhibition index" E [E=1/(pEGFR/pEGFR 0 )-1] was used as the variable describing the pEGFR inhibition as reported [27] . The equation is shown as Eq 5, and the block diagram is shown in Figure 1.…”

Pharmacokinetic-pharmacodynamic modeling of the antitumor effect of TM208 and EGFR-TKI resistance in human breast cancer xenograft mice

“…The natural growth of the tumor can be described by an exponential phase followed by a linear growth phase, eventually reaching a plateau [28] ,…”