Eric Wong (1), Luisa RojasChavarro (2), Paul Jones (1), David Egging (1), Wanchana Ungphakorn (2), Marta Valle (2), Ivan Matthews (1)
(1) UCB, (2) Parexel International
Introduction: Ginisortamab, a fully human IgG4 monoclonal antibody with first-in-class potential, neutralizes gremlin-1 and showed antitumor activity in several mouse models, including gastrointestinal cancers. ONC001 (NCT04393298) is an ongoing multi-part, multicenter, non-randomized, open-label, Phase I/II study assessing the safety, pharmacokinetics (PK), pharmacodynamics (PD), and antitumor activity of intravenous (IV) ginisortamab as monotherapy or in combination with selected standard of care regimens in patients with advanced solid tumors. Here we report the PKPD modelling of data from Part A, monotherapy dose escalation, which assesses ginisortamab at 100, 250, 500, 1000 and 2000mg administered by IV infusion every two weeks (Q2W), in patients ≥18 years with advanced disease, resistant or refractory to standard treatment, with performance status of ≤1 on the Eastern Cooperative Oncology Group scale.
Objectives: To characterize the PKPD relationship by performing PKPD modelling of data (ginisortamab and gremlin-1 serum concentrations) from ONC001 Part A and use the PKPD model to perform dosing simulations to support dose selection for later development.
Methods: The population PKPD model was developed following an iterative model building process using a non-linear mixed effects approach. The first-order conditional estimation with interaction (FOCE-I) in NONMEM (version 7.4.4) was employed for all model runs. Covariate analysis, including size covariates, sex, dose, and cancer type, was conducted to explain the variability in ginisortamab and total gremlin-1 serum concentrations. The final validated PKPD model was used to predict ginisortamab serum concentration, total and free gremlin-1 serum concentrations, and target suppression (defined as the percentage reduction in free gremlin-1 serum concentration after dosing versus baseline concentration) following different IV ginisortamab regimens.
Results: A total of 371 ginisortamab serum concentrations and 270 total gremlin-1 serum concentrations were available from 25 patients with different advanced solid tumor types, for model development. Ginisortamab serum concentrations and total gremlin-1 serum concentrations were best described by a two-compartment target-mediated drug disposition model with the binding of ginisortamab to gremlin-1 described by the quasi-steady-state approximation [1]. Inter-individual variability was included on clearance, central volume of distribution (Vc), peripheral volume of distribution (Vp), target degradation rate constant and internalization rate constant. The only statistically significant covariate was body surface area (BSA) (centered at median BSA of 2m2) on Vc and Vp via a power function. All parameters could be estimated with satisfactory precision and their shrinkages were below 29%. The prediction-corrected visual predictive checks of the final PKPD model demonstrated the median, 5th and 95th percentiles of the prediction-corrected observed data were contained within the 95% confidence intervals of the corresponding simulations, validating the predictive performance of the model.
Based on simulations performed using the final model, a dosage regimen of 100 mg Q2W, 250 mg Q2W, 500 mg Q2W, 1000 mg Q2W, 2000 mg Q2W, 1000 mg every one week (Q1W), 3000 mg every three weeks (Q3W) and 4000 mg every four weeks (Q4W) is predicted to produce a median target suppression ≥ 29%, ≥ 51%, ≥ 68%, ≥ 81%, ≥ 89%, ≥ 91%, ≥ 86%, and ≥ 83% over the dosing interval at steady state, respectively. The 1000 mg Q1W and 2000 mg Q2W regimens were predicted to produce a median target suppression close to or above 90% over the dosing interval at steady state.
Conclusions: The population PKPD model adequately describes PK of ginisortamab and binding of ginisortamab to circulating gremlin-1 in patients with advanced solid tumors. Simulations support the potential use of several dose regimens for further evaluation of the efficacy of ginisortamab in patients with advanced solid tumors.
References:
[1] Gibiansky L et al. J Pharmacokinet Pharmacodyn (2008) 35, 573-91
Reference: PAGE 32 (2024) Abstr 10983 [www.page-meeting.org/?abstract=10983]
Poster: Drug/Disease Modelling - Oncology