(M-054) Population pharmacokinetics and exposure-safety analysis of SGN-STNV (PF-08046055) in patients with locally advanced and/or metastatic solid tumors: Phase-1a/b study
Monday, October 20, 2025
7:00 AM - 5:00 PM MDT
Location: Colorado A
Hossam Kadry – Pharmacometrics and Systems Pharmacology, Translational Clinical Sciences – Pfizer Inc; Sujit Biswas – Clinical Pharmacology & Translational Sciences, Pfizer Oncology Division – Pfizer Inc.; John Harrold – Pharmacometrics and Systems Pharmacology, Translational Clinical Sciences – Pfizer Inc.; Vaishali Chudasama – Clinical Pharmacology & Translational Sciences, Pfizer Oncology Division – Pfizer Inc.
Clinical Pharmacologist Pfizer Inc. Mill Creek, Washington, United States
Disclosure(s):
Sujit Biswas: No financial relationships to disclose
Objectives: SGN-STNV is an investigational antibody–drug conjugate (ADC) comprising the humanized monoclonal antibody (anti-STn) linked to cytotoxic monomethyl auristatin E (MMAE). SGN-STNV was evaluated for establishing safe dose and schedule in patients with advanced solid tumors expressing Thomsen-nouvean antigen (STn). The objective of the current analysis is to develop population pharmacokinetic (PK) and exposure-response models to quantify sources of PK variability and relationships between exposure and safety end points.
Methods: The PK data from the phase 1 study (NCT04665921) were collected from 106 patients with various advanced level solid tumors across five dose levels ranging from 0.75-2.25 mg/kg and four schedules (QW, 3Q4W, 2Q3W, or 2Q4W) following total body weight (TBW) or adjusted ideal body weight (AIBW) dosing strategy. Nonlinear mixed-effects modeling with the first order conditional estimation method (NONMEM 7.5) was used to analyze acMMAE (antibody conjugated drug) concentrations following intravenous administration of SGN-STNV. Clinically relevant patient specific baseline characteristics were explored to explain the interindividual variability of key PK parameters. Final PK parameters were used to simulate exposures based on TBW and AIBW. Exposure – safety analysis was performed in R (Core Team, Vienna, Austria, version 4.1.2) using individual predicted acMMAE average concentration up to the event obtained from PopPK model.
Results: A two-compartment model with linear elimination reasonably described the observed acMMAE concentrations and parameters were estimated with good precision (%CV < 25). The estimated clearance (CL) and volume of distribution (V) in the central compartment were 1.27 L/day and 3.03 L, respectively. Intercompartmental clearance and peripheral volume were estimated to be 0.7 L/day and 2.27 L, respectively. Among commonly identified covariates, BW was identified to be a significant covariate on both CL and V reduced interindividual variability from 29.7% to 23.5% for CL and from 21.2% to 17.6% for V. Model simulations suggested AIBW dosing strategy reduced exposure of higher BW/BMI subjects and minimized interindividual variability across patient population, consistent with observed exposures. Exposure-safety analysis showed higher acMMAE exposures are associated with higher rate of observed safety events, Grade ≥3 TRAE and Grade ≥2 PN.
Conclusions: The final Population PK model was able to reasonably characterize acMMAE PK data from SGN-STNV across different dose and schedules for all subjects with BW being the significant covariate. Higher exposures correlated with higher rate of safety events and were tolerated with appropriate dose modifications. AIBW-based dosing was predicted to provide consistent exposures across a range of BW and reduced exposure driven safety events.
