Pharmacometric Analysis in Support of Dose Optimization for Pemigatinib Treatment of Adults with Locally Advanced or Metastatic Cholangiocarcinoma with Fibroblast Growth Factor Receptor 2 (FGFR2) Fusion or Rearrangements
Xiaohua Gong (1), Ayman Akil (2), Andre Ndi (2), Xiang Liu (1), Mark Lovern (2), Xuejun Chen (1)
(1) Incyte Research Institute, Wilmington, DE 19803, USA, (2) Certara Strategic Consulting, Princeton, NJ, USA
Objectives:
The objectives were to characterize the pemigatinib pharmacokinetics (PK) and exposure-response (E-R) relationships to support the dose recommendation for the treatment of cholangiocarcinoma with an Fibroblast Growth Factor Receptor 2 (FGFR2) fusion or rearrangement.
Methods:
A population PK (PPK) model framework was adopted. More than 10 different absorption models were attempted during the base model development. A stepwise covariate modeling procedure was performed at significance levels of 0.05 and 0.005 for forward addition and backward elimination, respectively.
PPK model-predicted posthoc exposures at steady state were used to conduct multivariate E-R analyses, with response endpoints including overall response rate (ORR), progression-free survival (PFS), percent change-from-baseline in serum phosphate, and treatment-emergent adverse events (TEAEs) with ≥10% incidence rate, etc. Continuous endpoints were analyzed using a nonlinear Emax regression framework. Binary endpoints were analyzed using a logistic regression framework. Time-to-event data were analyzed using both Kaplan-Meier method and Cox proportional hazard model.
Results:
The base PPK model was a 2-compartment model with drug dissolution modelled as a zero order process followed by a first-order absorption, a linear elimination, and an additive residual error on the logarithmic scale. Inter-individual variability was estimated for CL/F, Vc/F, Vp/F, Ka, and RT (release time, ie. the duration of zero order process for the study drug released from the pharmaceutical form in the gut). The final PK model included a covariance between inter-individual random effects on CL/F and Vc/F, and the following covariates: sex and the use of phosphate binder on CL/F, sex and the use of proton pump inhibitor (PPI) on Ka, the use of histamine-2 blockers (H2B) on RT, baseline weight on Vc/F and Vp/F. Overall, the model parameters were estimated with good precision (%Relative Standard Error [%RSE] < 19%) except the coefficient on the effect of H2B use on RT, which had %RSE of 38.9% that could be due to the small number of participants in the dataset (39 out of 467) who used H2B. All the statistically significant covariates were not clinically meaningful based on the magnitudes of effects and simulations.
The increase in serum phosphate observed after treatment with pemigatinib was exposure dependent and followed a sigmoidal relationship, with the baseline serum phosphate level as a significant predictor. The relationship between the serum phosphate concentration changes from baseline as well as pemigatinib AUC0-24h at steady state (AUCss) following once daily (QD) treatments and ORR followed a bell shaped relationship, and modeling results support 13.5 mg as an optimal dose for clinical development (1). No statistically significant correlation was observed between PFS and serum phosphate concentration changes from baseline or between PFS and pemigatinib exposures. The clinically notable TEAE of hyperphosphatemia (TEAE with preferred terms of hyperphosphatemia or blood phosphorus increased) were on target TEAEs, with the odds increasing by 9.0% for every 1 mg dose increase of pemigatinib; the incidence rate is predicted around 68% at the therapeutic dose of 13.5 mg QD. Of all other TEAEs evaluated, TEAE with preferred terms of decreased appetite, nausea, and stomatitis were also identified as having a statistically significant association with pemigatinib exposures, but their relationships with pemigatinib exposure were in general shallow with the estimated odds ratios at or below 5.2% for every 1 mg increase in pemigatinib dose.
Conclusions:
- Pemigatinib PK was adequately described by a 2-compartment model with linear elimination, with drug dissolution modelled as a zero order process followed by a first-order absorption, and with inter-individual variability estimated for CL/F, Vc/F, Vp/F, Ka, and RT, and a covariance between inter-individual random effects on CL/F and Vc/F.
- The covariate predictors identified as statistically significant are not considered clinically significant.
- Overall, the E-R analyses, especially the bell-shaped relationships between pemigatinib AUCss or percent change-from-baseline serum phosphate and ORR, support the proposed dosing regimen at 13.5 mg QD oral dose on a 2-weeks-on and 1-week-off regimen.
References:
[1] Zirkelbach JF, et al. J Clin Oncol. 2022;40(30):3489–500